BLOCKCHAIN: DECENTRALIZATION AS THE FUTURE OF MICROFINANCE AND FINANCIAL INCLUSION

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BLOCKCHAIN: DECENTRALIZATION AS THE
FUTURE OF MICROFINANCE AND FINANCIAL
INCLUSION
MSc. in Sustainability and Social Innovation
Master Thesis
ADVISOR
PhD. Sam Aflaki
STUDENT
CUELLAR BENAVIDES, Jorge Patricio
DECEMBER, 2018

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Abstract
Microfinance has been a buzzword in the realm of economic development ever since Dr.
Muhammad Yunus was awarded the Nobel Peace Prize 2006, due to his efforts in improving the
life of the poorest of the poor by the provision of micro-loans. Despite the proliferation of
Microfinance Institutions (MFIs) over the last two decades, the appearance of micro-loans can be
traced ever since the 1970s when multiple national governments started to provide loans to people
in the agriculture sector or developing small business. Nevertheless, the use of micro-loans as a
mechanism to draw people out of poverty was indeed devised by Yunus with the creation of the
Grameen Bank, and the provision of loans destined to poor entrepreneurs in Bangladesh. Both the
social and financial success that Grameen Bank experienced after its foundation, raise awareness
from multiple NGOs and National Governments, which ultimately replicated or tropicalized
Yunus’ model throughout the developing world.
With the further expansion of MFIs around the globe, the model started having multiple mutations
that have brought a mix of positive and negative outcomes, raising questions about the feasibility
and effectiveness of Microfinance as an economic development tool. Particularly, the rise of MFIs
that have focused on generating profits, instead of having the social goal of economic
empowerment through financial inclusion, has been widely criticized due to multiple controversial
cases that have resulted in multiple suicides and the exacerbation of poverty in entire communities.
Due to the rise of such issues in the sector, various scholars have developed literature that not only
assess the effectiveness of Microfinance as tool of economic development, but also identifies their
main roots. While some of these cases are exclusive to certain countries or institutions, there are
some that can be recognized as structural issues that any financial activity endures, but that
magnifies in the conditions where MF unravels. Elevated operation costs, lack of financial
sustainability and scalability, the presence of heavy information asymmetries, and little
transparency and bad governance have been recalled as some of the most persistent structural
problems behind Microfinance. The rise of digital technologies has brought hope as a corrective
measure that can be more efficient and effective that traditional regulation. Nevertheless,
consensus has yet to be found in terms of which kind of technology and which kind of architecture
could render the best results for the Microfinance sector.

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The Blockchain has been a hot topic over the last years due to the raise in cryptocurrencies,
especially the upward run that bitcoin had in 2017. Ever since, the tech sector has been praising
all the possible implementations that Blockchain could have to revolutionize almost every
industry; an innovation that could be as disruptive as the Internet has been. Regardless all the hype,
skeptics have been questioning the feasibility of such implementations of Blockchain; not only
because something can be done with Blockchain it makes sense to do it. At the end, everything
sums up to the spread between benefits and costs, small incremental gains through Blockchain
technologies do not necessarily help an early development of the infrastructure.
Having this in mind, the motivation to assess the potential of Blockchain technologies in the
Microfinance sphere raises from 2 fundamental aspects exclusive to the Microfinance industry:
1. The information asymmetry between the lenders and the loan holders is way great than in regular
commercial banking. Loan holders are in the lowest percentiles in terms of financial literacy and
banking. Arguably, the precarious education most of the beneficiaries have received leave them in
a vulnerable position when concepts such as contracts, risk, interest rate, insurance, and liability
are exposed to them. The source of asymmetry is structural, even when each element of their loan
is fully transparent, there will always be room for some agents taking advantage of them. At the
same time, Lenders have little or no-information from their beneficiaries since these rarely are
integrated in the mainstream economic or financial sector, hence there are no records to back up
the trustworthiness of such individuals, and most of the income generating activities are highly
variable or seasonal.
2. The capital requirements per transaction are considerably small and, on the contrary, there is a
great number of beneficiaries to attend. The cost of acquiring clients compared to the size of the
loan is drastically higher in Microfinance compared to regular commercial loans. Hence, the high
interest rates for micro-loans. Since the MFIs cannot recover the operation costs directly from fees,
the income from interest payments needs to be as high as possible. Therefore, an efficient and safe
way to manage these transactions could drastically aid both the lenders, with higher benefits by
eliminating or transforming the nature of the middle men, and the loan holders, by having less
interests to pay and mechanisms that can prevent over-leveraging.

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Table of Contents
ABSTRACT ..........................................................................................................................................2
GLOSSARY..........................................................................................................................................6
FINANCIAL INCLUSION AND MICROFINANCE .......................................................................................7
WHAT IS FINANCIAL INCLUSION? ...................................................................................................................... 7
HOW DOES FINANCIAL INCLUSION REDUCE POVERTY? .......................................................................................... 9
FINANCIAL INCLUSION ADVANCEMENTS AND SETBACKS ...................................................................................... 12
MICROFINANCE: FUNDING AND BANKING FOR THE BOTTOM OF THE PYRAMID....................................................... 14
THE EVOLUTION OF THE MICROFINANCE MOVEMENT ........................................................................................ 17
Microfinance before the Grameen Bank ............................................................................................. 17
The Grameen Bank Model................................................................................................................... 17
From the NGO movement to the Commercialization of Microfinance ............................................... 18
CHALLENGES AND SHORTCOMINGS IN MICROFINANCE ....................................................................................... 19
Why 30 years of Microfinance and we still have billions of poor?...................................................... 19
The Operation Costs ............................................................................................................................ 21
Financial Sustainability and Scalability ............................................................................................... 23
Mission Drift: Does Microfinance benefit the Bottom of the Pyramid? .............................................. 26
Information Asymmetry: Adverse Selection and Moral Hazard ......................................................... 29
Transparency and Governance ........................................................................................................... 32
Cases of Abuse from Microfinance Institutions .................................................................................. 33
Information Technologies: Innovative Solutions for Structural Challenges ........................................ 35
BLOCKCHAIN: THE FUTURE FOR TRANSPARENT TRANSACTIONS ........................................................ 37
WHAT IS BLOCKCHAIN? ................................................................................................................................ 37
Elements of the Blockchain and its Implications ................................................................................. 38
BLOCKCHAIN LANDSCAPE .............................................................................................................................. 41
Bitcoin and Cryptocurrencies .............................................................................................................. 41
Ethereum and the Smart-Contracts .................................................................................................... 41
PROSPECTS FOR SOCIAL INNOVATION .............................................................................................................. 42
Remittances and International Payments........................................................................................... 43
Digital Property Registries and Digital Identity for All ........................................................................ 44
Fair-Trade and Ethical Sourcing .......................................................................................................... 46
Reduction of Corruption ...................................................................................................................... 47
BLOCKCHAIN AS A CORRECTION MECHANISM .................................................................................. 48
TRANSPARENCY TO REDUCE THE INFORMATION ASYMMETRY .............................................................................. 50
SELF-REGULATION TO PREVENT MORAL HAZARD. .............................................................................................. 50
REDUCTION OF TRANSACTION COSTS. ............................................................................................................. 51
CHALLENGES FOR BLOCKCHAIN SOLUTIONS ...................................................................................... 52
INTERNET BANDWIDTH REQUIREMENTS ........................................................................................................... 52
THE FRONT-END AS A CENTRAL BOTTLENECK .................................................................................................... 53
VOLUME OF TRANSACTIONS AND COST-EFFICIENCY ........................................................................................... 54
REGULATION AND VALIDATION ....................................................................................................................... 55
RIGIDITY AND PRIVACY ISSUES ........................................................................................................................ 56
EMPIRICAL CASE: EVEREX ................................................................................................................. 57

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HISTORY AND OBJECTIVES ............................................................................................................................. 57
BLOCKCHAIN IMPLEMENTATION THESIS ........................................................................................................... 57
RESULTS AND CHALLENGES ............................................................................................................................ 58
THE FUTURE OF BLOCKCHAIN IN MICROFINANCE .............................................................................. 58
FOR ENTREPRENEURS AND NON-FINANCIAL INSTITUTIONS ................................................................................. 59
FOR INCUMBENT MFIS ................................................................................................................................. 60
FOR GOVERNMENTS AND REGULATORS ........................................................................................................... 61
CONCLUSION ................................................................................................................................... 62
REFERENCES .................................................................................................................................... 63
APPENDIX ........................................................................................................................................ 67

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Glossary
AS
Adverse Selection
BTC
Bitcoin
BT
Blockchain Technology
BOP
Bottom of the Pyramid
DLT
Decentralized Ledger Technology
DM
Desjardins Movement
DAO
Distributed Autonomous Organizations
FD
Financial Development
FI
Financial Inclusion
FS
Financial Stability
FFS
Formal Financial System
GB
Grameen Bank
GDP
Gross Domestic Product
ID
Identification
IA
Information Asymmetry
IT
Information Technology
IMF
International Monetary Fund
IoT
Internet of Things
JLLM
Joint-Liability Lending Method
MFI
Microfinance Institutions
MFM
Microfinance Movement
MENA
Middle East and North Africa
MDG
Millennium Development Goals
MH
Moral Hazard
NGO
Non-Governmental Organizations
P2P
Peer-to-Peer
PoW
Proof-of-Work
SHG
Self-Help Groups
SMEs
Small and Medium Enterprises
SCs
Smart-Contract
SBM
Social Banking Model
SDI
Subsidy Dependence Index
tps
Transaction Per Seconds
UN
United Nations
UNDP
United Nations Development Program
USD
United States Dollar

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Financial Inclusion and Microfinance
What is Financial Inclusion?
Poverty Eradication, a topic that rose throughout the Cold War to become one of the main fields
of study in the Public Policy and one of the 8 Millennium Development Goals (MDGs) dictated
by United Nations Development Program (UNDP). Probably none of the MDGs has been as
diagnosed and analyzed as the Poverty. Nevertheless, while many policies have been prescribed
to eradicate it, and great progress has been achieved (1 billion of poor less from 1982 to 2013),
there is still a long way to go per secure that most of humanity could have a decent standard of
living.
Amongst the multiple causes of poverty, the one that arguably has called the most of attention in
policy makers, think thanks, and humanitarian organizations, has been the lack of inclusion into
the financial system by the people at the Bottom of the Pyramid (BOP). Per Lopez & Winkler
(2018), the Financial Inclusion (FI) has been a major topic in the field of Development Economics
over the last couple of decades (Demirgüç-Kunt and Klapper 2012; Allen et al. 2012; Kumar,
Narain, and Rubbani 2015; Sahay et al. 2015).
The number of people excluded from the financial sector around the globe is just overwhelming.
Per the United Nations (UN), around three billion people in the world lacked access to FFS in
2008, even with the accelerated growth of the sector this number was reduced to reach the two
billion mark in 2014 (Lopez & Winkler, 2018). Amongst the products and services that the FFS
provides, and that those excluded are lacking, there are bank accounts, credit, insurance, saving
accounts, and efficient ways to transfer or receive social benefit payments – through an official
Financial Institution (Chibba, 2008).
Most of the population that lives without access to banking or financial services are suffering from
multiple forms of Social Exclusion, which ultimately end up forming a positive loop that unravels
into a vicious circle; usually a Poverty Trap (Adunda & Kalunda, 2012). Per Kempton et. al (2000),
Social Exclusion is a broad concept that encompasses a combination of linked problems such as
low income, poor housing, persistent unemployment, lack of skills, health issues, high crime
environments, pervasive poverty, and breakdown of the family nucleus. Social exclusion fosters
the social divisions and classes. The people within an acceptable social structure becomes fearful

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of the people in exclusion and the excluded end up resenting the included. This vicious circle
eventually translates into polarized societies that are not desirable for healthy economies or
democracies (Adunda & Kalunda, 2012).
Per Kempson and Whyley (1999, cited by Adunda & Kalunda, 2012), there are six types of
financial exclusion:
1. Physical Access exclusion: is derived from the remoteness in which most of vulnerable groups
live in, namely rural areas or even slums within urban settings.
2. Access exclusion: refers to the restriction to financial services through the processes of a risk
assessment not fit for the reality of those excluded.
3. Condition exclusion: is where the conditions attached to the financial products (for example
repayment terms) make them inadequate for the needs of certain groups.
4. Price exclusion: comes when some groups can only access to financial products or services at
prices they cannot afford (namely interest rates or commissions).
5. Marketing exclusion: is when someone is effectively excluded by the marketing and sales
policies of the Financial Institutions.
6. Self-exclusion: derives from individuals deciding that there is no gain in applying for financial
services or products because they foresee rejection from the Financial Institutions; in summary,
it can be interpreted as a negative self-selection bias.
Per Adunda & Kalunda (2012), there is not a universal agreement regarding what Financial
Inclusion really is. Hence, it is important to explore several meanings to determine its main
properties. For Thorat (2016), FI is the provision of affordable financial services, namely,
remittance facilities and access to payments, savings, loans, and insurance services by the formal
financial systems to those groups who tend to be excluded. For Chakrabarty (2010), Financial
Inclusion is the process of ensuring access to appropriate financial products and services needed
by all sectors of the society, particularly to the vulnerable groups, at an affordable price, and in a
transparent and fair way by regulated institutional bodies. For Chibba (2009), FI is an intervention
strategy that aims to overcome the market friction that prevents the markets from operating in
favor of the poor and underprivileged, therefore, FI offers incremental and complementary
solutions to draw people out of poverty and promote inclusive economic development. Lastly,
Adunda & Kalunda (2012) conclude that Financial Inclusion can be defined as “the process of

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availing an array of required financial services, at a fair price, at the right place, form and time
and without any form of discrimination to all members of the society. The objective of financial
inclusion should be advantaging the poor majority of who do not use formal financial services”.
From all these previous definitions, there are certain commonalities that can be drawn to form a
concise definition for the ends of this work. Therefore, Financial Inclusion will be defined as “the
provision of financial products and services, in an efficient and accessible way, to those groups
that have been excluded from the formal economic and banking system”.
Chibba (2008) suggests that tackling Financial Inclusion requires a focus on four key pillars:
private sector development, public sector support, financial literacy, and microfinance. While the
four pillars should be emphasized, Microfinance will be the center of this work due to the relevance
it has in the design of Public Policies and in the achievement of Financial Inclusion.
How does Financial Inclusion reduce poverty?
While arguably Financial Exclusion (FE) leads to other sorts of social exclusions and feeds the
dynamics of Poverty Traps, it is important to understand the mechanisms behind the effects that
the FI could have in the BOP. The economist Josepth Schumpeter, established in 1911 that the
Financial Institutions play a key role in the resource allocation process by providing arbitrage
between those with excess of capital and those in need of it. Also, Diamond and Dybvig (1983)
considered that the main role of the banking systems is the provision of liquidity that enables more
investments in productive assets, which enhances the efficiency of capital accumulation and
economic growth. Beck et al. (2009) described that a well-developed financial system, open to all,
reduces information and transaction costs, guides saving behavior, investment decisions, and
innovation, and influences the long-run growth rates.
The World Bank released a policy research report in 2008 entitled “Finance for All? Policies and
Pitfalls in Expanding Access”, in which it thoroughly explores the relevance, advances, and
setbacks of the Financial Inclusion Movement (FIM). In it, it states that evidence from multiple
studies (including calibrated general equilibrium models, specific policy experiments, and
econometric analysis of cross-country data) suggest that the more developed financial systems
tend to reduce inequality in the long-term. While this conclusion is well expected, it is important
to note that many of these studies suggest that the connection between financial development (in

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consequence Financial Inclusion) and reduction of inequality comes from the indirect effects of
financial development, not the mere integration of former excluded parts into the financial systems.
With the former on mind, it is vital to understand that the evaluation of the impact of FI in the
reduction of inequality and poverty requires two levels of assessment: the effects at the micro-
level, alas the direct effects FI has in the households and excluded communities, and the dynamics
that come from the aggregated effects in the whole economy, or macro perspective.
Research mentioned by the World Bank (2008) suggest that Financial Development (FD)
generates economic growth that narrows the income differentials between the different quintiles.
Beck, Demirg-Kunt, and Levine (2007) find a positive relationship between Financial Depth
(which in this case is expressed by the ratio of private credit to GDP) and the change in the share
of the lowest quintile in total national expendable income. This implies that a deeper financial
system not only accelerates the national economic growth, but also accelerates the increment of
the lowest quintile’s income share. The World Bank (2008) also mentions that “Li, Squire, and
Zou (1998) and Li, Xu, and Zou (2000) find a negative relationship between finance and the level
of income inequality as measured by the Gini coefficient, a finding confirmed by Clarke, Xu, and
Zhou (2006), using both cross-sectional and panel regressions and instrumental variable methods.”
(World Bank, 2008). The same study by Beck, Demirg-Kunt, and Levine (2007) also detects
that countries with higher levels in terms of FD ended up with a higher number of people coming
out of the $1 USD/day poverty line during the 1980s and 1990s.
Per the World Bank (2008), Giné and Townsend (2007) compared how growth and inequality
evolved in Thailand and showed that financial liberalization, meaning the reduction of entry
barriers to the financial sector both for suppliers and beneficiaries, together with the increase in
access to credit services are correlated with the fast GDP per capita increase that the Thailand’s
economy experienced from the late 1970’s to the early 1990’s. Nevertheless, regardless the long-
term trend towards increasing equality, initially they suffered a period of increase in income
inequality due to wealth gain of the new successful “empowered micro-entrepreneurs” by this new
context. Using the same general equilibrium model calibrated to fit Thai data on finance, growth,
and inequality, Giné and Townsned (2007) discovered that the greatest quantitative impact of
financial access and deepening has its origins in the indirect labor market effects, which ultimately

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are the same that decrease income inequality in the long-term surpassing the initial gains in
inequality.
Chibba (2008) states that multiple evidence indicates that FI spurs pro-poor growth and has the
capacity to alleviate poverty. Additionally, marginalized people in developing countries can be
improve their living quality through FI due to enhanced money management, access to finance at
fair costs, savings safety, and eradicating the dependence from the informal money-lenders.
Burgess and Pande (2005, cited by the World Bank 2008) studied India’s policy on bank branching
implemented from 1977 to 1990, which mandated commercial banks to open 4 branches in districts
without branches if they wanted to open a new branch in an operating district. The study finds that
due to this branching regulation, non-agricultural output accelerated its growth and poverty
declined faster in those districts that begun with a lower level of FD. Even more, wages in the
agricultural sector grew faster while the policy was enforced, while the urban wages did not
experience such a boost.
To target the issue of selection bias, Karlan and Zinman (2006a, cited by the World Bank, 2008)
convinced a consumer lender from South Africa to loosen its risk evaluation criteria for a group of
scarcely discarded loan applicants that was selected fortuitously. In this way, they were able to
compare between the randomly chosen borrowers and the control group of barely denied
petitioners, and came to the conclusion that six to twelve months after the mortgage approval,
recipients were significantly more plausible to retain wage employment, hardly experienced
hunger in their family unit, and unlikely to be poverty-struck.
Furthermore, a case of study in Peru implies that shortage of financial access decreases the chances
of family units in poverty of sending their children to school. Meanwhile, researches carried out
in Tanzania, Guatemala, and India suggest that households lacking access to credit are more
probable to reduce their children’s school attendance and put them into labor if needed than those
subjects to credit. Also, micro entrepreneurs in Guatemala collected data that indicate a positive
correlation between credit use and upward class mobility (World Bank, 2008).
In their assessment of Microfinance effects in the Middle East and North Africa (MENA)
countries, Gaysset and Neaime (2018) note that the inclusion of the poorest in the Formal Financial
System also might have a spillover effect over other economic segments. The authors argue that
those excluded from the FFS use cash in most of their transactions and make their economic

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decisions oblivious of the Monetary Policy. Therefore, by including this group of the population
into the system, the transmission mechanism of the monetary policy gets reinforced and it intended
effects are expressed faster into the real economy.
Although certain concerns regarding the hazard in expanding the access to credit, for example, that
it could exacerbate inequality, have been theoretically pointed out, certified data such as broad
cross-country regressions, estimation of general equilibrium models, and specific quasi-
experimental events, shows that financial expansion and augmented access to credit stimulates
economic growth while it decreases poverty and inequality rates. In addition, it is obvious that
financial assistance granted to the poor of certain regions benefits economic stability and increases
job opportunities within those areas. (World Bank, 2008)
Financial Inclusion Advancements and Setbacks
Relevant advancements have been achieved in increasing the FI levels worldwide. Demirguc-Kunt
et al. (2015) estimate that the number of unbanked people in the world has dropped by 20%
reaching the two billion mark in the period of 2011-2014 (Lopez & Winkler, 2018). The World
Bank Group estimated in that over 500 million people have been benefited directly or indirectly
by from Financial Inclusion policies (Investopedia, 2018). Additionally, Market MIX (2015)
estimated that global Gross Portfolio of MFIs overpassed the $92bn USD mark by 2015.
Over the last couple of decades, the traditional Financial Institutions have become aware of the
possibilities that the market at the BOP holds. Also, new organizations, such as the Microfinance
Institutions (MFIs), have rose to meet the saving/finance needs of these groups by developing new
services, micro-insurance policies, and commitment saving products are quite notorious, and
implementing new methodologies such as mobile branches, leverage of Self Help Groups (SHG),
deposit collectors, and mobile banking/payments. This trend does not seem to be slowing down,
and arguably, there are two main aspects pushing it. First, the use of Microfinance and MFIs as
the main vehicle to deliver financial services using microcredits as an anchor, and the rapid
integration of digital technology to provide solutions for the recurrent challenges that come from
serving people at the BOP.

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Despite the emphasis Financial Inclusion has had in the Economic Development sphere, there is
still a long way to go. Flexibility in policy, and in regulations where rigidities would harm the rise
of markets for the financially excluded, are necessary.
A doubt that still buzz over the head of the researches is whether FI impinges upon Financial
Stability (FS). FI requires specialized rules for a specialized market constituency. Therefore,
policies to foster increase access to financial services for those how have been excluded must also
consider the objective of FS. These should create opportunities for a sustainable development that
can overcome the various economic shocks which normally end up affecting the underprivileged
groups the most (Adunda & Kalunda, 2012).
Per McLean and Nocera (2010), the Financial Crisis of 2008 revealed that some of the most
aggressive policies for FI could lead to adverse outcomes, “giving rise to the tension between
financial stability and greater access for the population” (Garcia, 2016). Mishkin (1999) specifies
that “financial instability occurs when shocks to the financial system interfere with information
flow so that the financial system can no longer do its job of channeling funds to those with
productive investment opportunities”. While Padoa-Schioppa (2002) claims that “…financial
stability is a condition where the financial system is able to withstand shocks without giving way
to cumulative processes, which impair the allocation of savings to investment opportunities and
the processing of payments in the economy” (Garcia, 2016).
The theoretical risks on financial stability derive from the particularities of low-income
beneficiaries, the local Financial Institutions, the innovation in financial services, and from
outsourcing functions. The participation of the poor in the FFS derives into high information and
transaction costs, which precede to inefficiencies that are hard to counter. The effects of the
information asymmetries could deepen. In addition, the large territorial concentration, lack of
regulation, and inter-institutional lending, makes the local Financial Institutions vulnerable to both
exogenous and endogenous shocks (Garcia, 2016). There is still little empirical evidence on the
adverse effects of FI in FS, regardless, the existence of such conception weakens the theoretical
and political soundness of the Financial Inclusion as a development movement.
While the accelerated expansion of financial products and services directed to the BOP cannot be
denied, at least in the global scale, the story is different when rural and urban settlements are
studied separately. Multiple studies (Schreiner and Colombet 2001; Charitonenko and Campion

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2003; Honohan 2008; Beck and Brown 2011; Raghunathan et al. 2011; Allen et al. 2012; Swamy
2014) point that access and utilization of products and services from the formal financial sector
have mainly grow in urban areas, but have somehow neglected the rural settlements (Lopez &
Winkler, 2018).
The absence of momentum in rural FI is attributed to the tougher environment the Financial
Institutions face when serving rural clients and trying to remain financially sustainable. There is
evidence that MFIs with a high rural presence cannot leverage on economies of scale and
productivity effects at the same extent as the rural-oriented MFIs. This is mainly due to the higher
operation expenses and risks and the less favorable contracting setting rural-oriented MFIs face
(Lopez & Winkler, 2018).
Dhrifi (2013), claims that while, Schreiner and Colombet (2001), Charitonenko and Campion
(2003), Honohan (2008), Beck and Brown (2011), Raghunathan et al. (2011) Allen et al. (2012),
and Swamy (2014) suggest that FI boosts the growth rate of the GDP per capita, they do not
necessarily show that FI reduces poverty. In the case of MENA countries, these increments in FI,
and hence the GDP per capita, have not benefited the low-income strata and only have increased
the wealth of the upper segments (Gaysset & Neaime, 2018).
Last but not the least, most FI efforts focus on the overall increase of Financial Access (mostly by
branch expansion), while addressing market failures tends to be most effective. Also, research
suggest that it is better to increase FI through measures that expand supply by diminishing the
effects of market failures (such as information asymmetry and transaction frictions), instead of
relaxing screening and monitoring criteria, which ultimately can lead to negative outcomes in
terms of Financial Stability (Garcia, 2016).
Microfinance: Funding and Banking for the Bottom of the Pyramid
The idea of tackling extreme poverty by providing financial instruments, especially micro-loans,
to those out of the system, originated in the 80’s when Mohammed Yunus, recipient of the 2006
Peace Nobel Prize, founded the Social Banking Model (SBM) behind the Grameen Bank of
Bangladesh (Chibba, 2008). Ever since, Microfinance became the main vehicle to introduce
vulnerable groups into the financial systems of the developing world.

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Albeit the concept of Microfinance has been mentioned and roughly explained previously, it is
important to understand in detail what Microfinance covers and entails to be able to provide
solutions for its setbacks and tools for its further expansion. Per Adunda & Kalunda (2012), the
term Microfinance used to be only used for the grant of micro-loans to small firms and
entrepreneurs, outside the confines of institutional banking and group-based models. From being
an alternative source of funds for those underserved at the BOP, it has evolved into a tool for
uplifting their social standards and for them to get work their way out of poverty.
Plenty empirical research provides strong evidence in support of the positive role of microfinance
in the reduction of poverty (Karlan and Zinman, 2007; Cotler and Woodruff, 2008; Setboonsarng
and Parpiev, 2008), there have been critics regarding the methodology implemented in the
assessment of MF programs and in the lack of replicability of the results (effects that are only
country or site-specific). Also, there have been multiple cases in which the bad implementation of
MF policies and the rise of institutions with ulterior objectives have exacerbated the precarious
conditions of those whom they were supposed to benefit.
Ever since the success experimented by Professor Yunus, Microfinance has rose as a robust tool
that provides access to certain financial services designed for the groups living in poverty; a
gateway to provide an entire portfolio of products and services tailored for the poor. Microfinance
has attempted to close the gap between the incumbent financial institutions and the poorest by
providing intermediary mechanisms of transaction aggregation and rationalization of the
transaction costs (Sriram, 2005). The provision of micro-loans has served as a vehicle to provide
saving accounts, insurance, finance literacy, and credit records to those who were excluded from
the system. While this choice was never meant by design, different financial institutions have taken
advantage of the penetration and expertise of MFIs to deliver novel products aimed at the BOP.
Per the World Bank (2008), life and health insurance for the poor have been increasingly offered
by both for-profit banks and NGOs. For these to be economically viable for the commercial
insurer, it was necessary to find a delivery channel that had the trust from the target customers.
Naturally, MFIs, NGOs, and saving cooperatives become the most suitable vehicles to bridge both
parts.
The case for insurance policies in the provision of Microfinance is quite intuitive. There is a gap
that only MFIs can fill efficiently and there is a good economic incentive for the MFIs to do so;

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by protecting the beneficiaries they end up protecting themselves. But, what is the case for saving
mechanisms? What are the barriers that poor people face to save through the formal financial
system? Are there enough incentives for the Financial Institutions to outreach those at the BOP?
Certainly, the geographic exclusion plays a major role since most of the poor population, especially
the one in developing countries, still live in rural areas located far from the urban centers and with
poor infrastructure to sustain a bank branch. But even before this started to be considered an issue,
the Financial sector had to abolish a long-held myth: the poor do not have income to save. Multiple
studies have shown that the poor have savings, even when their income is considerably small and
they do not have constant sources of revenue. Most of the saving is done using mechanisms such
as the (Pool Saving or the other one), and it is intended to be used for consumption smoothing in
rough times or to face any sort of major emergency. By understanding this, MFIs managed to give
incentives and schemes in order to foster savings, such as providing loans that double the amount
of savings by the group (World Bank 2018).
Another interesting service that has been bundled with the MFIs offer is the transfer of
International Remittances, which have become a very relevant source of income in must of
developing countries. Usually, remittances sent via formal institutions are subject to costly fees
that spur the use of informal remittance channels. Most of these fees are the reflection of the high
transaction costs that formal institutions face in reaching the recipients or of the lack of competition
of bank in remote areas. Again, the geographical outreach and the trust built by MFIs make them
a natural choice to carry out remittances transactions in rural areas, adding up this service into their
portfolios.
In the same “Financial For All?” report by the World Bank (2008), Karlan and Valdivia (2006),
and Ashraf, Giné and, Karlan (2007) found that MFIs that provide financial services that go beyond
loans have better repayment performance and client retention metrics than those who only
specialize in credit. Moreover, the beneficiaries of such institutions also experienced better
performance in their businesses than their homologue with just credit. Still, the research from de
Mel, McKenzie, and Woodruff (2006) taking random samples of entrepreneurs in Sri Lanka found
that the lack of credit availability is the main barrier for business expansion, bundling credit with
proper insurance packages could be translated into higher take-up for credits.

17
The Evolution of the Microfinance Movement
Microfinance before the Grameen Bank
Inspired by the masterpiece of Paulo Freire titled “Pedagogy of the Oppressed” (1970), the 70’s
considered poverty as a structural problem that could only be tackled by the mobilization of the
poor. Focusing in spurring Income Generating Activities and small enterprises since the 1970’s,
women not only were identified as the poorest of the poor but also were regarded as a vital element
to ensure household wellbeing (Premchander, 2009).
Following this spirit, the concept of Microfinance was developed in the 70’s and 80’s as an
alternative to the failure stemming from the subsidizing efforts in rural credit of the two previous
decades. During that period, international donors and nations invested high amounts of capital in
providing cheap credit to farmers via National Governments and Multinational Organizations,
which resulted in high corruption and credit default rates (Kringlen, 2016).
The Grameen Bank Model
With the scarce opportunities of employment for poor women, the 80’s drawn support for women
entrepreneurial initiatives as a feasible option for seizing their economic potential (Premchander,
2009). SMEs, development of entrepreneurial skills, and Microfinance programs targeted to
women rose during that decade (Premchander, 2009).
The beginning of the Microfinance movement is normally associated with the now Nobel Peace
Prize Laureate Mohammad Yunus. In 1976, Mr. Yunus began to extend small credits to women
after a visit to the village of Jobra in India. With this, he noticed that small loans can generate
disproportionate improvements and opportunities to these groups, which ultimately motivated him
to build a movement that could drastically improve their lives. In the 1980’s, little after Yunus
developed an alliance with the Janata Bank to provide loans to the people of Jobra, the Grameen
Bank was founded with the only goal of providing financial services to the poor (Kringlen, 2016).
The Grameen Bank and the Microfinance Movement focused on matching the poor’s demand for
credit and financial services with the need for new sources of income and repayment methods of
the banks. The way the Grameen Bank managed to achieve this is to leverage form the
methodologies implemented in informal financial systems, such as the rotating savings and credit

18
associations (Kringlen, 2016).
The major innovation in Yunus model was the use of the Joint-Liability Lending Method (JLLM)
to reduce the risk of default. With the JLLM, MFIs provide loans to groups of borrower that share
the responsibility of repayment. Therefore, members of these groups have the right incentive to
monitor each other reducing the chance of default. Moreover, this method of lending results in
lesser operation and transaction costs, and in a reduction of the information asymmetry and the
moral hazard effects (Chae et. al 2012). The implementation of such lending methodology resulted
in portfolio defaults rates way below the average of the regular commercial banks. With this Yunus
broke the myth that the poorest of the poor are not creditworthy.
From the NGO movement to the Commercialization of Microfinance
Currently, MFIs ownership has diversified to form four main classifications: Banks, Non-Bank
Financial Institutions, NGOs, and Cooperatives. The former two are for-profit public organizations
owned by Shareholders, while the latest two are not-for-profit ones in which cooperatives are
member-based organizations (Roberts et al., 2018).
Shortly after the Grameen Bank gained notoriety, the Microfinance loans were mainly group
based, and savings were promoted as a way of offering loans matching the value of those savings.
Later, this kind of programs were receded to be merged with traditional microcredit formats. With
the increasing financial success of Microfinance, urge for financial sustainability grew, forcing
NGOs to take a “minimalist” Microfinance approach focused only in the provision of financial
services that could cover their operating costs (Premchander, 2009).
Therefore, linking the Microfinance sector with the commercial banking sector became a more
usual solution to this issue. In some countries, such as Bolivia and Uganda, MFIs have been
allowed to transform into Banks that can collect deposits from all sort of customers. A few of the
leading MFIs have been funded by institutional investors, and connections between Banks and
MFIs in multiple countries have granted banks funding to these MFIs, while keeping their lending
model focused on low-income individuals (World Bank, 2008).
The original mission of the MFIs expanded to cover all sort of financial services that were
demanded by the poor. Nowadays, savings, remittances services, and insurance coverage are part
of the portfolio of the average MFI. Over the last couple of decades, the Microfinance sector has

19
experienced an extraordinary expansion, with MFIs experimenting an average growth of between
40% to 60% in the total loan portfolio (Kringlen, 2016).
Nevertheless, in the last decade the maturation of the Microfinance movement has led to some
criticism regarding an apparent mission drift from serving the poor. “The media coverage
concerning microfinance shifted rather rapidly from being praising and rosy in 2005 and 2006 to
rather critical and grim in 2007” (Kringlen, 2016).
Despite of the criticism, the expansion of the MFI has not drastically slowed down. Mersland &
Strom (2012a) argue that even during the financial crisis, the growth of the sector remained
positive, with just minor decreases. Likewise, their study points out that the sector is becoming
more and more consolidated, and that the average loan portfolio amongst the MFIs doubled in
(Kringlen, 2016).
Challenges and Shortcomings in Microfinance
Why 30 years of Microfinance and we still have billions of poor?
While Microfinance has been praised by some as the silver-bullet to end poverty, there have been
cases in which the implementation of Microfinance Programs has given little to no results, and
even more, has had negative effects in those who have been targeted by the MFIs. There is still
debate in whether these are isolated cases that rose from specific context or the wrong
implementation of the MF policies, or if the entire Microfinance movement has overestimated its
effects in long-term.
Whereas evidence shows that Financial Inclusion triggers the growth rate of per capita GDP, and
usually it tends to be pro-poor growth, it does not mean that it directly aids those in poverty. For
example, in various MENA regions, the poor have a misconception that Financial Inclusion
increases average growth rate of GDP only by increasing the incomes of the rich and leaves behind
those with lower incomes, therefore they distrust the banking services and do not use them. To
round up this idea; the way FI affects income inequality and how it could improve income
distribution in those countries is still unclear.
Despite of that, to complement conventional Microfinance, the private sector has developed new
alternatives such as Mexico’s banking entity Compartamos, which was first based on the social
banking model but later evolved into a profit-based enterprise, where the social bottom-line is no

20
longer pertinent. Also, there are certain changes occurring within Microfinance system, for
example, the current agenda to scale-up Microfinance covers the use of global capital markets, that
may fall into a further development in its rapidly growing function (Chibba, 2008).
Critics also raise the point regarding the role that interest rates have for Microfinance beneficiaries.
Are the interest rates of the micro-credits directed to the poor too high? Most of the Microfinance
movement has been based on the premise that poor people can pay high interest rates, because the
funds are used in entrepreneurial projects that provide high levels of ROI (World Bank, 2008).
Therefore, multiple MFIs around the globe have been charging rates that usually range from 50%
to 100% with the justification that lending to the poor is a costly and risky endeavor, and by making
the over-simplification that all poor people are good entrepreneurs, and that all the productive
initiatives taken by them are bound to produce numerous returns (World Bank, 2008).
While it is true that success at that level of income generates great profit, theory points out that
most of the poor people are willing to take the MFIs interest rates because there is a lack of
financing options, or because the informal channels tend to be more expensive. Therefore, the
poor’s loan demand is inelastic with respect to the interest rates, meaning that the demand will not
react to the changes in the rates. To address this, a couple of studies by Dehejia, Montgomery, &
Morduch (2005), using data from a cooperative in Dhaka, and Karlan & Zinman (2007), using the
data from a South African consumer lender, find that in fact there are high elasticities of loan
demand with respect to interest rates. Emran, Morshed, & Stiglitz (2006) developed a theory to
reconcile these empirical discoveries with the claims that borrowers are highly insensitive to
changes in interest rates. Nevertheless, the Bangladesh data conveys that the elasticity decreased
(in absolute value) as the income of the beneficiary did so, whereas the South African data suggest
the opposite (World Bank, 2008)
There is a clear relation between the operating and funding costs of Financial Institutions, and the
interest rates these institutions offer to borrowers. While the funding costs of MFIs may differ
compared to conventional Banks, the Operation Costs are an area of opportunity for MFIs since
the clients they serve, and their circumstances, pose barriers to achieve economies of scale and to
achieve efficiencies that can assure fair interest rates.

21
The Operation Costs
The first, and most logical, challenge that Financial Institutions face when trying to reach the poor
are the operation costs. First, a considerable part of the poor live rural areas that are characterized
by low population density and feeble public infrastructure (Caudill, Gropper, and Hartarska 2009).
Even when the beneficiaries are settled in urban areas, these tend to be segregated from the
economic centers and to also have a relatively poor infrastructure; this sort of segregation translates
into raising operating expenses. Second, the structural exclusion the beneficiaries face arguably
raises the costs of funding, information, transactions, and monitoring. A survey performed by
Lascelles and Mendelson (2008), spotted 20 risk factors that could deter the growth in the
Microfinance sector. Among these factors, cost control is rank as the fourth most relevant. This
indicates that efficiency in operations is vital for MFIs in reaching their goals of outreach and
financial sustainability (Yimga, 2018).
Mersland & Strøm (2012b) reveal that for most of the MFIs’ changes in the interest rates, revenues,
and profitability are the result of “increased input prices”. They emphasize that elevated costs and
low profit margins are Microfinance’s main challenge. This conclusion is later supported by the
same Mersland & Strøm (2013), which find that Microfinance is usually an industry with low
profits. Kringler (2016) explores further this topic and finds that “the average portfolio yield is
close to 38%, whereas the operating costs of portfolio is above 30%” (Kringler, 2016).
The World Bank (2008) claims that most of MFIs face high unitary costs due to the small size, in
terms of value, of the loans. Thus, many of these MFIs heavily rely on subsidies or donors’ money.
Per the World Bank (2008), Cull, Demirgüç-Kunt, and Morduch (2007) took a sample of 124 MFIs
in 49 countries representing about half of all the MFIs clients worldwide, arguably the most
profitable and efficient. In this study, the scholars find that, even with this segmentation, just about
50% of these organizations were profitable or financially sustainable (World Bank, 2008).
For instance, assume that the cost for capital to be 10% and the transaction fee to be $5 USD for a
loan of $100 USD. Then the interest to break even would be $10 USD (cost of capital) + $5 USD
(transaction fee), ensuring the repayment to be $115 USD. Hence, 15% interest on the loan would
cover the costs. However, in case of micro lending, the transaction fee would remain the same. To
break even on a loan of $30 USD, the interest would be $3 USD (cost of capital + $5 USD
(transaction fee), making the total to be $38 USD. The interest that would be charged here is

22
26.67% to cover the costs. Despite the clarity of this mechanism, Gosh & Van Tassel (2012) argue
that “given that investors often tolerate below market returns on this funding, there is the possibility
that some microfinance lenders rely on cheap funding to cover high, and inefficient costs”. The
work of Morduch (2009) and Gonzales (2010), validate this by arguing that differentials in
management and operating expenses across MFIs “cannot always be explained away by the size
of loans or the rural versus urban settings” (Gosh & Van Tassel, 2012).
While the contentions of Gosh and Van Tassel might be true, not only the unitary cost is usually
higher because the transaction fee remains constant regardless the size of the loan. Apart from the
survey of Lascelles and Mendelson (2008), multiple studies (Hermes et al., 2011; Kneiding & Mas,
2009; Quayes et al., 2013) suggest that increasing loan sizes improves the lending efficiency. The
logic is that for the same amount lent MFIs need to monitor less beneficiaries if the loan size is
bigger, hence the monitoring cost per loan decreases. The same Gonzales (2010) accounts that an
increment of 10% to 20% of Gross National Income in the average loan size reduces operating
expenses by more than 7 percentage points (Yimga, 2018).
Per Kringler (2016), Field & Pande (2008) argue that since MFIs tend to use frequent collection
schemes (usually weekly) to reduce the risk of default, it is expected that they will incur in higher
costs of collection and monitoring that drive up the transaction cost. Even when these activities
are run efficiently by transferring them to members of the community (via joint-liability and group
lending), further costs could be incurred by the negotiation of new repayment schemes, the efforts
to keep the MFI’s trust and to avoid problems with performing loans, and the deviations on
management focus when loans goes in default. Therefore, it is safe to claim that MFIs operations,
at least in these regards, are pretty much organized the same as traditional commercial banks. Even
more, it could be argued that the expenses of the Microfinance industry are even greater due to the
absence of formal channels to enforce contracts (Kringler, 2016).
Lastly, since MFIs are usually supported by subsidies to fulfill their outreach goals, it is important
to understand whether these influence the cost structure. Caudill, Gropper, & Hartarska (2013)
find that subsidies effectively lead to a bulkier cost structure, even across multiple alternative ways
to measure the subsidies. The authors claim that even when the mechanism behind this relation
cannot be clearly identified, although they suspect is due to the negative incentive subsidies give

23
to operate efficiently, the correlation between subsidies and increasing costs is fairly robust
(Caudill, Gropper, & Hartarska, 2013).
Thus, if MFIs want to be financially sustainable, they must need to transfer these operating costs
further on to the borrowers via the interest rates (Dehejia, Montgomery, & Morduch, 2012;
Fernando, 2006; Morduch, 2000). As Kringler (2016) states “It is a paradox that the world’s
poorest are charged with the highest cost of capital”. This is why providing small credits at
accessible interest rates becomes one of the main challenges of the Microfinance industry
(Kringler, 2016).
Regardless the efficiency gains that might come from current regulatory, managerial, and
technological developments, multiple authors (Conning, 1999; Hulme & Mosley, 1996; Lapenu &
Zeller, 2002; Paxton & Cuevas, 2002) sustain that small size credits to the poor bear a higher
operation/transaction cost per unit. Cull et al. (2007), Cull, Demirgüç-Kunt, and Morduch (2009)
and Hermes et al. (2011), demonstrate that there is tradeoff between poor outreach and operations
efficiency exists, implying that as MFIs change their focus towards financial sustainability, they
possibly reduce their capacity to reach the poor. At the end “If a microfinance provider does not
reach operational self-sufficiency, it runs the risk of depleting its loan fund capital, which means
fewer loans to borrowers and potential bankruptcy” (Yimga, 2018). Therefore, the cost structures
of MFIs could have implications in terms of the long-term financial sustainability and scalability.
Financial Sustainability and Scalability
Another critical aspect for the MFM is the fact that MFIs struggle to reach optimal sizes to achieve
economies of scale and financial sustainability. Lascelles and Mendelson (2008) argue that, in
modern Microfinance, it appears that the greatest concern for the operators is to get external capital
to fund the expansion of their operations, feeding a growth rate that becomes unsupportable due
to their inability to grow sustainably. Hermes, Lensink, and Meesters (2011) state that MFIs deal
with a trade-off, either to serve the poor, known as outreach, or to cover their operation
expenditures Moreover, the accelerated growth that the Microfinance movement experienced
during its boom in the period 2004-2008, derived in a country-wide downturn of the MFIs’
portfolio in Bosnia and Herzegovina, Morocco, Nicaragua and Pakistan (Yimga, 2018).
Lopez & Winkler (2018) claim that MFIs having a bigger share of rural beneficiaries register a
higher “depth of outreach”, since the poorest of the poor tend to concentrate in this kind of

24
settlements. Nevertheless, this achieving depth of outreach by focusing on the rural poor is likely
to lead into higher financial sustainability issues.
Certain particularities affect the rural borrowers which lead to higher costs and threats to the
sustainability of the MFIs. Apart from the effects of the poor infrastructure and geographic
exclusions in the costs, most of the economic activities in rural areas tend to gravitate around
farming, which implies accounting for seasonality and high risk exposure. Also, the same
seasonality requires “comparatively larger loans with longer maturities which runs counter to the
microfinance tradition of granting short-term, small instalment loans without grace periods”
(Lopez & Winkler, 2018). Lastly, rural communities tend to face issues of asymmetric information
and contract enforcement that are tougher and more expensive to address, at least compared to
their urban counterparts. Therefore, it is expected that MFIs that mainly operate in rural settlements
face a considerably higher outreach-sustainability trade-off (Lopez & Winkler, 2018).
Robinson (2001, cited by Hermes & Lensink, 2007) notes that an issue raised in the literature
studying Microfinance deals with the sustainability of such programs. Providing financial services
to the poor is a costly business due to the high transaction and information costs this entails. In the
1990’s, the importance of financial sustainability of the MFIs gave rise to an important
(unresolved) debate between the for-profit approach versus the Social Banking Model (SBM).
Basically, the debate sums up to the question of whether giving subsidized interest rates is justified
or not. The supporters of the SBM argue that the vulnerable groups cannot afford higher interest
rates, hence “financial sustainability” goes against the aim of serving the poor, not to mention
serving the poorest of the poor. On the other hand, supporters of the for-profit approach argue that
large-scale outreach is not feasible in the long-term because MFIs are incapable to self-sustain
their operations (Hermes & Lensink, 2007). The greatest hindrances for MFIs to reach those casted
out from the financial system, especially those in remote rural areas, are still cost and access
(Lascelles & Mendelson, 2008). “This suggests that expansion may increase cost, thus hurting
efficiency.” (Yimga, 2018).
By using the Subsidy Dependence Index (SDI) devised by Yaron (1992), which indicates how
much an interest rates to borrowers should increase in order to cover all the operating costs of the
Financial Institutions, Hulme and Mosley discover that almost all of the MFIs in their sample were
subsidy dependent. Morduch (1999a, cited by Hermes & Lensinnk, 2007) does a similar estimation
for the Grameen Bank (GB), unveiling that, in order for it to become 100% subsidy free, the GB

25
would have needed to increase their rates by some 75% between 1985 and 1996. While these
results are consistent with the theory, it is important to note that the SDI assumes that an increment
in the interest rates automatically translates into higher profits for the Institutions. However, this
might be further from truth since higher rates could lead to lower profitability of MFIs in case of
adverse selection and the appearance of moral hazard. (Hermes & Lensink, 2007).
The over emphasis on financial sustainability and the trend towards the adaptation of Microfinance
by commercial banks have raised concerns regarding the effects of this shift in terms of outreach.
Individual-lending MFIs seem to outperform the outreach-based ones in terms of profitability, but
the proportion of underprivileged borrowers into their loan portfolio is considerably smaller than
for the group-lending institutions. Also, there is evidence that a rise in interest rates, above certain
threshold, leads to a worsening of the portfolio quality in the case of the individual-lending,
whereas this relation does not exist for the group-lending MFIs. The individual-lending
institutions, especially the ones that have scale, increasingly aim to attract wealthier clients,
whereas this deviation happen less in the group-lending ones. Moreover, the study strongly
underlines the relevance of institutional design when considering the trade-offs in Microfinance
(Hermes & Lensink, 2007).
Unfortunately, scaling-up is not an easy task for those MFI aiming at clients with higher purchasing
power. Moreover, MFIs are prone to lose some of their long-standing beneficiaries if they manage
to get richer. Per Cull, Demirgüç-Kunt, and Murdoch (2007), the impediment to serve wealthier
consumers comes from the JLLM followed by most MFIs. JLLM depends on a high volume of
beneficiaries gathered in numerous groups with certain homogeneity, at least in terms of financial
needs. The more income borrowers possess, the bigger the size of loans they aim at, and the more
diverse their needs become. Therefore, the purpose of JLLM gets lost and the use of individual-
based micro-lending, usually larger in size and less costly, becomes more suitable. (World Bank,
2008)
Honohan (2004, cited by World Bank 2008) also remarks that self-sustainability is usually not
achieved because MFIs do not have the size to generate economies of scale. By 2004, only in eight
nations Microfinance beneficiaries represented more than 2% of the population. Considering the
fragmentation of the market, just a few of these organizations managed to reach some scalability.
Moreover, most of the MFIs with the proper bandwidth are mature organizations that have drifted
away from lending the poor. By the supporters of the for-profit movement, this is interpreted as a

26
success. For the “social purists”, this is a clear example of a Mission drift; an issue that will be
debated further in the next section.
Regardless the efforts done over the last three decades, the FFS has not been able to eradicate the
activities of the informal players. The traditional Financial Institutions are not well equipped to
offer financial products in sizes and prices that are suitable for the people at the BOP.
Improvements and adaptations can be done to meet these needs through technological
advancements, but the will of those directing MFIs needs to focus on achieving self-sustainability;
in the entire extension of the word. (World Bank, 2008)
The notorious progress we have experienced in telecom technologies over the last decade,
especially the rise of the 3G and 4G technologies and smart-phones, promises major improvements
in the delivery of financial services. The upgrades are such that these advancements threaten to
remove financial intermediaries and providers in some areas of the system. Nevertheless, the
Microfinance industry has generally treated with marginalized and unconventional borrowers who
hold a little expertise on technology. Hence, intermediation might be difficult to eradicate (Yimga,
2018).
Mission Drift: Does Microfinance benefit the Bottom of the Pyramid?
Mersland & Oystein (2009) claim that “the microfinance industry is coming of age, and with its
maturation have come claims that the industry is abandoning its mission to serve the poor”. The
objective of all MFIs is to provide banking services to those at the BOP; to provide very small
credits to the very poor (Mersland & Oystein, 2009). Kringler (2016) supports this claim when he
claims that the effects of the utility-maximizing behavior can come to dominate the industry since
MFIs clients are regularly poor and desperate (Kringler, 2016).
As previously mentioned, over the last couple of decades more and more MFIs have shifted from
issuing group-loans based in joint-liability and SHG, to offering individual loans with a larger
average size; this phenomenon is known as “Mission Drift”. Purist and pundits have criticized it
by claiming that MFIs are drifting from the goal of benefiting the poor, opening the door to threats
that could demerit the movement or have major social and economic effects. On the other side,
those supporting the for-profit shift argue that there is no other way to assure the sustainability and
scalability of MF without incurring into individual lending and profit-seeking behavior; both
challenges treated on the previous section.

27
But how to detect when an MFI is drifting from its mission? In general, the average size of the
loan is used as the main metric to measure the level of outreach an MFI has (Bhatt & Tang, 2001;
Cull et al., 2007; Schreiner, 2002). As expected, there is a negative relation between the size of the
loan and outreach, because a bigger loan indicates that an MFI is either aiming at clients with more
income or their usual clients are improving their situation and can support bigger debt.
Nevertheless, Mersland & Oystein (2009) argue that there are another metrics that can shed more
light. First, expanding outreach means benefiting more women since this has been a priority since
the Grameen Bank. Second, the proportion of loans in Group Lending tells whether the MFI is
relying more on individual loans that require some sort of collateral, or is still benefiting those who
have nothing to guarantee the repayment. Lastly, the relation between rural vs urban loans also
counts as a proxy since the poorest of the poor tend to live in rural areas (Mersland & Oystein,
2009).
In assessing the impact of the so called “Mission Drift”, Cull, Demirg-Kunt, and Morduch
(2007, cited by the World Bank 2008) studied data from 124 MFIs in 49 countries and found that
both schemes of lending (pro-profit vs outreach) are profitable while serving the poor.
Nonetheless, there is a clear trade-off between profit generation and outreach when it comes to
serving the poorest of the poor (World Bank, 2008). Abate, Borzaga, and Getnet (2014),
implementing a stochastic frontier approach on data from Ethiopian MFIs, found evidence that
out-reach has a significant negative relation to the cost efficiency of MFIs (Yimga, 2018). Paxton,
Graham, & Thraen (2000) confirm in their country analysis that the trade-off between financial
sustainability and outreach to the poor does exist, since the costs associated with micro-loans are
higher compared to the mainstream credits (Mersland & Oystein, 2009).
On the other hand, Christen (2001) assess Latin American MFIs that became commercialized and
finds that their outreach did not drastically changed. Fernando (2004) also studies 39 transformed
MFIs and concludes that their financial situation improved without hurting their mission.
Littlefied, Morduch, and Hashemi (2003), conclude that MFIs with deeper outreach have a smaller
cost per borrower compared to those with bigger loans size, an efficiency indicator that might
offset the effect of the cost of providing smaller loans (Mersland & Oystein, 2009). Nevertheless,
all these studies are focused on certain players, countries, or regions, which means these results
cannot be replicated to the entire industry.

28
Pro-profits supporters claim that the clear connection between outreach and costs increments,
mounts up to justify this “change of heart”. There is an increasing emphasis in cost efficiency and
financial feasibility in the Microfinance realm, which responds to the competition from the entry
of incumbent banking players into the sector. Not only local players have entered the market for
diversification purposes, large commercial banks such as Citi, Deutsche Bank, and HSBC have
created microfinance divisions that aim to dominate. The entry of such players has “spurred
competition which in turn has driven interest rates and costs down making MFIs more effective in
controlling costs and increasing the variety of financial products available” (Yimga, 2018).
In addition, pro-profit supporters contend that centering into providing finance for the poorest of
the poor forces MFIs to rely on philanthropy and subsidies, which ultimately affect the service
quality. Also, there are relevant political and economic reasons to center in how to make financial
services available for all, not only in providing micro-loans to the poor (World Bank, 2008). Thus,
Rhyne (1998) and Christen and Drake (2002) claim that a Microfinance industry that tilts towards
commercialization is better equipped to serve the poorest of the poor, since profitability pushes
MFIs to be more efficient and to pursue new markets for their services (Mersland & Oystein,
2009).
Therefore, Mersland & Oystein (2009) performed a study assessing Mission Drift in 379 MFIs in
74 countries during the 2001-2008 period. In it, they concluded that there is no evidence supporting
that Mission Drift is present in the industry as a whole. Nevertheless, their panel data estimations
show that “the size of the average loan increases with increased average profit and average cost”
(Mersland & Oystein, 2009). This indicates that drift could happen if an MFI seeks higher returns
without becoming more cost efficient. Moreover, they also find that the average cost per loan tends
to be more relevant than the average profit in determining the size of the loans. Thus, special
attention should be paid in reducing costs to prevent a Mission Drift (Mersland & Oystein, 2009).
Mission Drift can be manifested in multiple levels, some arguably having a positive social impact
in the long-run. Nevertheless, once the profit element got into the equation sub-optimal results and
abuses rose in the Microfinance arena. While Mission Drift is not a topic usually mentioned in
traditional finance or banking, it is not rare to observe cases in which mismanagement and ill-fated
behavior have been translated in detriment and abuse on clients and the economy in general.
Economists claim that most of these misdeeds are market failures that result from the information

29
asymmetry between the stakeholders. The Microfinance Industry is not exempt from this
phenomenon. Even more, it is arguably more exposed than the habitual Financial Institutions.
Lastly, the potential for opportunistic behavior increases as MFIs moves away from the joint-
liability lending schemes that demand for some level of community engagement in monitoring and
collecting payments. In a context of harsher competition, multiple borrowing, and over-leveraging,
many MFIs have increasingly demanded for multiple types of collaterals which are not always licit
or fair (Duggan, 2016). Therefore, both Regulators and Donors should pay special attention to
signs of Mission Drift and changes in the MFIs lending practices.
Information Asymmetry: Adverse Selection and Moral Hazard
So far, it has been stated that the principal issues in providing credit to the poor are connected to
the risk management and the high transaction costs of reducing it via the monitoring, processing,
and enforcing micro-loans. This generally translates into an impediment towards scalability, or
financial sustainability, and interest rates way above the average in traditional commercial banking
(World Bank, 2008). The varied ownership structure and diversity of stakeholders in Microfinance,
make the Information Asymmetry the main source of risk for MFIs (Roberts et al., 2018).
Information Asymmetry (IA) is a well-known concept in the field of economics. The IA rises from
the fact that, in a decentralized market economy, different individuals have different levels of
information, and these differentials can deter the outcomes of the transactions between them. The
Nobel Memorial Prize in Economics’ laurate, Joseph Stiglitz (2002), points out two relevant
aspects about IA. First, some of the asymmetries are inherent because individuals naturally know
themselves better than anyone else does, and the rest of asymmetries rise organically in the
economic processes. Second, while IAs unavoidably happen, “the extent to which they do so and
their consequences depend on how the market is structured, and the recognition that they will arise
affects market behavior” (Stiglitz, 2002).
These two aspects are particularly relevant for the Microfinance Industry. First, the natural
asymmetries are difficult to offset because it is hard to store and retrieve information from the poor
and, likewise, the poor have limited access and understanding concerning the MFIs. Second, the
economic and regulatory environments in developing countries arguably are more likely to give
rise to deeper asymmetries with negative pervasive effects (Garmaise & Natividad, 2010). The
understanding of these elements is key for the scope of this work.

30
The Financial Institutions charge a fee for the costs of managing this asymmetry and the risks
involved with it. In theory, the fee comes from the difference between the interest they provide to
the capital owner or savers, and the interest they charged to the borrowers. Thus, the less
information available from a lender, the more risk and the greater the interest should be per keeping
the risk-return equation balanced (Sriram, 2015).
In general, there are two market failures that stem from the IAs. First, Adverse Selection (AS),
which is the inability of the MFIs to distinguish between high or low risk borrowers, and the
inability of borrowers to differentiate between trusted or not-trusted MFIs. Second, Moral Hazard
(MH), which is the tendency of some beneficiaries to use their loans in projects that would deter
their ability of repayment, or the propensity of MFIs to require collateral and loan policies
disadvantageous for the borrowers. In Garmaise & Natividad (2010), it is claimed that markets
with weaker institutions and regulations, IA considerations will increase the costs of raising funds
and could deter growth (Garmaise & Natividad, 2010). Per the World Bank (2008), substantial
evidence shows that MH is the main market failure affecting Microfinance, with AS having a
second role.
In their study on the effects of IA in the default of loans in the South African MFIs, Karlan &
Zinman (2006) discover that MH is pervasive in the market regardless of the characteristics of the
borrowers, while AS is mainly present on female borrowers or those who are having a lend for the
first time with a certain MFI. When assessing the effects of MH, they find that from 10% to 15%
of loan default comes from this market failure, and the rest comes from straightforward differences
in risk amongst the pool of borrowers (World Bank 2018).
Another assessment on the effects of IA in Microfinance was performed by de Janvry, McIntosh,
& Sadoulet (2006). In it, the scholars analyze how the entry of Guatemalan MFIs into the Credit
Bureau impacted in reducing the adverse effects of IA. They conclude that delinquency coming
from MH declined by 18% after the MFIs joined the bureau, while the decrease coming from AS
was considerably less but still present. The most relevant change in the group composition, after
the measure was implemented, was a large entry of men and exit of women which goes in line
with the conclusions drawn by Karlan & Zinman (2006) (World Bank, 2008).
Modern MFIs tackle the issue of Information Asymmetry and lack of trust through mutuality at
the local level. Meaning that they focus on figuring out demand and supply gaps at the local level,

31
to maximize the information available to bring trust back into the equation. In this context, every
little piece of information adds up to reduce transaction costs and frictions. Eventually, the
repetition of transactions and the creation of ledgers can build an “institutional memory” that can
replace the need of interpersonal trust or reputation in the current Microfinance schemes (Sriram,
2015).
The traditional theoretical view of credit transactions, even in the Microfinance sector, suggests
that the lenders are the only vulnerable party, not the borrowers. In practice, it has been observed
that wherever there are weak institutions and regulators, both sides of the coin behave in an
opportunistic way: borrowers can default and lenders can find ways to reclaim more than what
they agreed, in case of a default, or find illicit ways to request for repayments (Duggan, 2016).
Arguably, the great notoriety that Microfinance has achieved permeates to anyone claiming to be
an MFI. Therefore, not only those seeking for finance are more likely to let their guard down when
facing an MFI, but also it is more difficult to discern between well-intended and malicious MFIs.
Also, the focus on FI and outreach to the poor results in aiming at people who have never received
financial services or have enough financial literacy to deal with aggressive approaches. Therefore,
“As long as borrowers cannot reliably make these distinctions, stories of malfeasance by
Microfinance institutions may lead to a general punishment of the entire sector, as would-be
borrowers avoid MFIs and governments enact onerous regulations” (Duggan, 2016).
Yet if borrowers and other stakeholders tried to differentiate between well-intended and malicious
MFIs, the reputation alone would hardly eliminate these sorts of abuses. Without effective means
to verify whether a party is telling the truth or not, it will be troublesome for a third party to discern
between real claims of abusive behavior or fake ones (Duggan, 2016).
The existence of these threats results in interest rates that are considerably higher than those in the
mainstream banking. In most of the cases, the beneficiaries are aware of this and prepare to carry
this financial burden due to the lack of options or the higher costs coming from informal players.
When profit trumps over the social objectives, this can lead to abuses with devastating results.
Therefore, the transparency and governance of the MFIs play a major role in preventing abuses
and providing incentives for improvements in performance.

32
Transparency and Governance
A relevant amount of friction may arise if stakeholders are not able to verify whether their
objectives are met or not. Donors want to make sure their money is used efficiently and is having
a positive impact in excluded communities. Creditors are concerned about the use of the loans and
the MFIs’ ability to repay them. Borrowers want to have full disclosure of their loans’ terms and
conditions, and want to make sure they are charged fair rates. Lastly, Governments and regulators
are concerned with the health and stability of the entire Microfinance sector (Roberts et al., 2018).
Roberts et al., (2018) citing Barry and Tacneng (2014) recall that “at a time when over-
indebtedness and corporate governance are the topmost concerns facing MFIs, transparency in the
microfinance industry has become an important consideration.” (Roberts et al., 2018).
The accelerated growth that the Microfinance sector experienced over the last two decades has
exposed its structural vulnerabilities. Moreover, abuses from MFIs in multiple countries, such as
the 2010 Microfinance crisis in India, have caused a great reputational damage and raised questions
regarding the effectiveness of the Microfinance movement. All of this has been the source of the
increasing criticism over the lack of disclosure, and the feeble regulatory environment in the
industry. Thus, stakeholders are increasingly demanding for more transparency to strengthen the
trust mechanisms and protect the interests of all the involved parts (Roberts et al., 2018).
Quayes and Hasan (2014) claim that “providing timely and accurate information to stakeholders
can reduce information asymmetries, attract more funds, and improve MFI competitiveness”
(Quayes and Hasan, 2014). Nonetheless, poor MFIs’ disclosure may be the result of perceived loss
in competitiveness, fear of scrutiny, high costs of producing information, and efforts to preserve
the entire control over their operations. Additionally, Yaron and Manos (2010), contend that
greater MFI transparency could help to reduce the drawbacks of Information Asymmetry, and
guide the MFIs’ relationships with their stakeholders. Therefore, an improved comprehension of
the elements affecting the transparence of the MFIs can be used as a great contribution to develop
policies that promotes MFIs information disclosure (Roberts et al., 2018).
Solid MFI-stakeholder dynamics can improve the MFIs performance, avoid the over-leveraging
from clients, and enhance the long-term sustainability of the MFI. “Failure to consider the
importance of stakeholders may impact the MFI sustainability” (Freeman, 1984; cited by Roberts
et al., 2018). Barry & Tacneng (2014), claim that bigger commercial banks, cooperatives, NGOs,
and MFIs perform better than their smaller counterparts. Roberts et al. (2018), point that the size

33
of the MFI regulates the “association between the MFI ownership structure and transparency”
(Roberts et al., 2018).
The Donor’s willingness to fund MFIs heavily relies on the availability of performance data, both
in financial sustainability and outreach. Yet, information disclosure practices and requirements are
grounded on cultural and regulatory aspects that differ from country to country. Also, the absence
of a proper client protection policy and strong regulatory bodies demanding transparency in
lending criteria and practices, has led to over-indebtedness of borrower and unethical lending
behavior. This reinforces the threats coming from information asymmetry (Roberts et al., 2018).
Roberts et al. (2018) conclude that the financial sector development and its size are crucial
elements when determining MFIs’ level of transparency. In general, MFIs present low
transparency when the financial system well developed, and bigger MFIs are more transparent
than smaller ones. Also, they detect that NGOs tend to be more transparent that the other type of
MFIs, and that maturity and size of them also have a positive relation with their level of
transparency. Lastly, they find that MFI transparency is positively connected with the regulatory
frameworks but negatively with the institutional environment (Roberts et al., 2018).
Transparency and Governance are key to tackle the pervasive effects of Information Asymmetries
and the improvements in performance. The lack of proper reporting channels and enforcement of
good practices can lead to abuses that deter the reputation and the positive impact of the MFM.
Unfortunately, the lax regulation that industry has experienced overt the last decade has been
translated in scandalous cases of abuse present in all geographies.
Cases of Abuse from Microfinance Institutions
As Duggan (2016) points out, “In places where any lender can simply call itself a MFI,
opportunistic lenders can use the halo effect associated with microfinance to encourage borrowers
to make themselves unusually vulnerable to theft” (Duggan, 2016). This has been the case in most
of the Sub-Saharan African nations and parts of South Asia, where almost anyone can create a
MFI overnight just due to the feeble rule of law and the little control Governments enforce on
MFIs (Duggan, 2016). Also, Bhatt (2001) supports this statement by signaling that some MFIs
have faced issues with elevated default rates in multiple geographies. Chakrabarty & Bass (2013),
claim that loan defaults are not only bad for the Microfinance industry due to the losses they
generate, but also from the political and social effects that they can untangle. This, as Montgomery

34
(1996) and Hulme (2000), “has proven to be a trigger for serious social effects such as riots,
deterioration of community relationships and even suicide and death” (Hulme, 2000; Montgomery,
1996, cited by Kringler, 2016).
Seeing that the dominant frameworks have given MFIs more extrajudicial means to recover debt,
and vulnerable borrowers are encouraged to deal with new institutions and lending methodologies,
it is not a surprise that room for abuses is pervasive. Furthermore, if borrowers do not have the
means to properly differentiate between trustworthy MFIs and scammers, the overall reputation of
the Microfinance industry can get distorted. If the ill-intended behavior of a small proportion of
MFIs can hinder the trust in the industry, then “overall costs of this malfeasance stand to go well
beyond the value of the property that was actually stolen” (Duggan, 2016).
Countries such as Bolivia, Morocco, and Nicaragua have suffered Microfinance crises as the
accelerated growth of the sector led to client over-indebtedness. In extreme cases, the MFIs’
payment collection methods have come under harsher scrutiny, notably after the rise of the Indian
Microfinance Crisis of 2010, in which multiple borrowers from the state of Andhra Pradesh
committed suicides ascribed to loans from MFIs and their recollection methods (Duggan, 2016).
Other countries have also witnessed similar abuses in terms of illicit collection by MFIs. In
Bangladesh, the illegal repossession of assets, including the very roofs of borrowers’ homes, is
quite common. In Nigeria, beneficiaries have lost all their money falling prey of pyramid schemes
that were marketing themselves like banks. In China, leaders of credit and rotating saving groups
have disappeared with all the funds. Lastly, the former requirement of ATM cards as collaterals
by MFIs, pushed the South African Government to ban all sort of collaterals provisions (Duggan,
2016).
Whilst most of the existing literature have focused so far on the institutional failure and
incompetence, they have bypassed the assessment of how lending contracts might make borrowers
vulnerable to malicious lenders. Moreover, borrowers encounter risks not only derived from the
advertisement, structure, and enforcement of contracts, but also from the risk that MFIs could
break the contract to steal the funds of their beneficiaries without facing any repercussion (Duggan,
2016).
Unfortunately, researchers used to omit these issues, mainly because of a strong selection bias in
the available quantitative data on MFIs. A serious predilection towards large-scale quantitative
analysis has resulted in a limited view of the sector that only focuses in the large MFIs, since these

35
allow researchers to study them or are forced by national Governments to disclose their
information. This phenomenon has could have important implications in policy making since most
of what is known, and perceived from, MFIs comes from the systematic analysis of such data.
Therefore, researchers and policymakers should be careful in extrapolating the inferences drawn
from this research without considering the selection biases (Duggan, 2016).
Arguably, the presence of abuses in the Microfinance sector not only stems from the ill-intended
managers. The issues of high operation costs, lack of financial sustainability and scalability, and
the existence of mission drift creates incentives for the deviation of MFIs and for the adoption of
practices that might be detrimental for poor borrowers. Also, the lack of transparency and proper
governance do little to prevent the rise of malicious and rent-seeking behavior.
Regardless of this grim view of the Microfinance Movement, a beam of light appears when
considering the role of Information Technologies in the financial sector as a whole. Many experts
in the area claim that digital innovations are likely to disrupt the entire Financial System, making
it more transparent, fair, and democratic. The Microfinance industry is not an exemption in this
forecast.
Information Technologies: Innovative Solutions for Structural Challenges
Chibba (2008) states that the FI initiatives that leverage on technological innovations, especially
in telecommunications, are increasingly penetrating in developing countries, such as Philippines
and Guatemala. The poor and marginalized are increasingly reached by approaches such as mobile
banking, prepaid card, and electronic kiosks.
The adoption of new delivery channels such as agent banking, mobile phone money transfer
services, Microfinance banks, and relaxed Know-Your-Customer requirements are imperative in
reaching the unbanked. It is critical for the FI efforts to implement policies that accelerate the
adoption of regulatory reforms, innovative technology, and the development of infrastructure that
reduce the operation costs and allow the delivery of financial products and services “more rapidly,
efficiently and conveniently to broad sections of the population” (Adunda & Kalunda, 2012).
The World Bank (2008) contend that new technologies can increase the efficiency of MFIs and
expand the access possibilities for the beneficiaries. The efficiency gains can reduce the operation
costs of such institutions, which could enable the provision of small loans that are finally suitable
for the people at the bottom of the BOP. An example that sheds light of this potential is the case

36
of mobile banking in South Africa. Currently, there are more mobile users in Sub-Saharan Africa
than bank account holders. This condition empowered companies, such as the Kenyan payment
system M-Pesa, to leverage from the mobile penetration to integrate a payment system that can be
used by people in remote areas or with certain levels of marginalization. The success of M-Pesa
has been such, that it has lifted an estimate of 2% of Kenya’s households, has empowered over
185 thousand women to move into SMEs, and is used by 96% of the rural population (CNBC
Africa, 2017).
Another interesting example is the case of “Desjardins Movement” (DM), an NGO MFI in Canada.
DM created a Credit Committee to ensure that the information of its beneficiaries was available
regardless how big the MFI became. The members of the committee were meant to store the
information of the customers in their area, and thus, “bridged the information asymmetry” (Sriram,
2015). Once new technologies were adopted, the credit committee ended up becoming redundant
since it became possible to safely store the borrower behavior and its credit history. There were
even more changes in DM with the raise of IT, “Information on alternatives for lending and
borrowing was available without inter-mediation of a bank-like institution. In this scenario,
borrowing institutions reduced transaction costs due to reduced asymmetry of information”
(Sriram, 2015).
Yimga (2018) supports the claims of the World Bank by asserting that new technologies and
outreach channels “may positively influence microfinance efficiency” (Yimga, 2018). The raise
of IT systems such as mobile banking, biometric ID, and cloud-based Information Management
Systems for small enterprises, pave the way to reduce the cost of scalability for MFIs. This,
ultimately, will help in expanding the outreach of most MFIs, probably enabling reaching the
poorest of the poor. “Under these circumstances, microfinance expansion and efficiency seem to
be compatible objectives” (Yimga, 2018). Allen et al. (2014), in the specific case of outreach for
the rural poor, also concurs by stating that the use of modern technologies, especially mobile
banking, has the potential of smoothing the sustainability disadvantages of scaling rural MFIs.
This, could be achieved mainly by the reduction of operation and transaction costs, although is
more likely that this technology will be more suitable for payments and remittances instead of the
provision of loans (Allen et al. 2014).
By fostering the channeling of payments and remittances through formal Financial Institutions,
technological innovations have the potential to increase the deposit base of these institutions,

37
enabling the intermediation of more funds to the private sector. If Financial Institutions can
increase their knowledge on their clients and their creditworthiness, which can be drawn from the
reception of remittances, some of the beneficiaries of this service might become borrowers. Thus,
receiving remittances from Formal Financial Institutions might help recipients to gain access to a
broader selection of financial services (World Bank 2008).
“Blockchain technology has been heralded by many as the next big thing” (Hernandez, 2017). The
potential of Blockchain is in the spotlight of the media, national governments, and multinational
organization such as the International Monetary Fund (IMF) and the UN. Pundits claim that in the
next two decades, the Blockchain will transform society even more than the internet has
transformed media (Hernandez, 2017).
Having the potential to substitute the dominant Financial Institutions by enabling cheap,
transparent, and secure transactions, Blockchain can also be implemented in the realm of the
development with the potential to “offer new ways to track aid and tackle corruption, facilitate
smart-aid contracts and cut costs for international payments, but experience suggests it is through
adding value to existing development processes that it could have the most benefit” (Hernandez,
2017).
Blockchain: The Future for Transparent Transactions
What is Blockchain?
The origin of Blockchain can be traced back to October 2008, when Satoshi Nakamoto published
the white-paper behind the idea of Bitcoin. In it, Nakamoto exposes how the Blockchain
technology can solve the double-spending problem and be the building stone behind decentralized
currencies (Zwitter & Boisse-Despiaux, 2018). The solution proposed by Nakamoto consists in
using a decentralized ledger with network-enforced processes that are supported on a proof-of-
work consensus mechanism for updating the ledgers (Davidson, De Filippi, & Potts, 2016).
A Blockchain, also known as Decentralized Ledger Technology (DLT), is a data structure which
allows to create tamper-proof digital ledgers and to share them. The cryptographic component
enables anyone to access and add into the ledger securely. There is not a third party acting as a
middleman or authority. It is near to impossible to remove or alter data recorded on the ledger.

38
Therefore, Blockchain can arguably diminish or eradicate fraud and corruption, and reduce
transaction costs (Kshetri, 2017).
Per Zwitter & Boisse-Despiaux (2018), Blockchain “is a decentralized database, which stores a
registry of assets and transactions across a peer-to-peer network”, which differs from the regular
Peer-To-Peer (P2P) networks by not duplicating the content that has been transferred and
registering the value of such transactions using cryptographic techniques (Zwitter & Boisse-
Despiaux, 2018). For Evans (2014) it is a public decentralized ledger platform. For Davidson, De
Filippi, & Potts (2016), it is a technology designed to solve the double-spending problem
(Byzantine General’s problem) for digital currencies that work as decentralized P2P cash systems
(Davidson, De Filippi, & Potts, 2016).
In summary, a Blockchain is a “way of creating a robust, secure, transparent distributed ledger”
(Davidson, De Filippi, & Potts, 2016). Since Blockchain is based in cryptography, it can be
considered as a new technology for public databases or as a social technology that built for people
coordination (Davidson, De Filippi, & Potts, 2016). Therefore, the applications of Blockchain go
beyond the realm of the Bitcoin and cryptocurrencies, having the potential to disrupt multiple
sectors, including the Microfinance industry.
Elements of the Blockchain and its Implications
All the potential benefits that lay behind the Blockchain Technology (BT) stem from three main
elements of its structure: The composition of the blocks, the consensus mechanism, and the
decentralization and openness of the ledger.
Regardless of how complex the Blockchain might be perceived, its name is quite straightforward.
The so-called Blocks are batches of validated transactions that are encoded and arranged into what
is known as Merkle Tree (See Appendix 1). Each Block contains a cryptographic hash of the
previous block in the Blockchain, connecting both. Therefore, this connection of blocks form a
chain (The Economist, 2015). When a block has attained its limit of transaction hashes, it is lined
up with the previous blocks forming a Blockchain (Zwitter & Boisse-Despiaux, 2018).
A hash is a digital mechanism that compresses data into a specific format with a determined length.
For example, the hashing algorithm used by BTC is SHA-256, which stands for Secure Hashing
Algorithm, with a hash length of 256 bits. Therefore, by using this algorithm the resulting hashed
data will always be 256 bits long (ConsenSys, 2016). Thus, the hash acts as numerical fingerprint

39
which contains all the elements of the transaction and is imbedded in all future the transactions,
becoming the linking factor amongst all the blocks. Moreover, the utilization of hash functions in
the Blockchain is the key element to assure immutability because, in order to modify a transaction,
all the previous transactions and their copies should modify simultaneously. Otherwise, the hash
numbers will not match the records existing in all the Blockchain copies (Zwitter & Boisse-
Despiaux, 2018).
Blockchain keeps its integrity and remains immutable due to its consensus mechanism, this mainly
relies on two features: the “hashing” and the “Proof-Of-Work”. The Proof-of-Work (PoW) is a
mathematical problem that guarantees that no user will be able to know up-front which node will
be validating the transaction. Solving this problem is normally called “mining”, and is also
performed by members of the network. Since the validation of the transaction leads to receiving
an economic incentive, all the computers in the network compete in solving the mathematical
problem (Zwitter & Boisse-Despiaux, 2018). Hence, the PoW is the key mechanism that behind
the validation of each transaction.
The Blockchain is safe due to its decentralized nature. Since the history of every transaction is
stored in blocks of data that are cryptographically tied and this block is replicated on every
computer inside the network, Blockchain is “an immutable, secure, and transparent record of all
transactions that have ever taken place” (Zwitter & Boisse-Despiaux, 2018).
Lastly, Blockchains have the capability to sustain different levels of openness. The Permissioned
Blockchain, is a private Blockchain in which only the participants of it have full accessibility on
the information. The permissionless is a fully-open Blockchain that anyone can access. Also, there
are specific-purpose and general-purpose Blockchains. The specific-purpose are fit for the
management of assets, and the general-purpose are designed to permit users to develop programs
that can be stored on the Blockchain and can be automatically executed in a distributed way.
Regardless of these differences, BTs always share specific features: decentralized consensus,
immutability, cryptographic trust, resistance against tampering, and secure information sharing
(Kewell, Adams, & Parry, 2017).
With the previous contentions in mind, the differences between Traditional Ledgers and
Blockchain Technology can be summarized in the following table:

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Table 1. Comparison between Traditional Ledgers and Blockchain Technology
Traditional Ledgers
Blockchain Technology
Centralized: A single entity validates every transaction,
making them vulnerable by having just a single point of
failure.
Decentralized: Every member of the network holds a
copy of each transaction, eliminating the single point of
failure.
Opaque: Only authorized members have access to the
information in the ledger.
Transparent: Any member of the network can access
the data in the ledger without restrictions.
Changeable: Information can be modified by members
with overriding privileges.
Immutable: The information on the ledger is set in
stone.
Vulnerable to Theft: Multiple cases of identity and
information theft by hackers.
Encryption and Pseudo-Anonymity: Cryptography
impossible to break.
Time Lag: Depending on the systems used the
transactions can take days to be registered and
validated.
Fast entries: Transactions are completed, registered,
and validated in matter of minutes (depending on the
Blockchain’s architecture and computational power).
Source: Hernandez, K. (2017). Blockchain for Development–Hope or Hype?.
Lastly, the main virtues of Blockchain can be summarized as:
1. Censorship Proof: no entity can unilaterally decide which content will be stores in the
Blockchain.
2. Reliable: the Blockchain can be trusted in clarifying and transferring assets correctly.
3. Pseudo Anonymous: the Blockchain detects asset owners uniquely using individual
pseudonyms, but it can also retain the real-world identity.
4. Secure: it impedes the manipulation, the copy, or the double spending of any asset ownership.
5. Resilient: it verifies, clarifies, and transfers ownership regardless malicious attempts.
6. Consistent: consistency increases over time.
7. Upstanding: the Blockchain keeps the data integrity and consistency, and guarantees security
to every transaction, and the entire history of transactions (Drescher, 2017; cited by Zwitter &
Boisse-Despiaux, 2018).
For further understanding on the technical details and the functioning of the Blockchain
Technology, see the Annex section at the end of this work.

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Blockchain Landscape
Bitcoin and Cryptocurrencies
In early 2009, BTs were used to power the famous Bitcoin, a cryptocurrency-based protocol for
the trade of tokens called bitcoin. The Bitcoin (BTC) and the cryptocurrencies gained notoriety in
2013 with the steep rise in the Bitcoin price which passed the $1,000 USD mark (Mainelli & Smith,
2015). Then, in 2017 the Bitcoin went mainstream when it reached the value of $19,900 USD,
after having a value of $960 at the beginning of that year. In the same period, Bitcoin attained a
market capitalization of $320 billion USD surpassing that of multinationals such as Walmart and
even the total value of all UK currency notes in circulation. Silicon Valley personalities such as
Steve Wozniak (Co-Founder of Apple Inc.) and Jack Dorsey (Founder of Twitter) supported the
BTC, stating that it should be a worldwide currency (Koticha, 2018).
Ever since its ascension, BTs have received negative press coverage mainly due to the cases in
which Bitcoin have been linked with illicit and illegal acts such as drugs and weapons dealing
(Kewell, Adams, & Parry, 2017).
While Bitcoin has been troublesome in legal, social, and economic terms, and there have been
technical glitches with the Bitcoin wallets, the BTs have proven to be robust. In fact, as a test to
prove the Blockchain robustness, BTC has been outstanding, showcasing that the Blockchain is
resilient against a wide variety of attacks, from hackers to National security agencies. The success
of BTC in this matter has raised the interest of companies such as Nasdaq, BNY Mellon, UBS,
USAA, IBM, Samsung, and the number is increasing (Mainelli & Smith, 2015).
Ethereum and the Smart-Contracts
The increasing reputation of Bitcoin and the BTs gave rise to the creation of multiple
cryptocurrencies that aim to satisfied different needs in the financial sector. Amongst all the
cryptocurrencies that have appeared over the last decade, Ethereum has taken the spotlight due its
capacity to hold self-executing programs on them. Ethereum was proposed in 2013 by Vitalik
Buterin, a Blockchain developer, and went live in 2015 backed up by crowdsourcing (Chohan,
2017). Following the BTC trend, Ethereum’s value went above the $870 USD in December of
2017, after having a value of $8 at the beginning of that year (Kothica, 2018).

42
“Ethereum aims to be a superior foundational protocol, and allow other decentralized applications
to build on top of it instead of Bitcoin, giving them more tools to work with and allowing them to
gain the full benefits of Ethereum’s scalability and efficiency. ... [It aims to] provide a system such
that users can be guaranteed that no matter with which other individuals, systems or organizations
they interact, they can do so with absolute confidence in possible outcomes and in how those
outcomes might come about.” (Davidson, De Filippi, & Potts, 2016).
Ethereum allows to write and enforce what is known as Smart-Contracts (SCs), which can support
decentralized applications including Distributed Autonomous Organizations (DAOs). SCs and
DAOs facilitates the implementation of the Internet of Things (IoT), “which ultimately must
require a decentralized register because its scale will vastly exceed any possible centralized ledger”
(Davidson, De Filippi, & Potts, 2016).
The SCs are basically bank accounts for contracts embedded in Blockchains in the form of code
with predetermined conditions that self-execute and automatically distribute funds once these
conditions are met. Therefore, SCs can help to reduce response time to crisis by automatically
distributing funds to vulnerable groups when certain natural disasters happen or if the potential of
an epidemic breaks down (Hernandez, 2017). Also, SCs can be understood as computer protocols
that promote, verify, and enforce the performance of a contract: self-executing code. They are the
automation of the performance of contracts which only can be executed when determined
conditions are met, therefore eliminating the need for third-party resolution (Kewell, Adams, &
Parry, 2017).
Prospects for Social Innovation
Over the last decade, the involvement of the Non-Financial private sector has proved as being
essential to FI. The crucial role of digital and communication technologies, and market-based
approaches to serve the BOP through alliances that involve Financial and Non-Financial
organizations is resulting into promising products and services. Amongst many advances, the
mobile phone penetration, the exponential growth in information technologies, and the appearance
of biometric reliable technology have penetrated the mainstream finance sphere (Chibba, 2009).
With such openness from the financial sector and faster response coming from regulators, it is just
a matter of time to see BTs disrupting the whole sector.

43
Various NGOs and MGOs are experimenting with BTs to augment the efficiency, transparency,
and accountability of both public and private funding instruments. The projects have already
leveraged Blockchain in channeling donations and funds transparently, granting and managing IDs
to refugees, and creating trustworthy property registries. While these advancements pose a
promising future for BTs in the development sphere, they also raise concerns regarding privacy
risks (Zwitter & Boisse-Despiaux, 2018).
So far the Blockchain has centered in the creation and distribution of cryptocurrencies (Blockchain
1.0). On the contrary, the Development sector will likely use BTs to increase efficiency and
transparency in the automatization of logistics and IT infrastructure, such as digital identities and
smart-contracts (Blockchain 2.0). The current applications of smart-contracts are barely scratching
the surface in terms of the potential of implementation. Zwitter & Boisse-Despiaux (2018) argue
that forecasted-based financing could be implemented with smart-contracts in funding entities and
partners. The deployment of Big Data to predict the onset of any crisis and to use objective metrics
to trigger transactions via Smart-Contracts to engage in disaster risk reduction and conflict
management in a preventing way (Zwitter & Boisse-Despiaux, 2018).
Even the UN has been actively engaging with BTs for achieving the MDGs, especially in the
provision of identities and financial inclusion (Kewell, Adams, & Parry, 2017).
Remittances and International Payments
Kunt & Martinez Peria (2007), support that distributing remittances through formal Banking
Institutions increases the FI via bank outreach. The probability that a recipient holds a bank account
doubles if remittances are channeled through banks instead of informal channels (World Bank,
2008).
Transactions done using Blockchain technologies are borderless. The marginal fee charged for
these transactions is fixed regardless of the origin or the destination. The transaction costs on
remittances have historically been very high. Generally, immigrants use remittances services such
as Western Union, which cost up to 7% of the funds transferred. In transfers from South Africa to
neighboring countries, transfer fees can vary from 5% to 23% of the transaction value depending
on the kind of service used (Kshetri, 2017). Additionally, Hernandez (2017), supports these
estimates by stating that the global average remittance cost ranges from 7.6% to 20% of the amount
sent (depending on the countries of origin and destination.

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Blockchain has the potential to significantly diminish the operation costs in multiple sectors. The
World Bank determines that yearly savings of US$16bn can be achieved with a cost reduction of
5% (Hernandez, 2017). Per Santander, by enabling cross-border payments and trading, and simplify
processes and regulations, BTs are likely to cause cost savings ranging from $15bn to $20bn USD
by 2022 (Kshetri, 2017).
In 2015, Santander implemented a trial version of a Blockchain-based app that can allows transfer
from £10–10,000 in Euros to 21 countries, and in USD to the US. In Mexico, mexBT launched a
Blockchain platform for remittances between LatAm and Asia, the system allows transfers in both
BTC and fiat currencies (Kshetri, 2017).
Albeit the cutting-cost potential that Blockchain has in the remittances industry, there are still
environmental aspects BT developers must keep in mind. As Gibston et al. (2006) find in their
study of ATM usage by Tongan immigrants in New Zealand, there are three main barriers
hindering the use of ATMs by this group: not knowing how to operate the ATM, long distances
between the ATMs and the immigrants, and lack of trust in the security of the ATMs. Remittances
services powered by BTs should try to match the convenience and trust offered by incumbent
players when deploying solutions (World Bank, 2008).
Digital Property Registries and Digital Identity for All
The DLT has been used for land tenure and property rights purposes. Regardless of multiple
efforts, nowadays 90% of the land in Africa has not been registered, and in India, not having a
property is considered a stronger cause of poverty than caste levels or lack of education (Zwitter
& Boisse-Despiaux, 2018). In the same way, the lack of land ownership remains among the biggest
barriers for entrepreneurial activities and economic development. Estimations suggest that more
than 20 million families in rural India lack legal ownership to the lands in which they inhabit and
work (Kshetri, 2017). Therefore, BT opens an array of possibilities for properly addressing
corruption, uncertainty, and abuse in the land registration domain.
Land grabbing and land related frauds continue to be an issue in developing countries in which the
BOP is the most exposed to. The lack of the Rule of Law and corruption in these countries foster
the manipulation of paper registries by fraudulent groups. All over the world, there are documented
cases of farmers and micro-entrepreneurs have been dispossessed from their assets with rigged
titles or falsified documents (Kuznetsov, 2017). Registries that cannot be tampered and that are

45
publicly available can utterly diminish this type of abuses.
“As an immutable, time-stamped ledger, the Blockchain is an attractive tool to prove ownership
and existence” (Hernandez, 2017). Ownership manipulation would be rendered impossible with
the proper implementation of Blockchain solutions. The information disclosure that exists in the
Blockchain impedes any attempt of retroactive change or tampering. Developed countries, such as
Sweden and Japan, are presently testing multiple BT applications for land registry. It is time for
developing countries to follow up and to take advantage of the advancements done by these pioneer
nations (Kuznetsov, 2017).
Multiple Blockchain projects, such as Bitfury in Georgia and Factom in Honduras, have already
implemented aiming to improve land registry and property rights. (Hernandez, 2017). Bitland uses
Blockchain to map land documentation in Ghana, offering registries which later eases the
mobilization of funds and a transparent property market. Similar projects are being implemented
in Honduras, Sweden, and Georgia (Kewell, Adams, & Parry, 2017). Per Hernandez (2017), asset
registration may allow vulnerable groups in developing countries to seize up to US$20tn for capital
without any proof of ownership (Hernandez, 2017).
Approximately 1.8 billion people have no legally recognized identity. The lack of identity pushes
the affected people to live on the margins of the society, without the right to participate in
democratic, educative, healthcare, and formal economic activity. Part of this problem stems in the
centralized nature of the phenomenon, since most of the identities are provided by some legal
authority; mainly local or national governments. The features of BTs provide a feasible alternative
to build identities from the bottom up, which frees identities from the control of a central authority
without leaving it vulnerable to modifications or theft. Moreover, individuals have the capacity to
decide which elements are made public or not (Kewell, Adams, & Parry, 2017).
There are various initiatives already utilizing Blockchain for the creation of digital IDs. For
example, Cambridge Blockchain is a startup building a Distributed Digital Identity System that
allows Financial Institutions to eradicate redundancies in managing customer data. Also Civic is a
platform that combines BT and Biometric information in mobile devices for multi-factor safe
authentication (Ciobanu, 2018). Moreover, the Finnish startup MONI has been collaborating with
the Finnish Immigration Service since 2015 to provide digital identity numbers to refugees in
Finland, these numbers allow them to get bank accounts and loans. Also, Microsoft and Accenture

46
have been partnering with NGOs in a Public-Private partnership called ID2020, which aims to
support the UN’s goal in providing legal identities for all (Juskalian, 2018).
Beyond the clear economic gains that these initiatives would unveil, property registry and
trustworthy identification are key to develop transactions and credit histories which could
drastically reduce the IAs and facilitate the risk management when providing financial services to
the poorest of the poor. Identities are one of the pillars of our societies and a universal right that
Blockchain could help to secure.
Fair-Trade and Ethical Sourcing
Several experts have emphasized the possible impact that BTs could have in the supply chains.
The implications of BTs implementation in this area could lead to spillover effects in the
development and social realms. The traceability achievable through Blockchain could help to
identify wages and labor abuses, or even to keep track of the veracity of certain fair-trade programs.
Therefore, DLTs can create inclusive and fair supply chains that empower vulnerable groups
(Zwitter & Boisse-Despiaux, 2018).
Identifying the origin of products and services across intricate supply chains need transparent and
immutable metadata infrastructure, which must be trusted by all the stakeholders while,
simultaneously, be flexible to adapt to multiple circumstances and environments (Thiruchelvam,
et. al, 2018). Additionally, BTs permit the buildup of reputation to link trading partners directly.
For example, big multinationals with complex supply chains, such as Walmart, can provide direct
financing to their suppliers in the developing world to build capacity or improve processes
(Kshetri, 2017).
One of the most notable examples of the implementation of BTs in supply chains is in the coffee
industry. The adoption of Blockchain in the Coffee Supply Chain could be key to simplify the
supply chain process via digitalization and automatization, which can track the origin of raw
materials and guarantee fair trade policies (Thiruchelvam, et. al, 2018). The Swiss Coffee Alliance,
- a coffee trade group that supports producers with technological expertise- and Ambrosus – a
Blockchain and IoT integrator for quality assurance in food and pharma - announced a partnership
in 2018. This collaboration aspires to reduce the unethical practices, especially the uneven profit
distribution in the coffee supply chain. For example, while global coffee sales rose from $30bn
USD in 1991 to $81bn USD in 2016, the small famers have seen their income falling from 40% to

47
under 10% in the same period. Even more, farmers in the top producing countries, such as Brazil,
Colombia, Vietnam, and Indonesia, live in poverty with just enough money to break-even their
production (JOENG, 2018). The diamond industry is another sector which can be drastically
benefited from BTs. De Beers, the diamond giant with over $5bn USD in sales, is working on
Blockchain solutions to enhance the traceability of the diamonds across the entire supply chain
(Sanderson, 2018).
Reduction of Corruption
The decentralized and trustless nature of BT has the potential to reduce corruption by allowing
transparency and accountability amongst the government transactions. Based on the same
architecture of supply chain solutions, public Blockchains with identified parties can eradicate
bribes, fraud, and funds deviation from public entities. For MFIs, fully disclosed ledgers, end-to-
end from donors to beneficiaries, could be a milestone that ensures that funds are allocated
properly, without any abuse to the stakeholders, or the existence of funds with “unethical” origins
or endings in the financial supply chain (Zwitter & Boisse-Despiaux, 2018).
Blockchain can also be used to create “Qualified money”, which are funds specifically
programmed to serve certain functions or to be executed under certain circumstances via smart-
contracts. The autonomy of such funds naturally increases accountability to both beneficiaries and
donors, and leaves no room for corruption if the conditions can be meet in a digital way without
any sort of tampering (Zwitter & Boisse-Despiaux, 2018). BTs can also enhance internal and
external auditing. Auditors can perform real-time inspections of data and the registries can be
examined on daily basis instead of yearly, which ultimately reduce corruption and fraud (Kshetri,
2017).
Also, Blockchain can empower NGOs’ and other type of donors. Notably, it can make sure that
funds reach their intended beneficiaries and are spent in a proper way, For example, Bankymoon
– a South African bitcoin startup- allows African public school to crowdfund their utility expenses
by employing smart meters and Blockchain technologies to connect donors directly to the schools.
With this technology, donors can track the electricity that is being used by the schools and estimate
the energy their donations can buy (Kshetri, 2017). In 2016, Ant Financial, Alibaba’s online
payments partner, announced the development of BTs for their payments. Blockchain was initially
implemented in Alipay’s donation platform, where Donors can track transaction records, and

48
understand the destination and use of their donations. The objective of this initiative is to boost the
transparency and offer a trust mechanism by recording each transaction on the Blockchain
(Kshetri, 2017).
The rise of high-profile frauds has fostered BTs attractiveness amongst financial institutions. Ever
since Standard Chartered lost about $200 million USD from the Qingdqo fraud, the multinational
has partnered with DBS group and Singapore’s Infocomm to create Blockchain-based solutions.
Even the big commercial banks such as Bank of America and HSBC have begun their research on
Blockchain implementation for trade finance and other applications. In 2015, the Bitcoin
Foundation Ukraine and KUNA Bitcoin Agency signed a MOU with Kyiv Regional State
Administration to carry out a Blockchain-based e-governance system in the city of Odessa. The
objective of this initiative to assure fair and transparent auctions, and eradicate the chance of
document forgery (Kshetri, 2017).
As previously seen, fraud in the Microfinance industry has been unbridled in multiple geographies.
In the 2010-2012 period, the president of the Adoor Sree Narayana Dharma Paraipalana Union, in
India, received credits of around $1.15 million USD from the Bank of India on behalf of 5,000
families. The families had not asked for the loans but bear the debt collection proceedings. To
prevent such abuses, Tech Bureau and Infoteria implemented a Microfinance service in Myanmar
using the Blockchain platform Mijin to transfer loans and the account data in the system to local
MFIs (Kshetri, 2017).
Blockchain as a Correction Mechanism
In general, systems tend to centralization because this form of organization is the most efficient to
devise, settle, and enforce rules. Centralization hinders duplications, enacts hierarchies, and
provides arbitrage in disputes. However, these qualities pose a threat if the authorities of such
systems have facility to exploit them. “Centralization brings order, but this order can be brittle,
and adaptation toward decentralization begins to make the system more robust, flexible, secure
and efficient” (Davidson, De Filippi, & Potts, 2016). Centralization is born by and for trust, which
can be used to subtract benefits when the trust is politically built. This leads to rent-seeking
behaviors, which can be detected as an endemic dysfunction of centralized systems stemming from
the dispersion of resources in the search of obtaining such benefits. Decentralization has the

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promise to be a vaccine against rent-seeking practices when trust comes from cryptographic rather
than political means (Davidson, De Filippi, & Potts, 2016).
When Blockchain gets analyzed under the economic umbrella, it is clear that Blockchains behave
like markets due to its decentralized nature. “Markets are often efficient governance institutions
for spot contracts (a pure exchange economy), but where economic activity requires coordinated
investment through time (asset specificity), or an ongoing relation between parties (frequency), or
involves uncontractable dealings (uncertainty), alternative governance institutions, including
hierarchies and relational contracting, can be efficient ways to deal with the hazards of
opportunism”. In a political-economy perspective, the Blockchain can be considered as a type of
private order competitive federalism, since no entry barriers to one or more Blockchains is
equivalent to “voting with ones feet”. Therefore, efficiency gains come from the eradication of
rent-seeking behavior, which likewise is derived from the eradication of a centralized monopoly
control over the laws or the rules of the game (Davidson, De Filippi, & Potts, 2016).
Blockchain supporters claim that while societies normally required governance institutions such
as banks and governments to manage uncertainties around trust, BTs could make traditional
institutions obsolete by allowing individuals to perform transactions safely and transparently with
just technology, without the need of external central entities verifying them (Warburg 2016)
(Zwitter & Boisse-Despiaux, 2018).
BTs are also a method to contain opportunistic behavior by removing the need for trust by
leveraging crypto-enforced execution of contracts through transparency and consensus. This
means, at least theoretically, that there is no room for opportunism within the DAOs; meaning that
these schemes will work more as markets rather than organizations. Thus, if the model of firms
and markets proves to be right, and effective cooperation and investments are hindered by the
threat of opportunistic behavior, the BTs will be indeed disruptive. However, if governance exists
for reasons beyond the prevention of opportunistic behavior, then BTs are less relevant at the firm-
market view (Davidson, De Filippi, & Potts, 2016).
Considering the previous contentions, this work argues that the Blockchain Technologies have the
potential to drastically reduce the challenges that have hampered the positive effect of the
Microfinance Movement. Also, it can prevent the appearance of rent-seeking behavior and abuses
from ill-intended MFIs’ managers by providing the proper tools for regulation and proper contract

50
enforcement. Moreover, it can pave the way to the appearance of new players in the Microfinance
industry and a new kind of MFIs, which could extend the level of outreach and provide better loan
conditions for the poorest of the poor.
Transparency to Reduce the Information Asymmetry
Decentralized Ledgers improves the transparency of information exchanges, rendering trust
obligations easier to discard between transacting parties. The service of funds transfer is usually
supplied by financial intermediaries. Blockchain and DLTs redistribute the responsibilities of
transfer management to algorithms and computer code. Due to the P2P configuration of BTs, the
Blockchain represents a disruptive innovation that can drastically reduce the information
asymmetry in all sort of transactions (Kewell, Adams, & Parry, 2017).
Multiple institutional and economic elements establish whether regulation, information
distribution, and contracting hinder information asymmetry, or leave substantial asymmetries.
Amongst these elements there is the capacity to write, track, and enforce optimal contracts, and
the costs of disclosing information for all the stakeholders (Healy & Palepu, 2002).
As Healy & Palepu (2002) state, there are some prescribed solutions for the information
asymmetries. First, optimal contracts that contain clauses enforcing full transparency between the
parties can tackle adverse selection. Second, strong regulation could demand more disclosure in
the governing bodies to avoid the moral hazard (Healy & Palepu, 2002). In theory, the BTs could
power smart-contracts in which the terms and conditions of credits could be fully transparent for
all the stakeholders. Likewise, a public record of transactions available on a Blockchain will help
to create the credit profiles for borrowers, translating in less over-indebtedness and proper interest
rates for the poor. Moreover, this full disclosure will facilitate the reporting and the control by
regulators, which promise to improve the practices of the entire sector.
Self-regulation to prevent Moral Hazard.
In a way, BT are directed to build social and economic institutions. BTs are aimed to create and
execute the kind of rule-systems (such as Smart-Contracts, and DAOs) that facilitate custom socio-
economic coordination (Davidson, De Filippi, & Potts, 2016).

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Albeit parties might be in a dispute within a contract, there is still a common benefit in maintaining
the integrity of a Blockchain, or their reputational capital within it, because of the value that
reputation has in open decentralized systems. Signaling or screening mechanisms are expected to
become more sophisticated and efficient within the Blockchain context (Davidson, De Filippi, &
Potts, 2016).
In general, regulations in MFIs are linked with operation costs such as security systems, IT
investments, and the slowing down of MFI innovations. Therefore, in some cases the benefits of
the regulation are diluted by these costs (Mersland, 2009). While the design and implementation
of the regulations are the main determinant of such benefits, technologies that enable transparent
and cheap self-regulation pave the way to enforce schemes that prevent abuses from MFIs’
managers or employees.
Reduction of Transaction Costs.
In an economic perspective, decentralized ledgers are likely to be more cost-efficient compared to
the current centralized systems as Blockchain goes through three exponential cost curves: Moore’s
law (cost of processing digital information decreases exponentially), Kryder’s Law (cost of storing
digital information decreases exponentially), and Nielsen’s Law (the cost of transferring digital
information decreases exponentially) (Wiles 2015). (Davidson, De Filippi, & Potts, 2016).
Contrary to the current ledgers intermediaries, the Blockchain is “distributed, public, transparent,
encrypted and immutable” (Hernandez, 2017).
Garmaise & Natividad (2010) reveal that credit evaluations have a strong positive effect in
reducing the costs of finance for MFIs. In their study, they find that the interest rate charged to the
MFIs by institutional lenders decreases by 550 basis points after an evaluation. Again, the
reduction of information asymmetries has a positive impact in costs reduction (Garmaise &
Natividad, 2010). The BTs could facilitate the collection of information and even have the
potential to completely transform the way evaluations are performed using Smart-Contracts.
In the same work, Garmaise & Natividad (2010) also discover that reducing asymmetries can
considerably improve how MFIs operate. Credit evaluations act as a balancing force for MFIs
since both financial and social objectives are under scrutiny in these practices. Additionally, the
presence of rankings and indexes help to spur the competition in the industry. Therefore, the

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evaluations not only help to access cheaper funds, but also they provide incentives to improve
performance (Garmaise & Natividad, 2010). Additionally, the fact that the BTs are purely digital
and autonomous opens a wide range of costs that can be minimized throughout the entire value
chain, this results in efficiency gains in risk management, insurance services, and international
payments (Zwitter & Boisse-Despiaux, 2018).
Lastly, transactions executed with smart-contracts should face less loss of efficiency due to
information asymmetries (both adverse selection and moral hazard). Therefore, it could be
expected to see less counter mechanisms such as signaling and screening. Also, Smart Contracts
could be an effective mean to set a considerable number of low probability state-contingencies
into contracts, which ultimately mean a reduction in transaction costs related to writing contracts.
Nevertheless, bargaining costs, both ex-ante discovery and ex-post renegotiation, are difficult to
be affected by the adoption of BTs. Thus, the effects on enforcement costs will depend on the
extent in which human discerning remains relevant in the transactions (Davidson, De Filippi, &
Potts, 2016).
Challenges for Blockchain Solutions
Internet Bandwidth Requirements
When it comes to evaluate the feasibility of new technologies, the key question revolves around
the point of critical mass; per a technology to thrive, technical superiority versus substitutes is not
enough. The proper presence of three elements is needed for Blockchain to succeed and go
mainstream: demand, competition, and know-how (Mattila, 2016).
Amongst the possible negative externalities that might stem from BTs, the additional bandwidth
required to deliver transactions across the network is a rising concern. When it comes to developing
countries, the expected effects may be more severe since network congestion is a common issue
in such nations (Kshetri, 2017). Although BT could have an unprecedented impact in land registry
and citizen identification, skeptics argue that Blockchain might not provide the intended solutions
due to its complexity and its energy and bandwidth requirements; elements that could be missing
during many humanitarian crisis (Zwitter & Boisse-Despiaux, 2018).

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The Front-end as a Central Bottleneck
The biggest barriers for Blockchain adaptation also include the absence of education, information,
and user-friendly interfaces. Unfortunately, there has been little awareness of Blockchain
advantages amongst the key stakeholders in the Microfinance sector. For example, Saldo – a
Mexican MFI focused in financial literacy- found that it is very complex to talk about Blockchain
with both funders and beneficiaries. The key is to start first with the MFIs, which are more likely
to be familiar with BTs, to downstream and motivate the construction of knowledge (Kshetri,
2017).
Even when digital or e-banking has been steadily rising over the last decade, and more and more
Fintech initiatives have appeared threatening to take the place of the conventional banks, there is
little evidence of this happening. With such trend not moving forward, it is natural to wonder
whether this behavior will be replicated by the beneficiaries of MFI if Blockchain technologies are
adopted, therefore hindering the full potential that decentralized ledgers pose for the micro-loans.
Sriram (2015) first notes that, in traditional commercial banking, the smaller borrowers and lenders
will still need banks to carry out financial intermediation as their transaction sizes might not justify
direct contact or transaction with the capital owners. Also, Sriram mentions that risk-averse
individuals would continue to use traditional Financial Institutions because their trust is reposed
in the name of a “bank”. This trust has been long nurtured by national governments taking the role
of protectors of the depositors by regulating banks through licensing, standardized reporting,
monitoring through regular inspections, and insurance requirements to cover for all or part of the
savers’ deposits.
Solutions powered by DLTs need to be designed with an ethical and moral base, by taking in
consideration the digital divides and inequalities that can arise in the real world. Empirical
evidence shows that the groups in the higher strata tend to adapt and benefit from new technologies
first. People in developing countries, rural communities, or marginalized are less likely to have the
digital literacy to properly interact with BTs, which ultimately can evaporate the potential for good
within the DLTs (Hernandez, 2017).

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Volume of Transactions and Cost-Efficiency
Unfortunately, Blockchain is an energy-intensive technology. Even when solutions to reduce the
energy needs and costs have been implemented, BTs will always require server capacity and
computational power to process the transactions. Hence, in countries in where energy
infrastructure and internet access are insufficient, BTs quickly reach their limit in terms of
scalability. Moreover, internet accessibility and energy security are especially troublesome in areas
in which the poorest of the poor reside (Zwitter & Boisse-Despiaux, 2018).
The Proof-of-Work method that validates every transaction is computationally intensive and is
considered as costly and wasteful. As miners competitively commit resources to verify
transactions, Aste (2016) assess that around one billion Watts of electricity are used every second
to make a valid PoW for BTC. Considering this, alternative validation methods are being
developed, some of which might impact some MDGs but also ease some of the communitarian
properties of the PoW method (Davidson, De Filippi, & Potts, 2016).
Energy consumption also depends on the hardware used for operation of the network. Miners keep
the specifics of their hardware secret. Therefore, it is complicated to calculate the power needs and
usage of a network. An estimate proposes that even when bitcoin miners use the most efficient
hardware available, the annual electricity consumption could reach the two Terawatt-Hours mark
(above the consumption of 150 thousand people in the US). In a pessimistic scenario, the amount
of electricity used could go up to 40 Terawatt-hours (Kshetri, 2017).
Nowadays Blockchain dull when compared to the established transaction and ledger technologies.
Bitcoin, which was created to replace regular fiat currencies, can only perform 7 transactions per
second (tps). Ethereum, which was designed to tackle this limitation, is limited to less than 50 tps.
Therefore, there is still a big gap when compared to PayPayl’s 450 tps Visa’s 24,000 tps (Koticha,
2018).
These figures open doubts on how better BTs can become in terms of computational capacity and
energy efficiency. While curves such as the Moore’s law leaves hope for Blockchain to achieve
scalability, the speed in which the technology evolves is crucial to meet the expectations that have
been raised over the last couple of years.

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Regulation and Validation
As already mentioned, an economic order founded on the Blockchain can fully automate and
implement Smart-Contracts through DAOs. Nevertheless, the contractual enforcement remains an
issue when the sanction of a violation cannot be guaranteed by any authority or government.
Therefore, the question of whether the SCs operate at the coast of the Law raises (Davidson, De
Filippi, & Potts, 2016).
Technological solutions that tackle social problems do not operate in isolation. The potential that
any of these solutions has highly depends on the organizational and strategic levers of such
innovations. If the institutional context generally determines whether a social intervention will
succeed or not, it is only natural that the same will apply for the ones based on technological
innovations (IDF, 2017).
The risk of not adapting the Blockchain as a solution is not only limited to the lack of digital
literacy or the wrong implementation of the front-end. Projects using technological innovations to
tackle social problems regularly “find that getting buy-in is the toughest part of delivering an
effective solution, not the technology” (IDF, 2017). The buy-in not only has to come from those
using the technology but to all the stakeholders involved in the social initiative.
It is expected that Governments that have a history of commitment with transparency are more
likely to welcome Blockchain-based solutions. On the other hand, those that look for opaque
environments will likely hinder these efforts. The vested interest of some groups in power could
be the major obstacle to for the implementation of DLTs in the search of better transparency. The
deep understanding of the economic, social, and political context is key for the success of
Blockchain-based interventions (Hernandez, 2017).
The efforts to regulate the Blockchain have raised attention. The role of governments and
regulators are still not clear. Also, there is no clarity in the ways to set priorities and allocate
resources to different economic and social segments. The implementation of BTs may also conflict
with regulations and international laws. For example, the information stored in a decentralized
ledger is immutable and open to all public, which can go against the right to be forgotten and
privacy rights (Kshetri, 2017).

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Ultimately, a legal framework seems to be vital for Blockchain to reach its full potential, regardless
of the field the technology is applied to. Zwitter & Boisse-Despiaux (2018) state that, at least for
the humanitarian sector, BTs will need to comply with international legal frameworks such as the
Human Rights Law or the International Humanitarian law. For the Microfinance sphere this might
prove to be more challenging since both humanitarian and financial should be integrated in the
design of a solution. Exporting successful solutions might prove infeasible when national financial
regulations do not match the elements of successful implementations.
Rigidity and Privacy Issues
While the immutability of the information in a Blockchain and the automated nature of the Smart-
Contracts are arguably the most appealing features for MFIs, certain concerns raise regarding the
rigidity of the technology and the violation of privacy rights.
The potential of creating immutable ID records and automatically execute contracts, while
promising, will probably bring rigidity to the processes by taking the human margin of appreciation
out of the equation (Zwitter & Boisse-Despiaux, 2018). When considering the extreme
circumstances the poor face in their lives, full rigidity might not be as desirable for the
Microfinance and Financial Inclusion movements.
Also, there is no clarity in how to prevent the misuse of data, or enforce the right to be forgotten,
when Blockchains provide immutable and decentralized transaction information. Therefore,
privacy and data protection poses a considerable obstacle for the implementation of DLTs, notably
when identity registries and other databases contain personally identifiable information (Zwitter
& Boisse-Despiaux, 2018). Therefore, the full substitution of the human appreciation in the
Microfinance industry is unlikely to happen. The stakeholders should be careful in how Blockchain
is deployed in providing solutions, otherwise the efforts can be diluted by legal battles and
reputation loss.

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Empirical case: Everex
History and Objectives
Everex is a Fintech startup that offers Blockchain-powered solutions for Financial Institutions and
their customers. Everex’s technology allows the transfer of remittances, direct payments, exchange
of crypto and fiat currencies, and the provision of micro-loans via Blockchain (Lane, 2018).
Everex vision is to facilitate different mobile wallets to provider multi-currency and P2P
transactions that cover both fiat and crypto currencies on BT. Everex’s objective is to foster a
financial ecosystem in which most the digital wallets are supported by Everex technology, catering
Blockchain-powered interoperability amongst thousands of global digital wallets that are not
currently linked. With this, Everex will empower domestic and international remittances and
payments for individuals and SMEs, promoting economic development to those regions outside
the FFS (Lane, 2018).
Everex aims to providing financial services to over two billion people excluded to the FFS. It
offers access to an Everex based mobile wallet that acts as a regular Bank account with the
traditional banking services but with no fees for moving money around. With this wallet,
customers can get micro-credits and micro-financing at rates below the industry’s average and
with cryptocurrency backing (Evans, 2017).
Blockchain Implementation Thesis
Everex plans to achieve its goal by implementing a technology known as “cryptocash”, which
attaches a token value to a determined fiat currency. At the same time, Everex users will be able
to convert their own currency into “cryptocash” through this platform, enabling access to a
worldwide network of services (Investopedia, 2018).
The cryptocash is 100% backed by Ethereum, which not only works as a cryptocurrency but allows
the execution of Smart Contracts on top of it. This enables secure lending backed up by
cryptocurrencies (Evans, 2017).
The Everex’s founders claim that their technology benefits users by:

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1. Optimization of payments for individuals and institutions via BT for remittances and payments
across countries and currencies.
2. New business opportunities, such as remittances services, fiat/crypto currency exchange, and
cross-border micro-lending for individuals, NBFIs and Banks without using legacy payment
systems.
3. Major transaction costs reduction by bringing down the number of intermediaries in the cross-
border transactions.
4. Achieving settlement times of less than a minute. Therefore, resulting in faster turnover of the
capital for SMEs and an improvement of economic growth (Lane, 2018).
Results and Challenges
Everex successfully launched its first cross-border remittance pilot in 2016 and the e-wallet is set
for a second phase of commercial try outs. Also, the fintech has just closed an exclusive agreement
with Shwe Bank (SBM) in Myanmar. SBM is diversifying its business and will begin offering the
remittance service (Lane, 2018). Everex launched its Initial Coin Offering (ICO) on 2007 raising
over 6 million USD (Kuznetsov, 2017).
The volatility that the cryptocurrency has experienced pose a risk since the value of the loans or
remittances can vary drastically, measures to offset this variability can push the costs of transaction
up or can hurt the value of the remittances sent, causing a negative effect. Moreover, the gap in
digital literacy can affect the adoption of Everex technology by beneficiaries. Measures to facilitate
the use of the service and to create trust amongst users is key for Everex success in the future. By
just labeling the company as a Blockchain solution can hinder its credibility. Therefore, Everex
must show that it is a better solution than incumbent remittances and Microfinance services by the
way it is implemented and tangible benefits.
The Future of Blockchain in Microfinance
Sriram (2015) states that in a mature model where technology enables storage and retrieval of large
data, the function of intermediation could be as represented as following:

59
Source: Sriram, M. S. (2005). Information asymmetry and trust: a framework for studying microfinance in
India. Vikalpa, 30(4), 77-86.
Considering that the main role of Financial Institutions is the one of intermediation between those
who hold capital surpluses and those with short-term capital needs, the implementation of DLTs
could reshape the entire Microfinance landscape. Moreover, if the full potential of BTs is unfolded,
individual savers could be connected directly to those with capital needs, including the poorest of
the poor. This sort of outcome would arguably disrupt the entire composition and role of MFI as
they are known.
For Entrepreneurs and Non-Financial Institutions
Since Blockchain can change the landscape of the Microfinance sector, there is space for new
players to enter at different stages of the value chain. For example, by understanding that the digital
literacy and a user-friendly interphase are vital for the adoption of Blockchain, Startups could

60
focus in creating digital tools for financial education and in providing software developing for
MFIs Blockchain interphases.
Also, there are examples of large manufacturers, retailers and wholesalers that are playing an
incremental and complementary role in providing specialized financial services. For example, in
Mexico, consumer credit from Banco Wal-Mart and micro-supplier credits from Cementos
Mexicanos (Cemex) are addressing the needs of the poor. Another financial services are offered
by non-financial firms that are acting as local agents for banks in remote areas, or in areas where
there are no bank branches, to better serve the poor and the unbanked (Chibba, 2008). BTs foster
the provision of such services by leveraging the benefits of Smart-Contracts and the efficient
formation of credit records that Blockchain enables.
Moreover, in a new financial environment powered by the Decentralized Ledger Technologies,
native players of such technologies can slowly displace the incumbent MFIs from the leadership
of the sector. Efficient Blockchains that can hold transactions per second at similar rates as PayPal
or other digital payment platforms, with robust Smart-Contracts designed to service the poor, and
the proper outreach channels to provide digital and financial literacy, could create a new type of
MFIs that only would be connecting savers directly with borrowers at a relatively small fee per
transaction. This sort of schemes would resemble a marketplace in which the fund allocations
would be more efficient and interest rates could be drastically reduced, increasing the outreach of
the entire Microfinance Movement. Solutions of these kind have been already tested across
different geographies, ranging from Africa to Myanmar, with promising results. Still, the greatest
challenges to face are the regulations and the creation of trust in BTs.
For Incumbent MFIs
As argued in this work, BTs have the potential to reduce the effects of the structural flaws in the
Microfinance industry. MFIs could leverage the openness and immutability of the Blockchain to
create credit records that make risk assessment and management more efficient. The employment
of SCs could make the collection process more efficient and could help to diminish the need of
risky collaterals. Moreover, the near-time component in the recording of transactions would make
the reporting process more efficient and transparent, incentivizing the improvements in
performance and diminishing the appearance of rent-seeking behavior.

61
Additionally, DLTs could help in the provision of ancillary and complex services to the poor, like
insurances, remittances, and saving schemes. Using customized Smart-Contracts MFIs could
expand the coverage of their insurances without incurring further risks. The cost to set up the
proper infrastructure to offer remittances services could drastically diminish once the Blockchain
reaches certain maturation, integrating this service with the provision of micro-finance and saving
vehicles. Lastly, the same SCs’ logic could be used to assure that the beneficiaries of MFIs save
certain amount of their additional incomes and that those savings could generate certain degree of
returns without leaving the beneficiaries exposed to abuses.
Considering all the previous contentions, it is safe to claim that embarking into BTs is a wise
decision for the MFIs. Even more, doing it on an early stage could help to prevent the displacement
by Fintechs or commercial banks, which hold a greater expertise in digital solutions. By leveraging
their current field expertise and knowledge of the beneficiaries, MFIs could guide the creation of
Blockchain-based solutions that are properly catered for the poorest of the poor.
For Governments and Regulators
Many configurations of the Blockchain might be used to foster FI using Microfinance as a vehicle.
For this matter, the Microfinance sector could potentially benefit from numerous application
including public, private, federated or consortium Blockchain. Looking at the current scenario and
at the numerous players involved in the microfinance sectors, BTs could be implemented at various
levels and with very different objectives.
As previously mentioned, what has been observed across several MFIs and nations is that the entire
lending process could sometimes become a pervasive mechanism for mere profit generation, in
which the community and the poor end up, at best, not being benefited at all. One of the main
reasons behind these incidents has been is the lack of transparency in the various step of the
process, with difficult traceability of the amount of money borrowed, rates, cash outs, etc. For
those reasons the type of Blockchain that probably better fits the scope and objective of
Microfinance, besides being implementable without the need of a specific party that must be
constantly and professionally involved, is the public one.
Public Blockchains would guarantee perfect traceability of every action executed by all the parties
involved in a microfinance transaction, guaranteeing the public access to all the information

62
generated and stored. At the end, the beneficiaries of microfinance will be both “protected” and
benefited, since everything will be traced and will not need to rely on the trust on the quality of
the reporting by MFIs and their managers. On the other side, regulators and lending parties will
have just the same access to the information required, besides being able to fully monitor the
performance of MFIs throughout all the steps. At the end, regulators could be more efficient in
surveilling the actions of MFIs and could increase their response time in case of any anomaly rises.
Nevertheless, the greatest challenge for the regulators would be finding ways to achieve these
levels of transparency without violating privacy rights and guaranteeing the right to be forgotten.
The figure of consortium Blockchain or hybrid public/private schemes could be the key to get the
best of both worlds.
Conclusion
The Microfinance Movement has been an emblem of the development economics sector over the
last 3 decades. While there is still controversy regarding the depth of impact that Microfinance in
rising people out of poverty, empirical and theoretical research shows that it is important tool for
achieving Financial Inclusion and Economic Growth in poor households.
Regardless of the constant evolution and sophistication of the Microfinance industry, structural
challenges still hinder the full potential of the MFM. Especially, the persistent presence of
Information Asymmetries in the Microfinance sector frustrates the efforts to reduce operation and
funding costs, achieve financial sustainability and scalability, and implement proper reporting
schemes. Arguably, the reduction of such asymmetries could drastically increment the outreach
and coverage goals of the sector.
Amongst all the technology innovations that could revolutionize the financial sector, this work
argues that Blockchain has the potential to disrupt the entire sector. The immutability,
transparency, openness, and security of the technology makes it the perfect candidate to protect
the poor from abuses from ill-intended players. Nevertheless, BTs developers should keep in mind
the lack of digital literacy in the poor, the transactions that BTs can hold, and the possible attempts
against privacy rights. Whether BTs could disrupt Microfinance will depend in how fast the
technology matures and how much trust this system can create on lenders, borrowers, and
regulators.

63
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Appendix
Appendix 1. Merkle Tree Functioning
Source: Mitra, A. (2017). What is a Merkle Tree?. URL: https://www.thesecuritybuddy.com/encryption/what-is-a-
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Appendix 2. How Blockchain Works?
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Times, 1, 2015.

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Appendix 3. Specifics of Hashing
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Appendix 4. Symmetric Encryption
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introduction-to-encryption-9afd17f5da6d (visited on 16th December 2018).

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Appendix 5. Asymmetric Encryption
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