M.Com. Previous, 2019-20
Basic Quantitative Techniques and their Applications in Banks
1. Need and Importance of Quantitative Techniques in Bank management and
decision-making
Background
Numbers can be very complex, yet one can simplify them too. Given a large amount of
numbers, one might find it an almost impossible task to make sense of them. Despite
being difficult to understand, numbers are very important for getting a simple and clear
picture of what is going on around us. Numbers are everywhere. Your age, your mobile
number, your bank balance, your salary, your wealth, your expenses, and the list goes
on. Numbers become particularly important when you are dealing with a company or
institution that sells and purchases money itself! Banks are one of them.
Lot of numbers are produced in the day-to-day business of banks. These
numbers are a result of people purchasing, selling, intermediating and regulating the
various financial services and products supplied by banking companies. Purchasers of
banking products, for example, might be interested in knowing the interest rate that the
Banks are offering, the penalties that might be levied if their monthly balances fall short
of the minimum required balance, the fees and additional charges that banks might
charge for various services such as sending SMS alerts, and a whole lot of other
information which are essentially numeric in nature. Sellers of banking services might
be interested in knowing the day-to-day liquidity position of the bank branch, the latest
monetary policy rates, the number of daily transactions, and information on clearing of
inter-bank transactions, among lot of other information which, just like in case of the
purchaser, is numerical by definition. Those who act as intermediaries between banks,
between the banks and its final customers, between the banks and its share-holders
(basically the principal-agent issue), etc. might be interested in getting information about
the differences in earnings from their various alternative customers, the spread, the net
interest margin, various financial ratios, and much more other quantitative information.
The regulators of the banking industry will certainly be holding their microscopes on the
daily financial health of the banking sector by collecting information on the changes in
reported non-performing assets across banks, the ability of scheduled commercial
banks to meet the statutory requirements such as Cash Reserve Ratio (CRR), the level
and growth of the economy, the upward pressures on inflation, transactions occurring in
the inter-bank market, the level and behaviour of Stock market indices such as
SENSEX, NIFTY, etc., and many other such information that is essentially numerical in
nature.
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1.1. Some Introductory Ideas
- Transforming information into variables and thereafter analyzing them.
- Numerical data versus non-numerical data in the management of banks and policymaking
Information and Reporting in Banks
- Production of data through the day-to-day operations of banks.
- Different frequencies of data produced in and across banks [daily, weekly, fortnightly,
quarterly, bi-annually, annually and with higher and even lower frequencies].
Case Study 3: Byculla, Mumbai, Reserve Bank of India Office and daily reporting
of statutory compliance data by banks in India
1.2. Management Information System (MIS) in banking and bank-level decision
making
- Concept of MIS.
- Need for MIS in banks.
- Increasing amount of data in banks.
- Increasing size and complexity of banking data.
- Continuous dynamic changes in the external environment facing banks.
- Standardization of information and data in and across banks [operational and policymaking angles].
- Centralization of information and data in and across banks [operational and policymaking angles].
Case Study 4: Information Technology in Indian Banking Industry
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1.3. Variables used in decision-making and policy formation by banks and
regulators
- Illustrations of variables across the entire bank’s decision-making chain.
- 2018 Suresh and Paul, Pages 82-105, Pearson Publications.
1.4. Basic Quantitative Technique Tools useful in both the day-to-day and long
term operations and performance of banks
- Averages, Deviations, Variability, Correlation, Regression, Time Series Forecasting,
etc. along with illustrations.
1.5. Flow of Information and Data across banks
- Different kinds of Data are produced across the organization structure of a banking
firm. These data flow both vertically and horizontally in and across banks and to the
regulators.
Case Study 5: Flow of Information across the Organizational Structure of Union
Bank of India and the Bank of Baroda
1.6. Need and Importance of Quantitative Techniques in Bank management and
decision-making
A natural question that arises at this point is when does an information become data? If
you go to a bank branch to open a savings bank account and enquire about the interest
rate that the bank is offering as of now, the number that you get is not only information,
but also data. However, if the bank’s branch manager comes to you and offers you her
job because she is unhappy with the regional manager and her branch’s employees,
well, that is not data but information for you. It is information and not data because it
does not serve your purpose. The information that you receive should be able to help
you in fulfilling your immediate and future goals/targets/aims if it is to be considered
data. If not, then it is simply a piece of information, nothing more than that. However, if
you were looking for a job in banking sector when the manager approached to offer you
her job, well congratulations, you have data, and you are now employed! Since a lot of
information is produced in and around banks, as a student of banking (and insurance)
you must master the art of differentiating between information and data. Not all
information thrown at you will need any further analysis. Your colleagues in bank who
are jealous of your promotion may try to put you down by doubting your abilities, but if
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your aim is to focus on your work and deliver results, those events are just information.
No further analysis is needed. However, if you are a process auditor and want to
understand the work culture of the bank branch, then those gossips in break times
among you and your colleagues might be useful for you. In other words, what was
useless earlier might become data for you.
Why then should you be worried about learning quantitative techniques as
students of banking and insurance? For one, you cannot afford to ignore numbers when
you get a job or become an entrepreneur in financial sector. Numbers will help you
make sense of the good and bad going around in the financial system and your
sector/industry in particular. It will help you to take logically good decisions so that you
perform well as an employee or entrepreneur or a banking intrapreneur. For example,
as an assistant branch manager, or a branch manager, you will be able to quickly
forecast what might happen in your branch if the RBI raises the CRR. This will make
you a proactive thinker who remains well-prepared in any unseen event. Having a good
base in Quantitative Techniques might make you a better bank employee as you will be
able to understand the requirements of your banks, customers and other stakeholders.
By observing and analysing various numbers associated with your bank’s customers,
you might find it easy to make customized sales pitch to your prospective customers. If
you are employed in the risk management division, then you will be able to make
efficient models that describe the risk environment facing your bank.
The question that you should ask trying to understand the need and importance
of Quantitative tools and techniques in banking is “how will data and its analysis
improve bank-level decision-making and policy-formation?
As you appreciate by now, a banker has to deal with lot of information on daily
basis. While the Management Information System (MIS) as adopted in a bank helps the
banker to collect and organize data properly, the analysis, interpretation and contextual
significance of the collected data has to be undertaken by the banker herself. MIS or for
that matter any other software/technology cannot undertake the analysis and
interpretation of data for a banker. Quantitative Techniques help a banker to make
sense of the numbers generated due to the daily operations of a bank. These
techniques help a banker to make meaningful policy suggestions for the bank. The
policy-makers in the Reserve Bank of India (RBI), Securities and Exchange Board of
India (SEBI), and other important regulatory authorities make use of the techniques
learnt in this Unit for finding patterns, trends, inter-relationships, broad links and other
dimensions of the detailed data sets that banks generate on frequent basis.
The major need and importance of Quantitative Techniques for bankers can be
analyzed as below [PREPARE EACH TOPIC IN DETAIL AS PER YOUR CLASS
NOTES AND OTHER READINGS]:
1. Preparing Reports on bank-level operations.
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2. Undertaking scientific decision-making on bank-related issues.
3. Undertaking Statutory Compliance and reporting the same.
4. Communicating detailed data in summarized form to superior authorities of a bank.
5. Influencing the monetary and other policy-makers.
6. Increasing Efficiency in handling data.
7. Finding patterns that are not directly observable in tabulated data.
8. Testing various hypotheses for better policy-formation in banks.
9. Others.
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