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The Empirical Economics Letters, 18(3): (March 2019) ISSN 1681 8997
Disruptive Technologies and its Effect on the Workforce in
Banks: A Framework of Assessment for Mitigation
Neha Chhabra Roy
Narsee Monjee Institute of Management
Bangalore, India
Email: neha.chhabraroy@nmims.edu
T. Viswanathan
Symbiosis Institute of Business Management
Bengaluru, India
Abstract: The Banking Industry has been going through a rapid transformation
due to the fast pace growth in technology. The advent of disruptive technologies is
changing the competitive landscape of the banking industry. Banks embrace new
technologies to bring process improvements, cost optimization and to provide
value-added services. While investment in technology is inevitable, banks need to
prioritize the challenges of adopting new technologies. The technology
transformation in the banking industry poses significant challenges to its
workforce. This study is to examine and assess the impact of technological
disruptions on the workforce of banks in India. The fuzzy logic theory is used to
create Workforce Challenge Index for banks, and their respective risk category
classes are defined in sequence. The study proposes a conceptual mitigation model
that shows the interaction of workforce challenging factors, assessment of
identified challenges and mitigation measures.
Keywords: Workforce Challenges; Technical disruptions; Mitigation Measures;
Workforce Challenge
1. Introduction
The present era of banking is marked with digital revolution leading to the rapid growth of
technologies. The new generation of financial technology startups is unbundling the
banking model, providing smooth customer interface1 and facilitating banking services2. In
the pursuit of sustainable growth and to address competition, banks are embracing new
technology and redefine the ways of servicing customers. The technology transformation
has made a gradual shift from brick and mortar system to technology-enabled services that
need less human intervention. Now the question arises though positive aspects of
technological innovations are evidenced, but does the banking industry is growing with
technological developments or is it affected by disruptions also?
1Customers are embracing mobile and digital technologies for banking at one touch
2Ranging from money transfers, loans, mobile wallets etc
The Empirical Economics Letters, 18(3): (March 2019) 268
It is not hyperbole to say that 2018 is set to be one of the most exciting and potentially
transformative years for the banking industry since 2008, as open banking regulations,
technological reforms come into force across the globe. 3 The world banking is evidencing
the pros and cons of technology Developments,and disruptions in this race developing
nations are playing a pivotal role. Among all developing nation’s banking business is
growing with leaps and bound with recordaverage growth rate of 12%, whereasone of the
dominant player in this series with significant growth of 7% inIndia.
Since Indian Banking is in the midst of the Technology evolution, which is not only
advantageous but also creates disruptions The challenges faced by banking sector due to
technological development has been witnessed from decades in developed and developing
economies. The innovations in banking business affect various verticals to name a few
operations, functional domains, workforce,etc. In the search for differentiation and drive to
digitize the industry’s value chain, the nature of banks’ work is changing—along with the
skills required to deliver those services. That is particularly true for front-office and
information technology (IT) personnel.
The workforce is a backbone of any business growth aspects. While human invents
technology for the betterment of work, excessive invent of superior technology would lead
a war between technologyvs. humanity. Banks are now exposed to the dichotomy of
balancing technology adoption vs.workforce management. Therefore identifying
variouschallenges of the workforce due to technical disruptions is an essentialarea of
concern. In this backdrop, the questions arise are Indian banking business affected
bytechnological disruptions? How technical disruption affect workforce of Indian banking
business? What is the exact impact of technical disruption on banking employees? What
could be the feasible mitigation measures to reduce workforce challenges? The Central
argument to the paper revolves around identification, assessment, and mitigation of
workforce challenges. The objectives of the study are to identifythe various technical
disruptions to Indian banks, diverse workforce challenges about technological
disruptions and assess the impact of identified challenges and compute the Workforce
Challenge Index (WCI) for banks.
To elucidate these objectives, the organization of the paperisasfollows. Section 2 gives a
brief about technological development. A literature review is discussed in section 3,
the methodology of this research study is provided in Section 4. Section 5 presents the
analysis of the data, where features/observations of the analysis are discussed with the
classification of risk class across various projects. Section 6 discusses the mitigation
measures. The concluding observationsare presented in Section 7.
3http://www.ey.com/in/en/industries/financial-services/banking---capital-markets/ey-banking-on-
technology-india-banking-industry
The Empirical Economics Letters, 18(3): (March 2019) 269
2. Technical Disruptions for Banks
The banking sector has seen significant changes in 2017. Today, with a mobile app, users
in developing countries, can deposit and withdraw money, check account balance, pay
bills and take loans. The landscape of banking sector is facing disruption from new
financial technology-based companies as, the applications are experiencedin the U.S.,
where companies like Affirm, Lending club, prosper, Acorns are helping customers buy
more by offering simple installment plans, invest and accept capital with a mobile app,
invest their pocket change. 4 These disruptions in the fintech industry can be found in all
parts of the world and all financial sectors from insurance to asset management and
savings.The growth in fintech disruption has been helped by the customer expectations,
venture capital funding, ease of entry into the industry, and the pace of technological
evolution.(Türkmen and Değerli, 2015).
The paradigm of the financial world had changed when digitalization gave the banking
industry its first technological breakthrough.While digital disruption has an increasing
impact on banking industries, digital native generations are set to invade the professional
world, and thus add to the volume and variety of digital habits and behavior. When
combined with the booming use of internet and smartphones in emerging countries, there
is a lever effect, which consequences are difficult to anticipate for traditional financial
institutions who are not ready or agile enough to adapt. Figure 1 shows the technical
advancement of India banks which lead to disruptions.
Figure 1: Technical Advancements in Indian Banks leading to disruptions
Source: Prepared by Authors to compile information from various sources).
4https://financefeeds.com/banking-and-fintech-in-2018-disruption-and-technological-evolution/
Major technological
disruptions for Banking
Industry
Digitisation
Financial
Technologies
Data Analytics
Block Chain
Artificial
Intelligence
Cyber Security
The Empirical Economics Letters, 18(3): (March 2019) 270
Performance, profitability, and risk-reduction are the primary goals which banking and
financial sectors strive to achieve. In this data-driven world, performance is dependent on
those big data technologies which can store and manage semi-structured and unstructured
data in real time. Banks are finding it a little hard to comply with all of the local
governmental regulations. Sometimes the banks have to provide loans at a lower interest
rate to specificvital sectors like agriculture, housing, education. BFSI companies have
been optimizing operations across all functions because their aim to improve efficient
systems, enhance service-delivery models and customer engagement, and protect its
systems against cyber threats.5 For human resource management linked to data analytics
banks has to prepare for varied delivery models, varying skill set based on target job, and
training should be varying linked to the skill of associated candidates,(Resources, 2017).
The financial sector has been at risk for cybersecurity attacks since the inception of the
Internet, where this risk has increased in the past several years due to rapid changes in
computer hacking technology. Bot attacks rose significantly globally in 2015, resulting in
a 40% increase in attacks during 2015– and a record 45 million attacks in the last three
months of 2015. 6 Industry experts believe that between 2 million and 6 million jobs will
be lost over the next decade due to disruptive financial technologies like Artificial
Intelligence (AI) and blockchain. A report by Citigroup revealed that the downsizing of
the bank workforce is about to accelerate as more technology takes over jobs humans used
to do.7 Aggregating all these above discussed technological innovations work as
disruptions for banking business, aggregating all these technical disruptions,i.e.blockchain,
artificial intelligence, cyber security absorbed in banking business leads to suffering in
multiple dimension of the banking business. The primary areas which are affected in
banking business due to technical disruptions to name a few are operational, functional,
strategy and most importantly is workforce.
3. Technology Disruptions and Workforce Challenges
The rapid progress in technology is bringing a paradigm shift to the banks concerning
technology adoption and transformation. The leading trends in the banking industry are
digitization, mobile banking, data analytics, cyber security and partnership with fintech’s,
open API and blockchain. These disruptive technologies are forcing banks to relook at
their technology portfolio, operating mechanism,and service delivery models. These
waves of new technologies are poised to reinvent the workforce in the banking industry.
5https://intellipaat.com/blog/8-reasons-bfsi-is-betting-big-on-data-analytics/
6http://businessworld-usa.com/todays-cyber-security-threats-to-the-financial-sector/
7https://businesstech.co.za/news/industry-news/209135/30-of-banking-jobs-threatened-by-ai-and-
blockchain/
The Empirical Economics Letters, 18(3): (March 2019) 271
ATMs will perform the job of tellers, Chabot’s replace customer care executives,
Blockchain and artificial intelligence reduce the need for branch banking.
Banks need a proactive approach to encash the benefits of technology and manage the
aspirations of the employees. The workforce challenges are not only concerned withthe
business but from societalaspect as well, so focus on this area is a significant concern.
While talking about workforce challenges (Goldberg, 2009) (Cheung and Kaymak, 2008)
mentioned the advent of IT had shifted the traditional bankingto technology-driven
modern banking. The abrupt implementation of technology-enabled processes such as
Core banking solution, Internet and mobile banking and branchless banking has created
the need for specific IT skills. As a repercussion, it has created a skill gap among the
employees especially the traditionalists, baby boomers and Gen x to some extent.
Another challenge which is growing with the increased number of banking products and
their complexity requires an emerging skill set for bank employees and advance business
models.Public sector banks (PSB’s) would be required to recruit and use a large number of
specialists in a variety of areas like Risk Management, IT, HR, Treasury, Forex, etc.;
acquiring and retaining such specialist resource will be a major challenge for the PSBs
(Siraj and Pillai, 2013).
Tobridge this gap employees with continuum focus on skill development and
transformation. Complicacy and intricacies of understanding new process and acquiring
skill mostlyarea lengthy and time taking process, which affects existing work allocated to
employees and have a parallel effect on banking business. In the process of skill
transformation and development employees look for support from bank management and
senior officials which is lagging creating another challenge for the workforce.(Swider and
Weber, 2005).
Another aspect which was observed by (Singh, 2012) has focused on the compensation of
employees8; recently per employee cost for public sector banks have nearly doubled in the
five years between 2007 and 2017; reduction of this cost increases reliability on
technovation, in this process few skilled employees are always being a great contributors
who are adaptable to advance practices with their existing workload via putting ample
efforts get acquainted with advances but due to structured payment mechanism in banking
business, despite having advance skills employees are not recognized with adequate
compensation, which reduces morale for further up gradations.Structured payment system
and deficiency of skill-based compensation create a challenging environment for the
workforce to work with zeal.
8 In private banks, only 21 per cent of the nearly 300,000 employees fall in the category of clerks.
The Empirical Economics Letters, 18(3): (March 2019) 272
One of the weakest links in the HR policies of banking employees is career planning,
which leads to trouble without proper awareness about their respective career and the same
mindset works reluctantly to adopt new changes.(Henry, 2014)Compliance with work and
sufficient time delivery pressurize workforce to deliver things on time even with partial
understanding make delivery of project questionable (Rani and Garg, 2014).
Adequate training needs as per employee strength, and timely training exposure is need of
workforce in the advent of technology in the banking business. Employees felt the training
which is provided to employees, mostly lags experienced trainers or content of training.
Even, it was also observed that training sometimes is misleading and deviates from the
exact work domain.The training effectiveness is also not been measured after completion
of training would not support effectively to human resource.
With rapid changes taking place in the financial landscape, Scheduled Commercial banks
in India need a new generation of professional bankers who are more customer-centric,
technology-savvy, more highly qualified, flexible and agile with behavioral skill sets that
are now more comprehensive than previously. The quality of human capital will
increasingly become the cutting edge of competitiveness. Therefore, banking institutions
are interested to ensure competency and professionalism to serve their customers better.
Technology has brought substantial changes in banking regarding customer services and
new product innovations. The private sector banks are more dynamic in adopting latest
Human Resource Practices.The banking sector hasrealized the fact that in the changed
scenario, success will depend on the ability of banks to leverage the human potential and
capabilities. The competency approach to human resources management is based on
identifying, defining and measuring individual differences regarding the abilities that are
vital for the successful job performance.Work management embossed as another
challenging area where with existing jobs, first getting an understanding ofadvanced areas
and further experiencing impacts on existing work plan.
4. Methodology
The focus region for the case study is Indian public and private sector banks, An
exploratoryresearch designisusedtoidentifytechnical disruptions,and subsequent, workforce
challenges identification, set of key risk factors are identified through literature review, and
those risks got validated through semi-structured first discussion using an open-ended
questionnaire with 40 bank officials. (average experience between 5-15 years including
retired, executive, clerical who are administering the banking business). Challenge
assessment in which mostly qualitative risk factors are addressed, the assessmentwas
performed with the methodology used by (Kucukali, 2011; Roy and Roy, 2015) fuzzy
The Empirical Economics Letters, 18(3): (March 2019) 273
logic theory9 ( FLT). In this theory firstly through fuzzification, these personal risks
factors are converted into quantitative numbers,and again through defuzzification, a risk
class for each project has been estimated.
The personal risk was converted to well-designed, expert opined, administered the
primarysurvey using structuredquestionnaire, which addresses the severity of each
factor on the Likert scale of 1(very low) to 5 (Very High). Judgmental sampling was
used to send a questionnaire to who directly deal with banking business across India of10
different banks (5 public sector and 5 Private Sector banks) operating across
India,during September 2017andFeb 2018;banks are identified based on their market
capitalization and asset base considered for this study. As on September 2017, the top 5
public and private sector banks mapped while comparing their market capitalization and
asset base after attentive data extraction, deduplication and data validation and cleansing
technique over the response of 685 individuals, 635 respondents are considered for
analysis of the study.
5. Data Analysis
Potentialchallengesassociatedwith Indian banking sector workforce pertains to technical
disruptions are identified through literaturereview and were finalized with experts opinion
are categorized significant areas. The major factors wereskill deficiency, ample time for
skill transformation, skill-specific allowances, structured compensation mechanism;
training exposure; job role compliances; career planning, competency limitations and
performance management support from bank officials. In each area theme, there are sub-
risk variables present are represented in table 1.
The current practices which are handling workforce challenge assessment arethe mostly
qualitative approach the very first time using this approach any study is found in which the
assessment of workforce challenges is based on the quantitative assessment. Since all
these factors are intangible so usually quantification is less to be observed. For
quantification of these challenging factors, discussed in methodology segment FLT has
been used where firstly responses of all respondents are assessed mentioned in Table 1.
9FuzzyLogictheorydealswithallqualitativeandsubjectivefactorsquantificationsusingBooleanlogic.
Fuzzy Logic Trapezoid method isused in this paper for assessment. This method allocates more
weights towards high responses and less towards fewer responses. The fuzzy logic approach to risk
assessment takes part in both sides of expert and experimental categories as it both involves
professional/expert and public perception participation in the methodology
The Empirical Economics Letters, 18(3): (March 2019) 274
Table 1: Technology related Workforce Challenges assessment
Assessment
Factor
Assessment variables
No of
1’s
No of
2’s
No of
3’s
No of
4’s
No of
5’s
Total
Respon-
dents
Weighted
Sum
Weighted
Average
Rating
(Ri)
Weight(w)=
Rating
(Ri)*weighted
average
Normalized
Weights
Cumulative
Factor
Weight
Skill Based Pay
skill based compensation
24
124
131
203
153
635
1836
2.891
0.1
0.289
12.18%
12.18%
Training
Exposure
Training Effectiveness
165
268
106
70
26
635
1289
2.03
0.033
0.068
2.85%
9.53%
Training needs
123
150
250
74
38
635
1511
2.38
0.033
0.079
3.34%
Training support
91
230
171
90
53
635
1509
2.376
0.033
0.079
3.34%
Work
management
Work efficiency
242
266
81
39
0
628
1095
1.744
0.05
0.087
3.67%
8.27%
Work life balance
171
180
130
101
53
635
1388
2.186
0.05
0.109
4.60%
Redefining Job
roles
Adequacy
112
211
189
106
17
635
1398
2.202
0.05
0.11
4.64%
10.56%
preparedness
27
128
185
176
119
635
1785
2.811
0.05
0.141
5.92%
Flexible
Recruitment
Structured Approach for
recruitment planning
120
174
123
167
51
635
1426
2.246
0.1
0.225
9.46%
9.46%
Skill Deficiency
Skill Development
99
179
189
111
57
635
1531
2.411
0.1
0.241
10.15%
10.15%
Career
planning
Career progression
19
57
68
309
182
635
1865
2.937
0.05
0.147
6.18%
12.01%
planning during Job
Reduction
38
71
80
298
148
635
1756
2.765
0.05
0.138
5.82%
Performance
Management
support from
bank
management
Transparency
153
193
136
78
68
628
1443
2.298
0.05
0.115
4.84%
9.32%
KRA's
157
288
111
37
42
635
1350
2.126
0.05
0.106
4.48%
Competency
Mapping
Competency Building
strategy
130
283
142
43
37
635
1393
2.194
0.1
0.219
9.24%
9.24%
Time for Skill
Transformation
Skill Ugradation
100
271
126
94
44
635
1428
2.249
0.05
0.112
4.74%
9.30%
Skill Development
139
261
139
61
35
635
1375
2.165
0.05
0.108
4.56%
2.374
100.00%
The Empirical Economics Letters, 18(3): (March 2019) 275
6. Result
For factor impact assessment, relative weight for each factor was estimated after
normalization of each risk factor (fig 3). Top three prominent risk areas have come out as
skill-based pay, compensation, career planning and adaptability to change based on
respondents responses. The weights are used further for workforce challenge index
computation, where the area under the curveforeach risk factor was used to check the
impact of Risk Index presented in Table 2. The Risk Index estimated in this study comes
out as 2.1145 which show high impact.
Figure 2: Workforce challenges and respective impacts
12.18%
2.85%
3.34%
3.34%
3.67%
4.60%
4.64%
5.92%
9.46%
10.15%
6.18%
5.82%
4.84%
4.48%
9.24%
4.74%
4.56%
12.18%
9.53%
8.27%
10.56%
9.46%
10.15%
12.01%
9.32%
9.24%
9.30%
skill based compensation
Training Effectiveness
Training needs
Training support
Work efficiency
Work life balance
Adequacy
preparedness
Structured Approach for recruitment planning
Skill Development
Career progression
planning during Job Reduction
Transparency
KRA's
Competency Building strategy
Skill Ugradation
Skill Development
Comp
ensati
on to
meet
advan
ceme
nts
Training Exposure
Work
management
Employee
Adapatbility
to change
Comp
ensati
on
Mana
geme
nt
Skill
Defici
ency
Career
planning
Performance
Managemen
t
Comp
etenc
y
Skill
Transformat
ion
F A CT OR S C R E ATI NG WO RK F O R C E C HA LLE NG ES I N B AN K I N G
B U SI NE S S & I TS I M P A CT
Cumulative Weights
(Relative weights)(wr)
The Empirical Economics Letters, 18(3): (March 2019) 276
Table 2: Workforce Challenge Index estimation
Assessment
Factor
Assessment
variables
Relative
weights
Cumulative
Weights
score
Unity Matrix
AF=I * RF
AF matrix
MD=
wr* AF
Membership Degree Matrix (MD)
1
2
3
4
5
1
2
3
2
5
1
2
3
2
5
Skill specific
allowances
skill based
compensation
12.18%
12.18%
2
0
1
0
0
0
0.8
1
0.5
0.2
0
0.0974
0.1218
0.0609
0.0244
0.0000
Training
Exposure
Training
Effectiveness
2.85%
9.53%
5
0
0
0
0
1
0
0
0.2
0.4
1
0.0000
0.0000
0.0057
0.0114
0.0285
Training
needs
3.34%
4
0
0
0
1
0
0
0
0.6
1
0.4
0.0000
0.0000
0.0200
0.0334
0.0134
Training
support
3.34%
3
0
0
1
0
0
0
0.5
1
0.5
0
0.0000
0.0167
0.0334
0.0167
0.0000
Work
Management
Work
efficiency
3.67%
8.27%
3
0
0
1
0
0
0
0.3
1
0.7
0
0.0000
0.0110
0.0367
0.0257
0.0000
Work-life
balance
4.60%
4
0
0
0
1
0
0
0
0.9
1
0.1
0.0000
0.0000
0.0414
0.0460
0.0046
Job Role
Compliances
Adequacy
4.64%
10.56%
5
0
0
0
0
1
0
0
0
0.6
1
0.0000
0.0000
0.0000
0.0278
0.0464
preparedness
5.92%
4
0
0
0
1
0
0
0.2
0.5
1
0
0.0000
0.0118
0.0296
0.0592
0.0000
Compensation
Management
Structured
Approach
for
payments
9.46%
9.46%
5
0
0
0
0
1
0
0
0
0.4
1
0.0000
0.0000
0.0000
0.0378
0.0946
Skill
Deficiency
Skill
Development
10.15%
10.15%
3
0
0
1
0
0
0
0.6
1
0.7
0
0.0000
0.0609
0.1015
0.0711
0.0000
The Empirical Economics Letters, 18(3): (March 2019) 277
Table 2 continued
Career
planning
Career
progression
6.18%
12.01%
2
0
1
0
0
0
0.4
1
0.5
0
0
0.0247
0.0618
0.0309
0.0000
0.0000
planning
during Job
Reduction
5.82%
4
0
0
0
1
0
0
0
0.6
1
0.5
0.0000
0.0000
0.0349
0.0582
0.0291
Performance
Management
support from
banks
Transparency
4.84%
9.32%
2
0
1
0
0
0
0.6
1
0.5
0
0
0.0290
0.0484
0.0242
0.0000
0.0000
KRA's
4.48%
3
0
0
1
0
0
0
0.8
1
0.6
0
0.0000
0.0358
0.0448
0.0269
0.0000
Competency
limitations
Competency
Building
strategy
9.24%
9.24%
4
0
0
0
1
0
0
0
0.5
1
0.6
0.0000
0.0000
0.0462
0.0924
0.0554
Time for Skill
Transformation
Skill
Ugradation
4.74%
9.30%
5
0
0
0
0
1
0
0
0
0.9
1
0.0000
0.0000
0.0000
0.0426
0.0474
Skill
Development
4.56%
4
0
0
0
1
0
0
0
0.4
1
0.3
0.0000
0.0000
0.0182
0.0456
0.0137
0.0148
0.0304
0.0361
0.0367
0.0194
The Empirical Economics Letters, 18(3): (March 2019) 278
Figure 3: Membership Degree Vs. Weight Curves for challenge weight Estimation
The Attribute values ranging from 1 to 5 signify the value of the assessment, pictorial
representation between weighted averages vs. attributes histograms show that high
weighted average on attributes (e.g., Attributes 4 or 5) reflects a high-challenge
assessment (high rating) value, curves kewed to Right-hand side reflects high-risk value.
The asymptotic significant, two-tailed) level was 0.882 when all WCI values were
checked together and individually, which were greater than 0.05. (Table3) Risk Index
(WCI) value to be establishing a 5 grade evaluation scale where based on WCI value:(a)
Low risk (2-2.10); (b) Medium Risk (2.10-2.13); (c) Highimpact (2.13-2.15); (d) Very
high risk (2.15-2.30); and (e) extreme (2.3-3.0).
Table 3: WCI index and respective risk class classification
Bank name
WCI
Index
K Value10
Cumulative
Frequency11
Z score12
Risk Class
Axis Bank
2.159
1
0.95
1.2886
High
SBI
2.153
2
0.85
1.1117
High
PNB
2.134
3
0.75
0.5514
Natural Average
Canara Bank
2.13
4
0.65
0.4335
Natural Average
Yes Bank
2.125
5
0.55
0.2860
Moderate
Kotak Mahindra
2.124
6
0.45
0.2565
Moderate
Central Bank
2.11
7
0.35
-0.1563
Moderate
HDFC Bank
2.088
8
0.25
-0.8050
Low
Bank of Baroda
2.08
9
0.15
-1.0409
Low
ICICI Bank
2.05
10
0.05
-1.9256
Low
10 K is the order of WCI values in descending form ( Table 3) and n is total number of selected banks
11𝐹=𝑛−𝑘 +0.5
𝑛
12𝑍 𝑠𝑐𝑜𝑟𝑒 =𝑊𝐶𝐼 −𝐴𝑣𝑒𝑟𝑎𝑔𝑒 𝑜𝑓 𝑊𝐶𝐼
𝑆𝑡𝑎𝑛𝑑𝑎𝑟𝑑 𝐷𝑒𝑣𝑖𝑎𝑡𝑖𝑜𝑛 𝑜𝑓 𝑊𝐶𝐼
0.0148
0.0304
0.0361
0.0367
0.0194
0.0226
0.0333
0.0364
0.0281
0.1203
0.0000
0.0200
0.0400
0.0600
0.0800
0.1000
0.1200
0.1400
1
2
3
4
5
MDM/Weights
Score
M E M BE RSH IP D EG REE V S W E IGH TS C U R V E
Weights
Membership Degree Matrix
The Empirical Economics Letters, 18(3): (March 2019) 279
Figure 4: Framework for technology disrupted Workforce Challenges Mitigation
8. Conclusion
The influence of technology in banking has changed the fundamentals of the banking
business model and the nature of work. The industry that has been one of the largest
Technological
Disruptions
Identification of
banking system
Workforce Challenges
driven through
technological Disruption
Assessment of
Identified workforce
challenges
Index Estimation
Workforce
Challenge
Index (WCI)
(2.114)
Skill
Deficiency
Career
Planning
Performance
Management
support from bank
management
Time for Skill
Transformation
Work
Managemen
t
Training
Exposure
Competency
limitations
Compliant
job role
Structured compensation
mechanism
Lack of Skill
based
allowances
Career Planning
(12%)
Compliant Job
role (10.56%)
Skill Deficiency
(10.15%)
Training
Exposure
(9.53%)
Performance Management
support from bank
management (9.32%)
Lack of Skill
Transformation
(9.3%)
Skill Based
Compensation (12.18%
Structured
compensation
mechanism (9.46%)
Competency
limitation (9.24%
Work Management
(8.24%
Cyber
Security
Data
Analytics
Artificial
Intelligence
Digitisation
Block Chain
Technology
Financial
technologies
Cloud
Computing
The Empirical Economics Letters, 18(3): (March 2019) 280
employers is moving towards technology-enabled services. The emergence of Block
Chain, Robotics, and Artificial Intelligence is expected to change the basics of banking.
This progressive change in technology could undoubtedly benefit the banking industry.
At the outset, these developments provide alternative forms of banking services like
mobile wallet, peer to peer lending and other digital payment services. It is impertinent
for banks to adopt every new technology that emerges. At the same time, adopting new
technology poses various challenges related to the workforce. The depth, breadth, and
complexity of the workforce of the future for banking will bring some entirely new
challenges. Managing talent will take on a whole new dimension and require different and
innovative practices. Behavioral change needs to be embedded in managers to enable the
right cultural shifts in this rapidly changing environment. Managers must be equipped to
manage the external workforce through intermediaries or digital tool sets.
The various workforce issues laid out in this challenge also represent opportunities. By
adopting a focused and flexible workforce strategy, and developing an organization that
is customer-focused and digitally capable, an investment bank can build its brand, both
internally and externally. Creating an environment that allows for employees to create
their career brand across functions, while at the same time fostering work-life integration,
innovative work environments, opportunities for challenging work and opportunities for
advancement, is critical. Additionally, digital innovations will require the workforce to be
more diverse and agile regarding adapting to new roles over time, and banks will need to
focus on hiring those with broader skill sets. Banks will need to foster an innovative and
dynamic image to attract and retain the workers they want.
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