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Banks and Information Technology: Complexity, Flexibility, and Interconnectedness



This paper analyzes whether banks are special in comparison to other firms in the use of information technology (IT). IT spurs communication, digitization of business processes and establishment of internet and mobile customer access channels. IT modifies core banking technologies and facilitates automatic loan processing, electronic payments, and clearing and settlement transactions. Similar to the situation in other industries, IT increases complexity in banking by increasing product variety and conglomeration. However, pronounced asset-substitution problems may cause banks to become excessively complex in order to disguise risk-taking. Banks may abuse the additional flexibility that IT facilitates to shift risks at short notice or even become too big to fail. Finally, developments in IT may lead to increased interconnectedness in banking with potentially adverse effects on systemic risk. Several examples from the 2007–2009 financial crisis are given.
Electronic copy available at:
10 December 2010
Banks and Information Technology: Complexity, Flexibility, and
Matej Marinč*
University of Ljubljana and ACLE
This paper analyzes whether banks are special in comparison to other firms in the use of
information technology (IT). IT spurs communication, digitization of business processes and
establishment of internet and mobile customer access channels. IT modifies core banking
technologies and facilitates automatic loan processing, electronic payments, and clearing and
settlement transactions. Similar to the situation in other industries, IT increases complexity in
banking by increasing product variety and conglomeration. However, pronounced asset-
substitution problems may cause banks to become excessively complex in order to disguise risk-
taking. Banks may abuse the additional flexibility that IT facilitates to shift risks at short notice
or even become too big to fail. Finally, developments in IT may lead to increased
interconnectedness in banking with potentially adverse effects on systemic risk. Several
examples from the 20072009 financial crisis are given.
* Faculty of Economics, University of Ljubljana, Kardeljeva ploščad 17, 1000 Ljubljana, Slovenia, e-mail:, and Amsterdam Center for Law & Economics (ACLE), Faculty of Economics and
Business, University of Amsterdam, Roetersstraat 11, 1018WB Amsterdam, The Netherlands, e-mail:
Special thanks to Arnoud Boot, Igor Lončarski, Barbara Mörec, Peter Trkman and Razvan Vlahu for their
Electronic copy available at:
2. 1
1. Introduction
Not many things have reshaped the banking industry as much as information technology (IT) in the
last few decades and the 2007-2009 financial crisis in the last few years. IT spurs communication
within and across banks, allows for fast business process redesign and facilitates access to bank
customers through internet and mobile access channels.2 Banks are also increasingly using IT in their
core technologies, including automatic loan processing,3 electronic payments,4 and clearing and
settlement transactions.
This review seeks to determine what changes IT development may bring for banks. The banking
industry is undergoing a major transition from a predictable and rigid industry into a complex, quickly
evolving, and increasingly interconnected one. Are banks going too far in this transition and can IT
developments be (partially) blamed for this? More specifically, does IT development in banking go
hand in hand with increased instability? The importance of these issues is unquestionable and further
highlighted by the 2007-2009 financial turmoil.5
Banks may become excessively complex due to IT development. Similar to the situation in other firms,
IT development pressures banks to offer a variety of customized products and services, and to demand
workers with advanced quantitative skills. However, the existence of explicit and implicit guarantees
(e.g., deposit insurance, anticipation of bailout) may drive banks to take excessive risks. Banks may
use IT developments to mask risk-taking through increased complexity. Banks may design complex
products or transform themselves into highly opaque financial conglomerates that are too-complex-to-
regulate and/or too-complex-to-fail.
IT also increases the speed of change in firms and even more so in banks. What makes banks different
in this respect is their more pronounced risk-shifting incentives and the asset-substitution problem.
Fast growth, facilitated by IT, may not only be a result of efficient operations but also of pronounced
risk-taking, as the examples of Northern Rock and Icesave show. In addition, IT facilitates decision-
making based on hard information. Although this yields additional flexibility, it also makes banks
2 In a 2010 worldwide survey, KPMG (2010) found that 46% of respondents claimed that they had used mobile
banking, compared to only 19% in 2008. In the U.S., 58% of respondents claimed that they used online banking
in 2010 compared with 44% in 2004 (Pew Internet & American Life Project, 2010, 2004).
3 In 1998, only 62% of large U.S. banks (that responded to the survey) employed small business credit scoring
techniques when lending to small businesses (Frame, Srinivasan, and Woosley, 2001). Today, the majority of
large banks and an increasing proportion of small banks do this (Berger, Cowan, and Frame, 2009).
4 In the U.S., checks accounted for 46.4% of the total number of transactions in 2003, but only for 28.6% in
2007, whereas the use of debit cards increased from 20.2% to 30.6% (BIS, 2009, pp. 241242).
5 Total bank writedowns between 2007 and 2010 are expected to reach $2.2 trillion (IMF, 2010a). In the period
from January 2008 to October 2010, 275 banks failed only in the U.S. (FDIC, 2010). The real economies of the
G7 countries shrank by 3.5% in real terms in 2009 (IMF, 2010b).
2. 2
more footloose. Banks that excessively rely on hard information may weaken their relationships with
depositors and borrowers. This may decrease stability. Another consequence of high flexibility is that
banks imitate each other by following hypes and fads, which makes them even more interlinked. For
example, banks and credit-rating agencies have employed quantitative default models based on large
sets of historical data to predict the default probabilities of complex securities. The 20072009
financial crisis showed that these models systematically underestimated the probability of default,
thereby creating large systemic exposure of the banking industry.
Interconnectedness deserves special attention in banking due to the systemic risk that it creates. A
failure of one bank may then trigger contagion by the entire banking system with adverse spillover
effects for the entire economy. Banks seeking to maximize their own profits may disregard negative
externalities of their failure. In this negative view, banks would use some IT solutions even though this
may lead to excessive interconnectedness. Even more, banks may become too interconnected to fail,
knowing that the regulator or government needs to bail them out to prevent a systemic crisis.
This review seeks to merge three slightly separate strands of literature. First, it reviews the main
characteristics of IT use from information systems literature (e.g., Melville, Kraemer, and Gurbaxani,
2004; Chiasson and Davidson, 2005). Second, it uses management and economics literature that
discusses the impact of IT on changes in firm organization and structure (for a review, see
Brynjolfsson and Saunders, 2010). Finally, it uses banking literature (e.g., Berger, 2003; Boot and
Marinč, 2008) to discuss the special features of banks and their IT use and to give policy implications.
This paper is organized as follows. Section 2 discusses the use of IT by banks. Section 3 analyzes the
impact of IT on firm and bank complexity. Section 4 focuses on IT-induced flexibility. It is argued
that IT developments have made banks more interlinked and the consequences for systemic risk are
assessed. Section 5 concludes the paper with brief policy implications.
2. The use of IT
IT has been widely adapted across business sectors and a range of uses. IT has surpassed the narrow
definition in which: ―IT refers to the technological side of an information system. It includes the
hardware, databases, software, networks and other devices (Turban, McLean, and Wetherbe, 2002).
In a broader concept IT can be defined as ―computers as well as related digital communication
technology …‖ with powers to ―… reduce the costs of coordination, communications, and information
2. 3
processing‖ (Brynjolfsson and Hitt, 2000).6 Empirical evidence confirms (although not unanimously)
that IT improves productivity.7 In banking, IT applications have vastly improved industry core
technologies. In addition, general IT applications have facilitated communication, digitization of
business processes, new customer channels of access, and information sharing.
2.1. Use of general IT applications in banking
Communication, coordination, collaboration, and information availability: IT facilitates better
communication within and across corporate borders. Interaction between employees and customers
can flow directly through e-mails or indirectly through blogs and customer opinions (McAfee, 2006).
Communication can be structured through constantly evolving corporate intranets, extranets, text
messaging, corporate web sites, and information portals (Davenport, 2005).
Within the bank, virtual teams surpass geographical distances (although time zones and cultural
differences still affect communication; Lee-Kelley and Sankey, 2008). Communication across
corporate borders is strong in banking. Banks have established highly secure communication standards
such as SWIFTNet and EBICS to exchange a variety of information (e.g., account statements,
securities holdings, and debit and credit payment orders) between themselves and other financial
institutions. Automatic messaging systems (e.g., Loan/SERV) are becoming a standard in a syndicated
loan market and facilitate communication between several banks when lending to a single large
borrower. Banks increasingly exchange information about their retail and corporate borrowers through
public credit registers and private information exchanges. IT developments such as the internet and IT
tools (such as web browsers, aggregators, customer opinions, web wrappers programs that extract
machine-readable data from the Web) and IT architectures for information sharing have augmented the
quantity of information that banks possess (Pan and Viña, 2004).
Increased communication and greater information availability have improved the quality of bank
operations. For example, the evidence shows that the existence of information exchanges (e.g., credit
bureaus such as Dun & Bradstreet and Experian) improves the lending decisions of banks, reduces
loan interest rates, and decreases loan defaults (Pagano and Japelli, 1993; Kallberg and Udell, 2003).
Banks often compete fiercely in one market segment and cooperate closely in another. For example,
banks may cooperate in a lending syndicate and voluntarily share information through credit registers,
and at the same time compete fiercely for depositors. In addition, banks possess much valuable
6 IT has been applied to wide range of business processes and products, has spurred innovations in other
technologies, and has demonstrated great potential for constant improvement. All of these characteristics make it
a general-purpose technology (Bresnahan and Trajtenberg, 1996; Jovanovic and Rousseau, 2005).
7 See Brynjolfsson and Saunders (2010) for a discussion.
2. 4
proprietary information that may create substantial damage when leaked. Consequently, carefully
designed IT architecture for communication between banks and within banks is a must.
Business processes: IT has provided support for coordinating and automating business and
management processes within a bank and provided access to integrated data across the entire bank. IT
software and infrastructure are combined to link bank products and services to customers, back office
functions, and business units. In banking, special attention is given to risk management. Banks need to
build internal processes that identify, measure, and mitigate risk to comply with regulatory standards.
Risk-management systems need to provide automatic registration of risky events, allow for centralized
risk oversight over the whole bank, provide decision support for risk mitigation, and have a framework
for automatic reporting to regulators (Bamberger, 2010). Models for risk measurement and
management have become increasingly complex due to developments in information technology and
advances in quantitative finance (e.g., exponential growth in computation power and the Black-
Scholes model for option pricing). Value-at-risk and stress-testing are two the most commonly used
models that require substantial IT support (Fender and Gibson, 2001; Jorion, 2006, p. 431).
Online and mobile banking access channels: Banks are increasingly reaching their customers through
online and mobile banking channels.8 The introduction of internet banking generally increases bank
profitability.9 Internet banking also modifies the importance of other access channels. It acts as a
complement to a branch network (DeYoung, Lang, and Nolle, 2007; Hernando and Nieto, 2007).
Campbell and Frei (2010) showed that online banking induces replacement of marginally more costly
self-service delivery channels (such as ATMs), augmentation of costly service delivery channels
(branches and call centers), and an increase in transaction volume. The cost of services, customer
retention, and market share increase due to the introduction of online banking.
2.2. Use of IT in core banking technologies
As is shown next, IT has also substantially modified core banking technologies in both the back office
and front office. As a result, the quality and variety of banking products and services has improved
(Berger, 2003; Casolaro and Gobbi, 2007).
Automatic loan processing and transaction lending techniques: IT spurred automatic loan processing
based on hard quantifiable information about bank clients. Banks are increasingly using credit bureaus
8 For a review of internet banking, see VanHoose (2009) and Frame and White (2009); for a review of mobile
banking and mobile payments, see Mallat, Rossi, and Tuunainen (2004) and Dahlberg et al. (2008); for IT use in
micropayments, see Hinds (2004).
9 For the evidence from Spanish and Italian banking, see Hernando and Nieto (2007) and Ciciretti, Hasan, and
Zazzara (2009). DeYoung, Lang, and Nolle (2007) reported that U.S. community banks charged extra fees for
services related to deposit accounts upon introducing the internet channel. Greater revenues more than
compensated for the increase in wage expenses that these banks incurred.
2. 5
to gather information and using credit-scoring models to process it and approve the loan (Berger and
Udell, 2006). For example, banks use credit-scoring models when approving mortgages, credit cards,
and automobile credits to retail customers. Even lending to small and medium-sized enterprises
(SMEs) has become increasingly digitized. Transaction lending techniques, such as financial statement
lending, asset-based lending, fixed-asset lending, leasing, factoring, and small business credit scoring
(SBCS) use quantifiable information to automatically process loans. Transaction lending gives a
competitive edge to distant banks even though they may lack close personal contact with borrowers
(Berger and Udell, 2006).10
SBCS is particularly IT intensive because it gathers and processes data from multiple sources. SBCS
typically combines consumer data from the owner, small business data gathered by the financial
institution, and data obtained through consumer and commercial credit bureaus. The empirical
evidence shows that SBCS increases the availability of credit, the maturity and risk of credit, and the
distance between the bank and the borrower (Berger, Frame, and Miller, 2005; Berger et al., 2005;
Berger and Frame, 2007; Frame, Padhi, and Woosley, 2004; DeYoung, Glennon, and Nigro, 2008).
Electronic payments & clearing and settlement transactions: The most evident and empirically
quantifiable are the real effects of IT developments in payment systems and clearing and settlements.
IT lowers transaction costs and spurs the development of new payment products.11 Paper payments
such as cash and checks are increasingly being replaced by electronic payments such as debit and
credit cards or by mobile payments. Humphrey et al. (2006) found that replacing the costly paper-
based payment method with an electronic-based payment system and replacing branch offices with
ATMs resulted in cost savings of 0.38% of the twelve EU nations’ GDP.
IT and investment banking: IT is also important for banks when interacting with financial markets.
Large investment banks in particular offer services such as custody of securities, clearing, securities
lending, cash management, and reporting, which require substantial IT support (Channon, 1998;
Schmiedel, Malkamäki, and Tarkka, 2006; see also Duffie, 2010 for further description of the business
operations of large banks). Risk management that makes extensive use of IT is crucial in underwriting,
over-the-counter derivatives, and off-balance sheet financing. Investment banks also engage in
proprietary trading in primary and secondary markets and act as market makers. For trading activities,
banks increasingly use algorithmic trading. That is, they trade automatically based on complex and
often opaque algorithms through high-speed/frequency software engines.12
10 Although SBCS was initially adopted by large banks, it has also recently been used by small community banks
and in developing countries (Berger, Cowan, and Frame, 2009; de la Torre et al., 2010).
11 Banks are increasingly cooperating or even competing with telecommunications companies, payment
processors and IT vendors for the electronic payment market.
12 See Hendershott, Jones, and Menkveld, 2010 for more on algorithmic trading.
2. 6
The following pages examine how IT changes complexity, flexibility, and interconnectedness.
3. IT and complexity
IT has an impact on firm complexity in several dimensions.13 IT and its applications modify firm
product variety, the complexity of job tasks, and firm conglomeration. It is argued that banks are no
different in this respect; however, banks may become overly complex to mask their excessive risk
3.1. Product variety, workers’ skills and diversification benefits
Internet access channels and IT-induced information availability spur demand for product variety and
customization. For example, aggregation of customers slashes storage costs. Information availability
through browsers and customer opinions may boost demand for niche products (Anderson, 2006).14 IT
affects the entire firm and its strategy: firms are moving towards more customized products (Bartel,
Ichniowski, and Shaw, 2007). IT reduces the time of setting up a new production process, which
allows for customized production. Innovative, made-to-order production further increases
customization of products. Banks are no different. As mentioned in Section 2.2, banking has become a
broad business with a multitude of different products and services. Banks increasingly rely on hard
digitizable information. Leasing, factoring, asset-based lending, and fixed-asset lending have joined
relationship loans. Brokered deposits and money market deposits are now offered alongside bank core
deposits (Berger and Udell, 2006; DeYoung, Lang, and Nolle, 2007). Banks also cross-sell a wide
array of services and products including payments, savings, and advisory services (de la Torre et al.,
2010). Cost efficiencies due to IT have made possible microfinance loans and facilitated a variety of
micropayment products.15 Banks also tailor their products and services to their clients’ needs and
characteristics. An instructive example is complexity in mortgage lending. IT capabilities for data
collection and mining allow mortgage lenders to sell complex and customized financial products to
consumers and employ the information advantage with respect to the risk of consumers and the
products offered (Willis, 2006).
IT also increases the complexity of job tasks, together with the demand for workers with advanced
problem-solving skills (Bartel, Ichniowski, and Shaw, 2007). Computers replace jobs that rely on rule-
13 The structural complexity of a firm may be defined as the number of jobs or services performed, the number of
departments, or the variety of specialists that work in a firm (Damanpour, 1996).
14 Bils and Klenow (2001) showed that product variety in the U.S. increased 1% per year from 1959 to 1999 and
was accelerating in the last two decades.
15 For example, mobile banking can increase access to finance in developing countries for a previously
unbankable population (Kapoor, Ravi, and Morduch, 2007).
2. 7
based tasks but are complementary for nonprocedural cognitive tasks (Autor, Levy, and Murnane,
2003). IT spurs employee productivity through enhanced cooperation (e.g., through virtual teamwork;
Majchrzak et al., 2004), empowerment of employees and multitasking (Aral, Brynjolfsson, and
Alstyne, 2007).16 In investment banking, the technical skills of employees became increasingly
important along with the improvements in quantitative finance and IT developments. Because such
codified skills could be learned at universities, the importance of long-term mentoring of new
associates has declined (Morrison and Wilhelm, 2008). At the same time, the need for IT investments
has been huge. The need for IT investment and demand for quantitative workers’ skills has driven the
organizational change in investment banking. Before the 1980s, investment banks were organized in
partnerships. A flat wage, the threat of being fired, and promised long-term gain for success worked
together to retain capable new associates and nurture long-term mentoring (Morrison and Wilhelm,
2008). The decline in the need for mentoring and the need for investment forced investment banks to
grow substantially and become publicly traded.17
The complexity in firms increased also through greater diversification. Firms that more intensively
employ IT are slightly more diversified. In addition, diversified firms demand higher investment in IT
(Hitt, 1999). IT increases performance of firms that follow multi-focused business strategies more than
the ones that have a single focus (Tallon, 2007). Interestingly, the positive relation between IT and
diversification is strong only for diversification in related activities and for moderate geographic
diversification (Ravichandran et al., 2009). The rationale for the positive relation between
diversification and IT may be the following. The costs of communication and coordination among
business units are more pronounced for diversified firms than for specialized firms. Therefore the
benefits of IT in lowering communication costs are the highest for diversified firms and when firm
activities are related. In the unrelated activities, strategic controls (where the need for communication
and coordination is high) are replaced by financial controls and IT is needed less (Liu, Ravichandran,
Briefly, IT affects complexity. It increases product variety and customization. Workers need to
become proficient in advanced technical and problem-solving skills, with the ability to work in
16 Bresnahan, Brynjolfsson, and Hitt (2002) showed that IT is complementary to workplace reorganizations to
more decentralized organizations, human capital investment, and the introduction of new products and services.
Banks seem to be no different. IT investment related to consulting services, implementation services, training
and education, and support services improves bank performance, but not direct IT investment in hardware and
software (Beccalli, 2007).
17 The value of mentoring declines especially in trading departments in investment banks, where codified,
quantitative knowledge seems to be the most important. Soft knowledge and therefore mentoring, however, can
still be important in departments where relationship building with clients is still crucial, such as in wealth
management, M&A, and private equity.
18 Rather than performed in-house unrelated activities can be outsourced. IT reduces the cost of communication
with outside partners (Brews and Tucci, 2004). Firms can increase their focus and specialization, lower inter-
firm hierarchy, and increase external partnering.
2. 8
(virtual) teams and multitask. IT generally leads to greater benefits of diversification in related
3.2. IT and conglomeration in banking
The attractiveness of geographic diversification in banking increased due to IT developments. IT
driven scale economies are present in back office operations. Studies have identified substantial IT-
based cost reduction and economies of scale in processing electronic payments (Hancock, Humphrey,
and Wilcox, 1999; Beijnen and Bolt, 2008) and in clearing and settlement systems (Schmiedel,
Malkamäki, and Tarkka, 2006).19 Scale economies also derive from running a sizeable distribution
network. For example, internet banking allows banks to reach more distant customers at practically
zero marginal cost but at high initial investment. Big banks have both a greater capacity to make a
large investment in IT and a larger customer base.20
Big banks adopted IT technologies much sooner and to a greater extent than small banks. Big banks
gained an advantage in transaction lending technologies that rely on easily quantifiable, hard
information, whereas small banks more often employ relationship lending, which uses soft information
about local markets and soft person-to-person information about local borrowers.21 Big banks may rely
less on soft lending techniques than small banks because transmission of soft (i.e., unquantifiable)
information through hierarchical and geographical distances within a bank is difficult (Stein, 2002;
Liberti and Mian, 2009).
IT developments have lowered information problems, especially within large banks. Berger et al.
(2007) found that IT-induced technological progress increased the profitability of large, multimarket
banks more than small community banks.22 The effect occurred through both greater revenues and
lower costs, and it was especially pronounced for geographically dispersed large banks.
Lower communication costs facilitate the ability to control branch managers from the parent bank.
Through online banking, customers may be approached directly from the parent bank. In addition, IT-
enhanced methods for risk management and improvements in credit-scoring and data-mining
techniques may (partially) shift the decision-making from a branch manager to the parent bank. Berger
19 IT-induced economies of scale reach across national borders. In the future, technological improvements may
further reduce the burden of various technical requirements, fiscal rules, and legal frameworks, and consequently
decrease fragmentation in payment processing and the clearing and settlement industry.
20 DeYoung (2005) showed that internet-only banks, even though less profitable than brick-and-mortar banks,
were able to realize substantial economies of scale. IT development may increase the importance of global
branding (Wright, 2002) and trust (Brynjolfsson and Smith, 2000).
21 Big banks were also the first adopters of internet banking (Courchane, Nickerson, and Sullivan, 2002).
22 Large banks also gain a quality advantage over smaller competitors by having a denser branch network, by
engaging in more advertising, and by having more employees at the branch level (Dick, 2007). Felici and
Pagnini (2008) showed that IT allowed banks to easily open branches in more distant markets.
2. 9
and DeYoung (2006) found that parent banks control affiliate banks better, contributing to decreased
agency costs of distance. They attributed this finding to technological progress.
Parallel with Morrison and Wilhelm’s (2008) demise of the investment banking partnership, the
increased importance of IT (high initial investment needed and greater codification of employee skills)
may make small community banks inefficient and they may lose ground in competition with huge IT-
intensive banks. Small banks may need to redefine their models in this light. Small banks may be
forced to increasingly focus on niche markets in a particular market segment, geographic region, part
of the supply chain, or specific product.23
Not everything is grim for small(er) banks though. Empirical evidence points to the existence of
diversification discount in which diversification in multiple activities destroys firm value (Leaven and
Levine, 2007; Schmid and Walter, 2009). Big financial conglomerates may have entrenched
themselves and bigger focus may be desirable in the future.
The question is what makes conglomeration and increased complexity in banking special.
3.3. Costs of bank failure
In banking, there exists another, a more negative explanation of why IT may spur greater complexity.
Banks (and bankers) may intentionally increase complexity for their private benefit. They may bet on
earning high profits and disguise the risks that they are taking.
In banking, several implicit and explicit (government) guarantees encumber the control that bank
investors (such as depositors) have over bank risk-taking. Deposit insurance is prevalent in banking
and insured depositors have only a few incentives to monitor their bank’s risk. Even uninsured
depositors may rely on implicit government bailout guarantees. Consequently, banks may have bigger
incentives than non-financial companies to swiftly increase risk and the asset-substitution problem
may be more pronounced.
Additional key difference between banks and other firms is that bank failure creates huge negative
externalities for the economy at large. A collapse of one bank may damage confidence in the financial
system at large and may trigger a system-wide collapse or panic. If one bank goes bankrupt, deposit
holders may interpret this event as a signal for the existence of solvency problems in the entire
financial sector and react by massive withdrawal of funds. The social cost of bank failures may then be
considerable. Bank failures can produce a sharp monetary contraction and induce a recession. Bank
failures may reduce the supply of bank loans, which is especially detrimental to small- and medium-
23 In e-banking small banks may provide localized services and information (e.g., links to important community
information or specialized customer information); see Southard and Siau (2004).
2. 10
sized business financing (Hubbard, Kuttner, and Palia, 2002). The total collapse of a banking system
might even cause a breakdown of the payment system and impair trade. Empirical research confirms
that the costs of bank crises are high. In cross-country studies, Hoggarth, Reis, and Saporta (2002)
assessed the costs at 15 to 20% of annual GDP.24
The broad economic importance of bank stability and considerable costs of bank instability to the
economy at large justify the existence of extensive banking regulation. Deposit insurance prevents
costly bank runs (Diamond and Dybvig, 1983) but needs to be accompanied by capital regulation.
Capital regulation (e.g., Basel I, II and III capital requirements) aims to put bank capital at risk, giving
banks incentives to correctly evaluate the risks of their operations. Capital regulation may then
diminish the negative externalities of excessive risk-taking triggered by deposit insurance or other
implicit government guarantees.
3.4. Excessive complexity in banking
In the more negative view, banks may use IT support in calibrating complex risk-measurement and
risk-management models and designing complex products in order to disguise excessive risk-taking.
The complexity of loan agreements, which IT support enables, may, besides serving various needs and
preferences of customers, also trick customers into signing a loan contract without knowing its
detailed structure.25 For example, lending in mortgage markets was based on complex attributes of
mortgages such as adjustable interest rates, postponed mortgage principle payment, and substantial
prepayment fees, and did not require full documentation of ownership of assets and income (Mayer,
Pence, and Sherlund, 2009). Borrowers had a hard time understanding the mechanics of complex
mortgage terms (e.g., for adjustable-rate mortgages, see Bucks and Pence, 2008; Campbell, 2006) or
were even under attack by predatory lenders (Engel and McCoy, 2002).
The complexity of mortgage backed products was further increased due to misaligned incentives of
mortgage originators. The incentives of mortgage originators were largely driven by increasingly
frequent subsequent mortgage securitization. Mortgage lenders did not keep mortgages on their
balance sheets, but followed an ―originate-to-distribute‖ model: mortgages were pooled together and
were sold to investors on the capital markets. Because mortgage lenders did not cover the entire loss of
default, they were eager to collect higher origination fees at the expense of deteriorating lending
standards (Keys et al., 2010). Mayer, Pence, and Sherlund (2009) argued that the lack of correct
incentives of mortgage originators and falling house prices were the main drivers of mortgage
delinquencies in 2008.
24 For a comprehensive survey on banking crises, see Allen and Gale (2007).
25 A caveat should be made. IT is not the only driver for creating and disseminating complex products. Others
may include quantitative models and the institutional framework.
2. 11
Several market participants were tricked by complex mortgage products and other structured financial
products generated through the ―originate-to-distribute‖ model. These include credit-rating agencies,
large insurance companies (monoliners), and regulators. Large investment banks were able to reverse-
engineer the models that credit-rating agencies used to rate collateralized debt obligations. For
example, Standard & Poor’s provided a CDO Evaluator Manual on its website (Benmelech and
Dlugoszb, 2008) and investment banks could use it to obtain the highest possible rating at minimum
costs. Usually this also meant the highest inherent risk at the given rating.
The combination of complex financial conglomerates, off-balance-sheet financing through SPVs and
ABCP conduits also obscured the risks from the regulator. Calomiris and Mason (2004) showed that
credit card securitization was used to circumvent capital regulation in regulatory arbitrage.Acharya
and Schnabl (2009) saw regulatory arbitrage as one of the culprits of the 20072009 financial crisis.
The complexity of large financial conglomerates also created a too complex to fail problem. The
systemic concerns may force the regulator to bailout the failed large financial conglomerate.26
Worrisomely, banks may anticipate bailout and even become intentionally too complex to fail to ride
on implicit bailout guarantees. IT solutions may help banks to (intentionally or unintentionally) reach
this goal.
In short, banks and other firms use IT to boost product variety, customization and diversification in
related activities. However, banks may go too far in creating complex products and processes to hide
the risks from borrowers, credit-rating agencies, regulators, and other capital market participants.
4. Speed of change
Now the impact of IT on flexibility and the consequent repercussions for stability and
interconnectedness will be evaluated.
4.1. IT induces change and flexibility
The mere adoption of IT creates a huge change in a firm. Firms need to adopt IT swiftly together with
the entire range of coordinated changes in organizational activities (Milgrom and Roberts, 1990). The
use of IT may produce substantial economies of scale in only certain tasks. It is the manager’s
responsibility to lead the reorganization of processes and jobs to increase productivity of employees.
Autor, Levy, and Murnane (2002) analyzed two back-office departments of a bank that adopted check
26 The controlled unwinding of a large financial conglomerate is especially difficult if it operates under different
bankruptcy codes and under the authority of several regulators, if interconnections within the conglomerate are
opaque, and if bank creditors (e.g., depositors, REPO creditors) abruptly terminate their funding (Squam Lake
Working Group on Financial Regulation, 2009).
2. 12
imaging and optical character recognition software. They provided evidence that computer-based
technology replaces numerous procedural or rule-based tasks. However, many tasks were unchanged
and it was the manager’s role to see how these tasks would be organized in jobs. Specialized jobs were
created in the Deposit Processing Department, but in the Exceptions Processing Department the
development led to integration of tasks in one job.
Several corporate IT systems (e.g., Enterprise resource planning systems) include templates for the
business process design called best practices (Scheer and Habermann, 2000). Together with
implementation of a corporate IT system, a firm can modify its current business practices to reflect the
best business practices.27
The implementation of corporate IT systems equips firms with additional flexibility and agility to
transform business processes and products as a response to unexpected changes in the corporate
environment (Sambamurthy, Bharadwaj, and Grover, 2003).28 Enhanced communication, teamwork,
and cooperation within the firm and across the firm borders provide a fruitful framework for constant
modifications in business products and processes.29 Because business processes are digitized,
innovations in business processes can be easily replicated across the entire firm (McAfee and
Brynjolfsson, 2008). This creates substantial opportunities to quickly scale up advantage in the firm.
In addition, the internet access channel allows for swift (and relatively cheap) adoption of changes in
business products and immediate distribution to customers.30
Hitt, Keats, and DeMarie (1998) argue that firms need to obtain strategic flexibility in order to survive
in an increasingly competitive business environment. Firms may not have much choice but to be
prepared to enter and exit new markets immediately when opportunities and threats crystallize. In IT-
intensive industries competition has heated up and has become more of a ―win all or lose everything
situation (McAfee and Brynjolfsson, 2008).31 IT development has increased turnover of small firms
and concentration of the industry in large firms. Saunders (2009) attributed this result to the
27 Ramirez, Melville, and Lawler (2010) found synergies between IT and business process redesign as drivers for
strategic organizational change that would positively affect the market value of a firm. The fit between business
processes and IT is important (Trkman, 2010).
28 For example, service-oriented architecture (SOA) allows for service-based software components that are
attached to independent functional units (Baskerville et al., 2010). These functional units may be located inside
or even across corporate borders and may also provide a basis for designing flexible IT structures in traditionally
rigid industries such as banking (Homann, Rill, and Wimmer, 2004).
29 However, already implemented IT systems may also act as inhibitors of change. Legacy IT systems usually
use closed form architectures which are inflexible and force the bank to rely on a single IT vendor. This may
impede the introduction of new financial products or removal of redundant work processes (Mazursky, 1989).
30 In the case of a bank branch network, potential changes require a substantial period of time and investment
(e.g., due to education of employees).
31 The relationship goes in the other direction as well. IT investment is relatively more valuable in competitive
and dynamic industries (Melville, Gurbaxani, and Kraemer, 2007).
2. 13
observation that large firms have used business process replication to gain economies of scale whereas
small firms were operating in niche markets.
4.2. Risky growth strategy in banking
Banks are becoming flexible institutions with the ability to transform their products and their business
processes and to grow extraordinarily fast.32 This is very similar to other non-financial firms. What is
different (or more pronounced) in banking is that flexibility may go hand-in-hand with (potential)
instability and may be detrimental for the economy at large.
Several examples from the 20072009 financial crisis demonstrate the role of IT applications in
banks’ rapid and risky growth.33 The Icelandic bank Landsbanki realized extraordinary growth in the
Netherlands and the UK by offering Icesave online savings accounts with attractive interest rates. In
only five months of presence in the Netherlands, it raised €1.7b in approximately 130,000 accounts (de
Moor, du Perron, and Krop, 2009, pp. 54, 56). The subsequent collapse of Landsbanki created a
diplomatic dispute between Iceland and the UK and the Netherlands.
Another example that shows the dangers of high growth is the collapse of the UK bank Northern
Rock. Northern Rock’s assets on a consolidated basis grew more than six-fold from 1997 to 2006
(from £15.8 billion to £101.0 billion).34 During this period Northern Rock transformed from a building
society with a limited geographical focus to an important nationwide player in the UK mortgage
market. Rather than relying on branches Northern Rock employed IT based originate-and-distribute
model. Nationwide distribution was enabled by the network of intermediaries (e.g., large firms of
introducers and groups of smaller intermediaries) that relied on an online mortgage approval system.
In 2006, 89% of all mortgage lending was performed through intermediaries and 90% of all
intermediary business was conducted online.35 To finance this extraordinary growth, Northern Rock
substantially increased its leverage, which made it sensitive to wholesale securitization markets and
may be one of the main culprits in its demise (Shin, 2009). The systemic stability considerations
necessitated government intervention and Northern Rock was subsequently nationalized.
32 Bank managers argued that continuously evolving regulation (e.g., IFRS and Basel II), outsourcing of IT
personnel, systems, and processes and multi-channel access to products and services contribute towards more
agile banks (Oosterhout, Waarts, and van Hillegersberg, 2006).
33 On the other hand, IT could also be used strategically to deter entry. Gan and Riddiough (2008) showed how
government-sponsored enterprises (GSEs) in the mortgage market, such as Fannie Mae and Freddie Mac, could
use their competitive advantage to deter entry into the industry. Credit-scoring techniques (which heavily used
IT) have provided a scale advantage and GSEs were able to impose control through licensing agreements over
mortgage sellers. GSEs forced retail mortgage originators to simply apply GSEs’ credit-evaluation models
without revealing the precise mechanics of the models (see also van Order, 2001; Straka, 2000).
34 See Northern Rock Annual Report 1998, p. 31, and Northern Rock Annual Report 2006, p. 59.
35 Northern Rock Annual Report 2006, p. 34.
2. 14
The (negative) relationship between flexibility and stability in banking will now be further analyzed.
4.3. Flexibility, soft information, and instability in banking
IT increases the importance of hard quantifiable information, giving banks greater flexibility but also
contributing to their less stable footprint.
The introduction of internet banking changes depositors’ behavior by facilitating the shift from
relationship-oriented core deposits established through bank branches (e.g., checking accounts)
towards more non-relationship finance (e.g., money market deposit accounts and brokered deposits;
DeYoung, Lang, and Nolle, 2007). The non-relationship nature of deposits impacts bank stability.
Relationship-oriented core deposits seem to be more stable than market-based deposits. Iyer and Puri
(2010) provided evidence that depositors with longer relationships with the bank were less likely to
withdraw funds in a bank run. Shin (2009) showed that in the demise of Northern Rock internet,
telephone, offshore, and postal accounts were depleted to a much greater extent than the core branch
deposits. In addition, the combination of the increasingly non-relationship nature of bank lending
coupled with non-relationship market-based deposits may increase bank fragility (Song and Thakor,
The internet delivery channel also reduces the availability of soft information that a bank would
otherwise obtain through the person-to-person relationship at bank branches (Agarwal and Hauswald,
2008). Lending techniques that extensively use soft information, such as small-business lending, are
less suitable for use over the internet than those that rely on quantifiable hard information such as
credit card loans, auto loans, and mortgages. Banks that adopted internet banking realized an increase
in credit card lending, invested more in off-balance sheet activities and had more diversified loan
portfolios (DeYoung, Lang, and Nolle, 2007; Ciciretti, Hasan, and Zazzara, 2009).
IT developments and reliance on hard information has spurred securitization of consumer loans (e.g.,
credit card, auto, and mortgage loans) and large business commercial papers. The dissemination of
information through consumer credit bureaus together with better (and standardized) information
processing led to lower information capture and greater marketability of consumer loans.
Consequently, banks became more flexible but also lost their competitive advantage against other
banks and against financial markets.
Lost franchise values may go hand in hand with increased risk taking (Keeley, 1991; Martinez-Miera
and Repullo (2010)).36 Banks that securitize a large part of their portfolios face an increased moral
36 Evidence from the mortgage industry is aligned with the view that IT makes banking a fast-evolving win-or-
lose industry with increased risk. Livshits, MacGee, and Tertilt (2010) showed that consumer bankruptcy
2. 15
hazard problem, which may result in lax screening standards and lazy monitoring (Gorton and
Pennacchi, 1988; Berndt and Gupta, 2009). The evidence from the 20072009 financial crisis
confirms the negative relationship between marketability and stability (Mian and Sufi, 2009; Keys et
al., 2010).
However, IT developments do not always yield greater marketability. In contrast to consumer loans,
small business loans are rarely securitized, even though banks process them with transaction-lending
techniques that use hard quantifiable information (such as SBCS). The rationale may be the following.
Historic data about the performance of small business loans is rarely available and is bank-specific
(Temkin and Kormendi, 2003). Banks, especially small ones, often combine SBCS with other lending
techniques, including ones based on soft information. A rating agency involved in the securitization of
small business loans therefore needs to assess the bank’s performance and its process of loan
origination instead of the characteristics of the pool of small business loans. This is more costly. In
addition, moral hazard issues pertain to servicing securitized small business loans (see also Berger and
Frame, 2007). The high information content of small business loans persists.
The role of IT determines its impact on loan marketability. In the case of consumer loans, IT mainly
facilitates dissemination of information and, by doing this, increases marketability. In the case of SME
loans, however, IT development mainly leads to better processing of information and to a lower extent
to dissemination of information. Consistent with Hauswald and Marquez (2003), IT development
increases the advantage of a bank that engages in monitoring of SMEs, decreasing marketability of
small business loans.
The recipe for overcoming the drawbacks of flexibility/marketability would be to further engage in
relationship banking and use IT-induced flexibility to strengthen relationships with customers. Banks
can constantly improve products and services, increase their variety, and adjust them to customer
needs. For example, cross-selling is important for strengthening the relationship between a bank and
its borrowers (de la Torre et al., 2010). In addition, cross-selling may increase the stability of a
depositor base. Iyer and Puri (2010) found that depositors that also have loans at the same banks were
less likely to run. Cross-selling therefore acts also as partial insurance against a bank run. In addition,
banks should access their customers through multiple access channels and at different points in time.
For example, banks should use internet banking complementary to a strong branch network to promote
cross-selling of customized products and services.
Indeed, flexibility may sometimes go hand in hand with stability and IT developments may help
mediate information problems within banks. IT facilitates organizational practices (such as
increased in the U.S. due to two IT-related effects: lower transaction costs of lending and lower costs of
2. 16
multitasking, teamwork, and job rotation) that may mitigate communication problems between bank
4.4. Excessive interconnectedness in banking
Another danger of IT development in banking may crystallize. Excessive reliance on hard data can
lead to ―footloose corporations‖ through greater marketability (Boot, 2009; Boot and Marinč, 2010).
Following the hypes and fads that marketability spurs makes banks dependent on investor sentiment.
This may increase volatility and reduce bank stability (Shleifer and Vishny, 2010). The pressure from
the financial markets (e.g., due to information spillovers, Acharya and Yorulmazer, 2008) may force
bank(er)s to herd which makes them more interconnected.
For example, Gerding (2009) attributed major responsibility for the current financial crisis to the
sophisticated risk-management strategies by financial institutions (see also Haldane, 2009). The
default risk models that banks used relied substantially on historical data about loan delinquencies but
failed to consider the incentives of mortgage originators and therefore underestimated defaults among
borrowers (Rajan, Seru, and Vig, 2010).38 The error of models based on historical values is the highest
when soft information about borrowers is more important than hard quantifiable information.
Furthermore, such an error is systematic in nature and cannot be simply corrected by including more
detailed historical values.
One has to admit that IT is not directly responsible for the failure of default risk models. The main
fault lies in an inappropriate use of IT solutions. What may be true, however, is that IT simplified the
inclusion of a large amount of historical data. For example, sharing information through information
registries or extracting machine-readable data from the Web may create systemic problems because
banks would make decisions based on the same information. Incorporating human and economic
incentives into algorithmic analysis is more difficult to perform. Rajan, Seru, and Vig (2010) called for
the use of structural models instead of reduced-form statistical models (in a similar vein as used in
monetary policy decision-making in the last decade; see Gali and Gertler, 2007).
This may point to the current inefficiency of automated IT decision systems: they may generally
perform well, but in the case of a drastic event they may break down. The events in the ―flash crash
confirm the problematic nature of automated IT systems. On 6 May 2010, the U.S. equity and futures
markets fell by more than 5% and then quickly recovered. What is even more interesting is that several
37 Another such practice may be a rotation policy. Loan officers report more accurate information if they are
faced with the threat of rotation (Hertzberg, Liberti, and Paravisini, 2010).
38 Another systematic mistake in default models may be disregarding exposure of securities to systemic risk
(Coval, Jurek, and Stafford, 2009).
2. 17
stocks were traded at 1 cent per share, and several others for $100,000 per share, an event attributed to
the combination of the large order from automatic execution program and algorithmic trading systems
(CFTC and SEC, 2010).
A failure of automated IT systems may deepen a systemic shock. Beck (2010) argued that banks were
simply forced to disconnect their trading computers during the peak of the 20072009 financial crisis.
The environment changed so much that relying on historical data was useless. In addition, the
additional complexity was huge and computer models needed to be substantially reconfigured, which
required time. Caballero and Simsek (2009) argued that weakening bank balance sheets increases
interlinkages between banks. The complexity of such an environment drastically increases and
liquidity in the system may evaporate, further exacerbating the complexity and interlinkages in the
banking system.
Complex IT-supported risk management systems that banks employ sometimes increase systemic risk
even though they decrease the risk of an individual bank. For example, the diversification that risk
management produces may lower the risk of the individual bank but may increase the systemic risk of
several banks failing at the same time (Wagner, 2010). Adrian and Shin (2010) showed that
investment banks adjust their leverage to business cycles due to their VaR management. This
subsequently increases the volatility of security prices and market-wide volatility. Regulators should
focus on the stability of the entire banking system instead of the stability of an individual institution
and use risk-management systems (such as stress testing) themselves to control systemic risk.
4.5. Interconnectedness and decomposition of the value chain in banking
IT-enhanced communication may facilitate outsourcing of non-core capabilities and lead to (partial)
decomposition of the value chain.39 Outsourcing is common in the case of back-office business
processes such as check clearing and payment processing, risk management and measurement
systems, and IT systems.40
Outsourcing eases the complexity of individual bank but may create even direr systemic risk concerns.
For example, banks increasingly rely on the credit assessment of credit-rating agencies. Credit-rating
agencies drastically underestimated the default probabilities before the 20072009 financial crisis.41 In
39 IT and outsourcing are especially correlated in the case of high levels of input diversity, if the level of
technological change is low and industry standards are present (Sahaym, Steensma, and Schilling, 2007).
40 Tas and Sunder (2004) positively assess offshore outsourcing of business processes in banking (e.g., overseas
call centers for customer support) only if supporting tools and application software (e.g., virtual team rooms and
active project plans) are of sufficiently high quality. IT outsourcing was prevalent in small U.S. banks, whereas
large banks relied on internally-built IT systems (Ang and Straub, 1998).
41 In November 2007, S&P recalibrated its online LEVELS@default model in a way that default probabilities of
non-documentation loans with low FICO scores increased by 60% (Standard & Poors, 2007).
2. 18
this sense, outsourcing of credit assessment to credit-rating agencies may have triggered systemic
exposure of the entire banking system to the default risk models of a few mayor credit-rating agencies.
This increased the interconnectedness of the banking industry.42
Security IT risks also increase the interconnection between banks. If a large credit card database is
stolen then all banks (and customers’ trust in their security) may suffer at the same time.43 In addition,
if firms are connected through common IT architecture, the security of the network may depend on the
weakest link, the strongest link, or the average link (Anderson and Moore, 2006), depending on how
the investment in security systems is organized. Firms may invest in security on their own, the best
firm may provide security, or firms may together work on security.
Decomposition of the value chain may also lead to additional interconnectedness across banking,
insurance and mutual fund industries, credit rating agencies and IT providers. Such interconnectedness
may lead to unexpected spillovers of risks and contagion (Allen and Carletti, 2006). The 20072009
financial crisis clearly demonstrated the dangers of such interconnectedness. Over a span of eleven
days (from 14 to 25 September 2008), the investment bank Merrill Lynch needed to be sold to Bank of
America, the investment bank Lehman Brothers filed for bankruptcy, the insurance corporation AIG
obtained heavy government support, and the savings bank Washington Mutual was seized by the
Federal Deposit Insurance Corporation (see also Brunnermeier, 2009).
It has been shown that IT may be one of the drivers of interconnectedness. Alternatively, banks may
intentionally herd and increase interconnectedness, and one way of doing this may be to rely on
common models and use common IT solutions. In this more negative view, IT may provide support
for banks to become too interconnected to fail in order to exploit government guarantees.
5. Conclusions and brief policy implications
IT spurs fundamental changes in banking. Banks are driven to become highly complex and mutually
interlinked institutions with the ability to quickly change their products, services, and processes. What
42 In the securitization market, the impact of credit-rating agencies is not only direct by rating securitization
tranches but also indirect by rating monolinersinsurance companies that insure the securitization tranches.
Monoliners became indispensible for the existence of securitization markets, and their ability to offer credible
guarantees depends heavily on themselves having AAA ratings. A failure of a monoliner then produces a chain
reaction through banks active in a structured finance market.
43 Although there has been limited evidence of a systemic IT-induced failure, the increasing use of IT in banking
may elevate the probability of such event. Nonetheless, there have been several individual failures: JP Morgan
Chase’s online banking was down from 13 to 15 September 2010 (
business/16chase.html?scp=1&sq=chase%20outage&st=cse). On 5 July 2010, the IT outage at Singapore’s DBS
bank lasted for seven hours and made ATMs unavailable. DBS bank has outsourced some of its IT operations to
IBM. IBM has taken responsibility for the outage and attributed it to human error
2. 19
makes banks special is their systemic importance for the economy at large and the consequent
presence of implicit and explicit guarantees in banking. Exacerbated risk shifting and the asset-
substitution problem in banking have revealed a more negative picture of excessively increased
complexity, interconnectedness, and banks’ ability to change quickly. Brief policy implications are
now given.
Banks may use IT support to provide excessively complex products and to hide the risks involved.
Prudential regulation should limit redundant complexity. Elevating capital requirements across the
board may streamline banks toward prudent risk taking. The regulator should surveil corporate
governance mechanisms including the relationship between risk taking and pay for performance for
core bank employees. This could shift the focus of regulation from hard data to human incentives.
Anti-predatory practices in mortgage markets can be established. Prompt corrective action should
facilitate timely intervention and special bank bankruptcy regime should allow for fast split up of
different parts of the financial conglomerate. Large financial conglomerates should write their own
resolution plans so called ―living wills.‖44 Such living wills should also deal with the transition or
dissolution of bank information systems. Certain too risky activities can be separated from banks (see
the Volcker rule in the Dodd-Frank Act that prohibits proprietary trading by banks for their own
In banking flexibility has (also) a dark side. It may derail the key attribute of a bank: its stability.
Moreover, it may work to increase interconnectedness by allowing banks to follow fads and hype, and
thereby increase the volatility and systemic risk in banking. The regulator can promote responsible
bank growth through higher capital requirements for systemically important banks45 and/or through
dynamic loan loss provisioning (i.e., by acknowledging already incurred and anticipated losses in bank
loan portfolio; see developments under Basel III and Saurina, 2009 for Spanish experience). Dynamic
loan loss provisions may also work as a macroprudential tool for the regulator to measure the
resilience of the banking system against a macroeconomic shock.
IT may also help the regulator. For example, information-sharing IT architectures could be designed to
limit the potentially contagious effect of information sharing and to maximize the benefits of
disclosure. Stress test models could analyze the impact of the individual bank failure in the closely
interconnected banking system. Disclosure and closer surveillance of automatic decision systems used
in banking may also be needed. The discrepancy between banks and their regulators seems to exist.
Whereas banks have fully embraced IT developments, the regulators may have been lagging behind.
44 See the recently accepted Dodd-Frank Act; Dodd-Frank Wall Street Reform and Consumer Protection Act,
H.R. 4173, 111th Cong., 2nd Sess. 2010.
45 For example, Switzerland aims to impose capital requirements of 19% of risk weighted assets for their
systemically important banks. Adrian and Brunnermeier (2010) have proposed macroprudential regulation based
on the CoVaR measure of interconnectedness between financial institutions.
2. 20
Acharya, V.V., and P. Schnabl (2009), How Banks Played the Leverage "Game"?, in Restoring
Financial Stability: How to Repair a Failed System, ed. by V.V. Acharya, and M. Richardson. Wiley,
Hoboken, New Jersey, p. 83-100.
Acharya, V.V., and T. Yorulmazer (2008), Information Contagion and Bank Herding, Journal of
Money, Credit and Banking, Vol. 40(1), p. 215-231.
Adrian, T., and M.K. Brunnermeier (2010), CoVaR, Working paper, November 1.
Adrian, T., and H.S. Shin (2010), Liquidity and Leverage, Journal of Financial Intermediation, Vol.
19(3), p. 418-437.
Agarwal, S., and R.B.H. Hauswald (2007), The Choice between Arm's-Length and Relationship Debt:
Evidence from Eloans; AFA 2008 New Orleans Meetings Paper, March.
Allen, F., and E. Carletti (2006), Credit Risk Transfer and Contagion, Journal of Monetary
Economics, Vol. 53, p. 89-111.
Allen, F., and D. Gale (2007), Understanding Financial Crises, Oxford University Press.
Anderson, C. (2006), The Long Tail: Why the Future of Business is Selling Less of More. Hyperion.
Ang, S., and D.W. Straub (1998), Production and Transaction Economies and IS Outsourcing: A
Study of the U. S. Banking Industry, MIS Quarterly, Vol. 22(4), p. 535-552.
Aral, S., E. Brynjolfsson, and M. Van Alstyne (2007), Information, Technology and Information
Worker Productivity: Task Level Evidence, NBER Working Paper Series No. 13172, June 2007.
Anderson, R., and T. Moore (2006), The Economics of Information Security, Science, Vol. 314(5799),
p. 610-613.
Autor, D.H., F. Levy, and R.J. Murnane (2003), The Skill Content Of Recent Technological Change:
An Empirical Exploration, Quarterly Journal of Economics, Vol. 118(4), p. 1279-1333.
Autor, D.H., F. Levy, and R.J. Murnane (2002), Upstairs, Downstairs: Computers and Skills on Two
Floors of a Large Bank, Industrial and Labor Relations Review, Vol. 55(3), p. 432-447.
Bamberger, K.A. (2010), Technologies of Compliance: Risk and Regulation in a Digital Age, Texas
Law Review, Vol. 88(4), p. 669-739.
Bartel, A., C. Ichniowski, and K. Shaw (2007), How Does Information Technology Affect
Productivity? Plant-Level Comparisons of Product Innovation, Process Improvement, and Worker
Skills, Quarterly Journal of Economics, Vol. 122(4), p. 1721-1758.
Baskerville, R. L., M. Cavallari, K. Hjort-Madsen, J. Pries-Heje, M. Sorrentino, and F. Virili (2010),
The Strategic Value of SOA: A Comparative Case Study in the Banking Sector, International Journal
of Information Technology and Management, Vol. 9(1), p. 30-53.
Beccalli, E. (2007), Does IT Investment Improve Bank Performance? Evidence from Europe, Journal
of Banking and Finance, Vol. 31(7), p. 2205-2230.
Beck, R. (2010), Can IT Lean against the Wind?. Communications of the ACM, Vol. 53(5), 38-40.
Beijnen, C., and W. Bolt (2009), Size Matters: Economies of Scale in European Payments Processing,
Journal of Banking and Finance, Vol. 33(2), p. 203-210.
Benmelech, E., and J., Dlugosz (2009), The Alchemy of CDO Credit Ratings, Journal of Monetary
Economics, Vol. 56(5), p. 617-634.
Berger, A.N. (2003), The Economic Effects of Technological Progress: Evidence from the Banking
Industry, Journal of Money, Credit and Banking, Vol. 35(2), p. 141-176.
2. 21
Berger, A.N., A.M. Cowan, and W.S. Frame (2009), The Surprising Use of Credit Scoring in Small
Business Lending by Community Banks and the Attendant Effects on Credit Availability and Risk,
Federal Reserve Bank of Atlanta Working Paper 2009-9, March.
Berger, A.N., and R. DeYoung (2006), Technological Progress and the Geographic Expansion of the
Banking Industry, Journal of Money, Credit, and Banking, Vol. 38(6), p. 1483-1513.
Berger, A.N., A.A. Dick, L.G. Goldberg, and L.J. White (2007), Competition from Large,
Multimarket Firms and the Performance of Small, Single-Market Firms: Evidence from the Banking
Industry, Journal of Money, Credit and Banking, Vol. 39(2-3), p. 331-368.
Berger, A.N., M. Espinosa-Vega, W.S. Frame, and N. Miller (2005), Debt, Maturity, Risk, and
Asymmetric Information, Journal of Finance, Vol. 60, p. 28952923.
Berger, A.N., W.S. Frame, and N. Miller (2005), Credit Scoring and the Availability, Price, and Risk
of Small Business Credit, Journal of Money, Credit, and Banking, Vol. 37, p. 191222.
Berger, A.N., and W.S. Frame (2007), Small Business Credit Scoring and Credit Availability, Journal
of Small Business Management, Vol. 45(1), p. 5-22.
Berger, A.N., and G.F. Udell (2006), A More Complete Conceptual Framework for SME Finance,
Journal of Banking and Finance, Vol. 30, p. 2945-2966.
Berndt, A., and A. Gupta (2009), Moral Hazard and Adverse Selection in the Originate-To-Distribute
Model of Bank Credit, Journal of Monetary Economics, Vol. 56, p. 725743.
Bils, M., and P.J. Klenow (2001), The Acceleration of Variety Growth, American Economic Review,
Vol. 91(2), p. 274-280.
BIS (2009), Statistics on Payment and Settlement Systems in Selected Countries - Figures for 2007,
Bank for International Settlements,
Boot, A.W.A., (2009), Footloose Corporations: Have Financial Markets Destabilized Firms? In Dutch:
―De ontwortelde onderneming‖, Van Gorcum Publishers.
Boot, A.W.A., and M. Marinč (2008), The Evolving Landscape of Banking, Industrial and Corporate
Change, Vol. 17(6), p. 11731203.
Boot, A.W.A., and M. Marinč (2010), Financial Innovation: Economic Growth versus Instability in
Bank-Based versus Financial Market Driven Economies, Work in progress.
Bresnahan, T.F., E. Brynjolfsson, and L. Hitt (2002). Information Technology, Workplace
Organization and the Demand for Skilled Labor: Firm-level Evidence, Quarterly Journal of
Economics, Vol. 117(1), p. 339-376.
Bresnahan, T.F., and M. Trajtenberg (1996), General Purpose Technologies 'Engines of Growth'?,
Journal of Econometrics, Vol. 65(1), p. 83-108.
Brews, P.J., and C.L. Tucci (2004), Exploring the Structural Effects of Internetworking, Strategic
Management Journal, Vol. 22(5), p. 429-451.
Brunnermeier, M.K. (2009), Deciphering the 2007-08 Liquidity and Credit Crunch, Journal of
Economic Perspectives, Vol. 23(1), p. 77-100.
Brynjolfsson, E., and L.M. Hitt (2000), Beyond Computation: Information Technology,
Organizational Transformation and Business Performance, Journal of Economic Perspectives, Vol.
14(4), p. 23-48.
Brynjolfsson, E., and A. Saunders (2010), Wired for Innovation: How Information Technology is
Reshaping the Economy, MIT Press.
Brynjolfsson, E., and M. D. Smith (2000), Frictionless Commerce? A Comparison of Internet and
Conventional Retailers, Management Science, Vol. 46(4), p. 563-585.
2. 22
Bucks, B., and K. Pence (2008), Do Borrowers Know Their Mortgage Terms? Journal of Urban
Economics, Vol. 64, p. 218-33.
Caballero, R.J., and A. Simsek (2009), Fire Sales in a Model of Complexity, NBER Working Papers
15479, National Bureau of Economic Research, Inc.
Calomiris, C.W., and J.R. Mason (2004), Credit Card Securitization and Regulatory Arbitrage,
Journal of Financial Services Research, Vol. 26(1), p. 5-27.
Campbell, J.Y. (2006), Household Finance, Journal of Finance, Vol. 61, p. 1553-1604.
Campbell, D., and F. Frei (2010), Cost Structure, Customer Profitability, and Retention Implications
of Self-Service Distribution Channels: Evidence from Customer Behavior in an Online Banking
Channel, Management Science, Vol. 56(1), p. 4-24.
Casolaro, L., and G. Gobbi (2007), Information Technology and Productivity Changes in the Banking
Industry, Economic Notes, Vol. 36(1), p. 43-76.
CFTC and SEC, 2010, Findings Regarding the Market Events on May 6, 20010, Report of the Staffs
of the CFTC and SEC to the Joint Advisory Committee on Emerging Regulatory Issues, September
30, 2010,
Channon, D.F. (1998), The Strategic Impact of IT on the Retail Financial Services Industry, Journal of
Strategic Information Systems, Vol. 7(3), p. 183-197.
Chiasson, M.W., and E. Davidson (2005), Taking Industry Seriously in Information Systems
Research, MIS Quarterly, Vol. 29(4), p. 591-606.
Ciciretti, R., I. Hasan, and C. Zazzara (2009), Do Internet Activities Add Value? Evidence from the
Traditional Banks, Journal of Financial Services Research, Vol. 35(1), p. 81-98.
Courchane, M., D. Nickerson, and R. Sullivan (2002), Investment in Internet Banking as a Real
Option: Theory and Tests, Journal of Multinational Financial Management, Vol. 12, p. 347363.
Coval, J., J. Jurek, and E. Stafford (2009), The Economics of Structured Finance, Journal of Economic
Perspectives, Vol. 23(1), p. 325.
Dahlberg, T., N. Mallat, J. Ondrus, and A. Zmijewska (2008), Past, Present and Future of Mobile
Payments Research: A Literature Review, Electronic Commerce Research and Applications, Vol.
7(2), p. 165-181.
Damanpour, F. (1996), Organizational Complexity and Innovation: Developing and Testing Multiple
Contingency Models, Management Science, Vol. 42(5), p. 693-716.
Davenport, T. (2005), Thinking for a Living, Boston: Harvard Business School Press.
de la Torre, A., M.S. Martinez Peria, and S.L. Schmukler (2010), Bank Involvement with SMEs:
Beyond Relationship Lending, Journal of Banking and Finance, Vol. 34(9), p. 2280-2293.
de Moor, A.J.C., du Perron, C.E. and P.J. Krop (2009), De bevoegdheden van De Nederlandsche Bank
inzake Icesave, Ordered by the Ministry of Finance in The Netherlands, 11 June, 2009.
DeYoung, R. (2005). The Performance of Internet-Based Business Models: Evidence from the
Banking Industry, Journal of Business, Vol. 78(3), p. 893-947.
DeYoung, R., W.W. Lang, and D.L. Nolle (2007), How the Internet Affects Output and Performance
at Community Banks, Journal of Banking and Finance, Vol. 31(4), p. 1033-1060.
DeYoung, R., D. Glennon, and P. Nigro (2008), Borrower-Lender Distance, Credit Scoring, and Loan
Performance: Evidence from Informational-Opaque Small Business Borrowers, Journal of Financial
Intermediation, Vol. 17(1), p. 113-143.
2. 23
Diamond, D., and P. Dybvig (1983), Bank Runs, Deposit Insurance and Liquidity, Journal of Political
Economy, Vol. 91, p. 401-419.
Dick, A.A. (2007), Market Size, Service Quality and Competition in Banking, Journal of Money,
Credit and Banking, Vol. 39, p. 4981.
Duffie, D. (2010), The Failure Mechanics of Dealer Banks, Journal of Economic Perspectives, Vol.
24, p. 51-72.
Elberse, A. (2008), Should You Invest in the Long Tail?, Harvard Business Review, Vol. 86(7/8), p.
Engel, K.C. and P.A. McCoy (2002), A Tale of Three Markets: The Law and Economics of Predatory
Lending, Texas Law Review, Vol. 80(6), p. 1255-1381.
FDIC, 2010, Failed Bank List, October 2010.
Felici, R., and M. Pagnini (2008), Distance, Bank Heterogeneity and Entry in Local Banking Markets,
Journal of Industrial Economics, Vol. 56(3), p. 500-534.
Fender, I., and M.S. Gibson (2001). Stress Testing in Practice: A Survey of 43 Major Financial
Institutions, BIS Quarterly Review, June, 58-62.
Frame, W.S., and L.J. White (2009), Technological Change, Financial Innovation, and Diffusion in
Banking Working paper, July 15.
Frame, W.S., M. Padhi, and L. Woosley (2004), The Effect of Credit Scoring on Small Business
Lending in Low- and Moderate Income Areas, Financial Review, Vol. 39, p. 3554.
Frame, W.S., A. Srinivasan, and L. Woosley (2001), The Effect of Credit Scoring on Small Business
Lending, Journal of Money Credit and Banking, Vol. 33, p. 813825.
Furst, K., W.W. Lang, and D.E. Nolle (2002), Internet Banking, Journal of Financial Services
Research, Vol. 22, p. 95117.
Gali, J., and M. Gertler (2007), Macroeconomic Modeling for Monetary Policy Evaluation, Journal of
Economic Perspectives, Vol. 21(4), p. 25-45.
Gan, J., and T.J. Riddiough (2008), Monopoly and Information Advantage in the Residential
Mortgage Market, Review of Financial Studies, Vol. 21(6), p. 2677-2703.
Gerding, E.F. (2009), The Outsourcing of Financial Regulation to Risk Models and the Global
Financial Crisis: Code, Crash, and Open Source, Washington Law Review, Forthcoming.
Gorton, G., and G. Pennacchi (1988), Banks and Loan Sales: Marketing Non-Marketable Assets,
Journal of Monetary Economics, Vol. 35, p. 389411.
Haldane, A. (2009), Why Banks Failed the Stress Test, speech at the Marcus-Evans Conference on
Stress-Testing, 13 February (2009).
Hancock, D., D.B. Humphrey, and J. Wilcox (1999), Cost Reductions in Electronic Payments: The
Roles of Consolidation, Economies of Scale, and Technical Change, Journal of Banking and Finance,
Vol. 23, p. 391-421.
Hauswald, R., and R. Marquez (2003), Information Technology and Financial Services Competition
Review of Financial Studies 16(3), 921-948.
Hendershott, T., C.M. Jones, and A.J. Menkveld (2010), Does Algorithmic Trading Improve
Liquidity? Journal of Finance, Forthcoming.
Hernando, I., and M.J. Nieto (2007), Is the Internet Delivery Channel Changing Banks' Performance?
The Case of Spanish Banks, Journal of Banking and Finance, Vol. 31(4), p. 1083-1099.
2. 24
Hertzberg, A., Liberti, J.M., and D. Paravisini (2010), Information and Incentives Inside the Firm:
Evidence from Loan Officer Rotation, Journal of Finance, Vol. 65(3), p. 795-828.
Hinds, D. (2004), Micropayments: A Technology with a Promising but Uncertain Future,
Communications of the ACM, Vol. 47, p. 44.
Hitt, L.M., 1999, Information Technology and Firm Boundaries: Evidence from Panel Data,
Information Systems Research 10(2), 134-149.
Hitt, M.A., B.W. Keats, and S.M. DeMarie (1998), Navigating in the New Competitive Landscape:
Building Strategic Flexibility and Competitive Advantage in the 21st Century, Academy of
Management Executive, Vol. 12(4), p. 22-42.
Hoggarth, G., R. Reis, and V. Saporta (2002), Costs of Banking System Instability: Some Empirical
Evidence, Journal of Banking & Finance, Vol. 26(5), p. 825855.
Homann, U., M. Rill, and A. Wimmer (2004), Flexible Value Structures in Banking, Communications
of the ACM, Vol. 47(5), p. 34-36.
Hubbard, R.G., K.N. Kuttner, and D.N. Palia (2002), Are There Bank Effects in Borrowers’ Costs of
Funds? Evidence from a Matched Sample of Borrowers and Banks, Journal of Business, Vol. 75(4), p.
Humphrey, D., M. Willesson, G. Bergendahl, and T. Lindblom (2006), Benefits from a Changing
Payment Technology in European Banking, Journal of Banking and Finance, Vol. 30(6), p. 1631-
IMF, 2010a, Global Financial Stability Report: Sovereigns, Funding, and Systemic Liquidity, World,
Economic and Financial Surveys, October 2010.
IMF, 2010b, World Economic Outlook Database, October 2010.
Iyer, R., and M. Puri (2010), Understanding Bank Runs: The Importance of Depositor-Bank
Relationship and Networks, Review of Financial Studies, forthcoming.
Jorion, P (2006), Value at Risk: The New Benchmark for Managing Financial Risk, 3rd Edition,
Jovanovic, B., and P.L. Rousseau (2005), General Purpose Technologies, NBER Working Paper
11093, Cambridge, MA.
Kallberg, J.G., and F.G. Udell (2003), The Value of Private Sector Business Credit Information
Sharing: The US Case, Journal of Banking and Finance, Vol. 27(3), p. 449-469.
Kapoor, M., S. Ravi, and J. Morduch (2007), From Microfinance to m- Finance, Innovations:
Technology, Governance, Globalization, Vol. 2(1-2), p. 82-90.
Keeley, M. (1990), Deposit Insurance, Risk, and Market Power in Banking, American Economic
Review, Vol. 80, p. 1183-1200.
Keys, B. J., T. K. Mukherjee, A. Seru, and V. Vig (2010), Did Securitization Lead to Lax Screening?
Evidence from Subprime Loans, Quarterly Journal of Economics, Vol. 125(1), p. 307-362.
KPMG, 2010, Consumers and Convergence IV, Convergence Goes Mainstream: Convenience Edges
Out Consumer Concerns Over Privacy and Security, July, 2010,
Laeven, L., and R. Levine (2007), Is There a Diversification Discount in Financial Conglomerates?,
Journal of Financial Economics, Vol. 85(2), p. 331-367.
Lee-Kelley, L., and T. Sankey (2008), Global Virtual Teams for Value Creation and Project Success:
A Case Study, International Journal of Project Management, Vol. 26(1), p. 51-62.
2. 25
Liberti, J.M., and A.R. Mian (2009), Estimating the Effect of Hierarchies on Information Use, Review
of Financial Studies, Vol. 22(10), p. 4057-4090.
Liu, Y., and T. Ravichandran (2008), A Comprehensive Investigation on the Relationship between
Information Technology Investments and Firm Diversification. Information Technology and
Management, Vol. 9(3), p. 169-180.
Livshits, I., J. MacGee, and M. Tertilt (2010), Accounting for the Rise in Consumer Bankruptcies,
American Economic Journal: Macroeconomics, Vol. 2(2), p. 165-193.
Majchrzak, A., A. Malhotra, J. Stamps, and J. Lipnack (2004), Can Absence Make a Team Grow
Stronger?, Harvard Business Review, Vol. 82(5), p. 131-137.
Mallat, N., M. Rossi, and V. K. Tuunainen (2004), Mobile banking services. Communications of the
ACM, Vol. 47(5), p. 42-46.
Martinez-Miera, D., and R. Repullo (2010), Does Competition Reduce the Risk of Bank Failure?,
Review of Financial Studies, Vol. 23, p. 3638-3664.
Mazursky, A.D. (1989), Closed-Architecture Systems, Information Systems Management, Vol. 6(3), p.
Mayer, C., K. Pence, and S.M. Sherlund (2009), The Rise in Mortgage Default, Journal of Economic
Perspectives, Vol. 23 (1), p. 27-50.
McAfee, A.P. (2006), Enterprise 2.0: The Dawn of Emergent Collaboration, MIT Sloan Management
Review, Vol. 47(3), p. 21-28.
McAfee, A.P., and E. Brynjolfsson (2008), Investing in the IT That Makes a Competitive Difference,
Harvard Business Review, Vol. 86(7/8), p. 98107.
Melville, N., K. Kraemer, and V. Gurbaxani (2004), Review: Information Technology and
Organizational Performance: An Integrative Model of IT Business Value, MIS Quarterly, Vol. 28(2),
p. 283-322.
Melville, N., V. Gurbaxani, and K. Kraemer (2007), The Productivity Impact of Information
Technology across Competitive Regimes: The Role of Industry Concentration and Dynamism,
Decision Support Systems, Vol. 43(1), p. 229-242.
Mian, A., and A. Sufi (2009), The Consequences of Mortgage Credit Expansion: Evidence from the
U.S. Mortgage Default Crisis, Quarterly Journal of Economics, Vol. 124, p. 1449-1496.
Milgrom, P., and J. Roberts (1990), The Economics of Modern Manufacturing: Technology, Strategy,
and Organization, American Economic Review, Vol. 80(3), p. 511-528.
Morrison, A.D., and W.J. Wilhelm (2008), The Demise of Investment Banking Partnerships: Theory
and Evidence, Journal of Finance, Vol. 63(1), p. 311-350.
Pagano, M., and T. Jappelli (1993), Information Sharing in Credit Markets, Journal of Finance, Vol.
43, p. 16931718.
Pan, A., and Á. Viña (2004), An Alternative Architecture for Financial Data Integration,
Communications of the ACM, Vol. 47(5), p. 37-40.
Pew Internet & American Life Project, 2004,
Pew Internet & American Life Project, 2010, Older Adults and Social Media, August 27, 2010,
Rajan, U., A. Seru, and V. Vig (2010), Statistical Default Models and Incentives, American Economic
Review, Vol. 100(2), p. 506-510.
2. 26
Ramirez, R., N. Melville, and E. Lawler (2010), Information Technology Infrastructure,
Organizational Process Redesign, and Business Value: An Empirical Analysis, Decision Support
System, Forthcoming.
Ravichandran, T., Y. Liu, S. Han, and I. Hasan (2009). Diversification and Firm Performance:
Exploring the Moderating Effects of Information Technology Spending. Journal of Management
Information Systems, Vol. 25(4), p. 205-240.
Sahaym, A., H.K. Steensma, and M.A. Schilling (2007), The Influence of Information Technology on
the Use of Loosely Coupled Organizational Forms: An Industry-Level Analysis, Organization
Science, Vol. 18(5), p. 865-880.
Sambamurthy, V., A. Bharadwaj, and V. Grover (2003), Shaping Agility through Digital Options:
Reconceptualizing the Role of Information Technology in Contemporary Firms, MIS Quarterly, Vol.
27(2), p. 237-263.
Saunders, A. (2009), Has Information Technology Leveled in the Competitive Playing Field?,
Working paper, February 2009.
Saurina,J.(2009), Loan Loss Provisions in Spain. A Working Macroprudential Tool, Estabilidad
Financiera, Vol. 17, p. 11-26.
Scheer, A., and F. Habermann (2000), Making ERP a Success: Using Business Process Models to
Achieve Positive Results, Communications of the ACM, Vol. 43(4), p. 57-61.
Schmid, M.M., and I. Walter (2009), Do Financial Conglomerates Create or Destroy Economic
Value?, Journal of Financial Intermediation, Vol. 18(2), p. 193-216.
Schmiedel, H., M. Malkamäki, and J. Tarkka (2006), Economies of Scale and Technological
Development in Securities Depository and Settlement Systems, Journal of Banking and Finance, Vol.
30, p. 1783-1806.
Shin, H.S. (2009), Reflections on Northern Rock: The Bank Run That Heralded the Global Financial
Crisis, Journal of Economic Perspectives, Vol. 23(1), p. 101-119.
Shleifer, A., and R.W. Vishny (2010), Unstable Banking, Journal of Financial Economics,
Forthcoming, September.
Song, F., and A.V. Thakor (2007), Relationship Banking, Fragility, and the Asset-Liability Matching
Problem, Review of Financial Studies, Vol. 20, p. 2129-2177.
Southard, P.B., and K. Siau (2004), A Survey of Online E-Banking Retail Initiatives, Communications
of the ACM, Vol. 47(10), p. 99-102.
Squam Lake Working Group on Financial Regulation (2009), Improving Resolution Options for
Systemically Relevant Financial Institutions, Council on Foreign Relations Press, October 2009.
Standard & Poor's, 2007, Standard & Poor's Enhances LEVELSо 6.1 Model, November 9,
Stein, J.C. (2002), Information Production and Capital Allocation: Decentralized vs. Hierarchical
Firms, Journal of Finance, Vol. 57, p. 18911921.
Straka, J.W. (2000), A Shift in the Mortgage Landscape: The 1990s’ Move to Automated Credit
Evaluations, Journal of Housing Research, Vol. 11, p. 207-232.
Tallon, P.P. (2007), Does IT Pay to Focus? An Analysis of IT Business Value under Single and
Multi-Focused Business Strategies. Strategic Information Systems, Vol. 16, p. 278-300.
Tas, J., and S. Sunder (2004), Financial Services Business Process Outsourcing, Communications of
the ACM, Vol. 47(5), p. 50-52.
2. 27
Temkin, K., and R.C. Kormendi (2003), An Exploration of a Secondary Market for Small Business
Loans, Small Business Administration,
Trkman, P. (2010), The Critical Success Factors of Business Process Management, International
Journal of Information Management, Vol. 30(2), p. 125-134.
Turban, E., E. McLean, J. Wetherbe, N. Bolloju, and R. Davison (2002), Information Technology for
Management: Transforming Business in the Digital Economy, 3rd edition, John Wiley & Sons, New
van Oosterhout, M., E. Waarts, and J. van Hillegersberg (2006), Change Factors Requiring Agility and
Implications for IT, European Journal of Information Systems, Vol. 15(2), p. 132-145.
Van Order, R. (2001), A Microeconomic Analysis of Fannie Mae and Freddie Mac, Regulation, Vol.
23, p. 27-33.
VanHoose, D.D. (2009), Internet Banking, Networks Financial Institute Policy Brief 2009-PB-12,
December, 2009.
Wagner, W. (2010), Diversification at Financial Institutions and Systemic Crises, Journal of Financial
Intermediation, Vol. 19(3), p. 373-386.
Willis, L.E. (2006), Decisionmaking and the Limits of Disclosure: the Problem of Predatory Lending:
Pricing, Maryland Law Review, Vol. 65, p. 707-840.
Wright, A. (2002), Technology as an Enabler of the Global Branding of Retail Financial Services,
Journal of International Marketing, Vol. 10(2), p. 8398.
... Мавзуга оид адабиётлар таҳлили IТлар банк ва уларнинг алоқаларини ривожлантириб, фаолиятни тезкор равишда қайта лойиҳалаштиришга имкон беради [2]. Ўз ўрнида, банк секторининг ички ва ташқи иш фаолиятлари ITларнинг ривожланиши билан янада ривожланиб бормоқда [3] ва бу энг катта таъсир қилган соҳа сифатида банк тизимини кўрсатиш мумкин [4]. ...
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In spite of the conspicuous use of the Internet as a delivery channel, there is a relative dearth of empirical studies that provide a quantitative analysis of the impact of the Internet on banks´ financial performance. This paper attempts to fill this gap by identifying and estimating the impact of the adoption of a transactional web site on financial performance using a sample of 72 commercial banks operating in Spain over the period 1994-2002. The impact on banks´ performance of transactional web adoption takes time to appear. The adoption of the Internet as a delivery channel involves a gradual reduction in overhead expenses (particularly, staff, marketing and IT). This effect is statistically significant after one and a half years after adoption. The cost reduction translates into an improvement in banks´ profitability, which becomes significant after one and a half years in terms of ROA and after three years in terms of ROE. The paper also concludes that the Internet is being used as a complement to, rather than a substitute for, physical branches.
We test some predictions about the effects of technological progress on geographic expansion using data on banks in U.S. multibank holding companies over 1985-1998. Specifically, we test whether over time (a) parental control over affiliate banks has increased, and (b) the agency costs associated with distance from the parent have decreased. The data suggest that banking organizations exercise significant control over affiliates that has been increasing over time, and that the agency costs associated with distance have decreased somewhat over time. The findings are consistent with the hypothesis that technological progress has facilitated the geographic expansion of the banking industry.
We examine the economic effects of small business credit scoring (SBCS) and find that it is associated with expanded quantities, higher average prices, and greater risk levels for small business credits under $100,000. These findings are consistent with a net increase in lending to relatively risky "marginal borrowers" that would otherwise not receive credit, but pay relatively high prices when they are funded. We also find that: 1) bank-specific and industrywide learning curves are important; 2) SBCS effects differ for banks that adhere to "rules" versus "discretion" in using the technology; and 3) SBCS effects differ for slightly larger credits.
This paper examines technological progress and its effects in the banking industry. Banks are intensive users of both IT and financial technologies, and have a wealth of data available that may be helpful for the general understanding of the effects of technological change. The research suggests improvements in costs and lending capacity due to improvements in "back-office" technologies, as well as consumer benefits from improved "front-office" technologies. The research also suggests significant overall productivity increases in terms of improved quality and variety of banking services. In addition, the research indicates that technological progress likely helped facilitate consolidation of the industry.
Some have argued that recent increases in credit risk transfer are desirable because they improve the diversification of risk. Others have suggested that they may be undesirable if they increase the risk of financial crises. Using a model with banking and insurance sectors, we show that credit risk transfer can be beneficial when banks face uniform demand for liquidity. However, when they face idiosyncratic liquidity risk and hedge this risk in an interbank market, credit risk transfer can be detrimental to welfare. It can lead to contagion between the two sectors and increase the risk of crises.
We describe some of the main features of the recent vintage macroeconomic models used for monetary policy evaluation. We point to some of the key differences with respect to the earlier generation of macro models, and highlight the insights for policy that these new frameworks have to offer. Our discussion emphasizes two key aspects of the new models: the significant role of expectations of future policy actions in the monetary transmission mechanism, and the importance for the central bank of tracking of the flexible price equilibrium values of the natural levels of output and the real interest rate. We argue that both features have important implications for the conduct of monetary policy.