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Sources Of Banking Risks: Credit, Market And Operational Risks

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Sources Of Banking Risks: Credit, Market And Operational Risks

Banking risk refers to the future uncertainty which creates stochasticity in the cash flow from receivables of outstanding balances. Banking Risks can be described in the Vonn-Neumann-Morgenstern (VNM) framework of Money lotteries. In this framework, the set of outcomes are assumed to be continuous and monetary in nature, and the lottery is a list of probabilities associated with the continuous outcomes. When applied to the banking framework, the cash flows (the set of outcomes) are assumed to be continuous and stochastic in nature. A theoretical model for the risk is represented in the framework below:


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There are three broad sources from which banking risks originate: 1. Credit Risk 2. Market Risk 3. Operational Risk.

CREDIT RISK:

Credit Risk arises when the borrower defaults to honour the repayment commitments on their debts. Such a risk arises as a result of adverse selection (screening) of applicants at the stage of acquisitions or due to a change in the financial capabilities of the borrower over the process of repayment. A loan will default if the borrower’s assets (A) at maturity (T) falls below the contractual value of the obligations payable (B) (Vasicek,1991). Let A_i be the asset of the i-th borrower, which is described by the process:

MARKET RISK:

Market Risk includes the risk that arises for banks from fluctuation of the market variables like: Asset Prices, Price levels, Unemployment rate etc. This risk arises from both on-balance sheet as well as off-balance sheet items. This risk includes risk arising from macroeconomic factors such as sharp decline in asset prices and adverse stock market movements. Recessions and sudden adverse demand and supply shock also affect the delinquency rates of the borrowers. Market Risk includes a whole family of risk which includes: stock market risks, counterparty default risk, interest rate risk, liquidity risk, price level movements etc.

OPERATIONAL RISK:

Operational Risk arises from the operational inefficiencies of the human resources and business processes of an organisation. Operational risk includes Fraud risks, bankruptcy risks, risks arising from cyber hacks etc. These risks are uncorrelated across the industries and is very organisation specific. However, Operational risk excludes strategy risk and reputation risk.

This blog is the continuation of the first blog, which was on the topic – The Basics of the Banking Business and Lending Risks. To read the blog, click here ― www.dexlabanalytics.com/blog/the-basics-of-the-banking-business-and-lending-risks

Stay glued to our site for further details about banking structure and risk modelling. DexLab Analytics offers a unique module on credit risk analysis training in Bangalore.

 

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The Basics Of The Banking Business And Lending Risks:

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The Basics Of The Banking Business And Lending Risks:

Banks, as financial institutions, play an important role in the economic development of a nation. The primary function of banks had been to channelize the funds appropriately and efficiently in the economy. Households deposit cash in the banks, which the latter lends out to those businesses and households who has a requirement for credit. The credit lent out to businesses is known as commercial credit(Asset Backed Loans, Cash flow Loans, Factoring Loans, Franchisee Finance, Equipment Finance) and those lent out to the households is known as retail credit(Credit Cards, Personal Loans, Vehicle Loans, Mortgages etc.). Figure1 below shows the important interlinkages between the banking sector and the different segments of the economy:

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Figure 1: Inter Linkages of the Banking Sector with other sectors of the economy

Banks borrow from the low-risk segment (Deposits from household sector) and lend to the high-risk segment (Commercial and retail credit) and the profit from lending is earned through the interest differential between the high risk and the low risk segment. For example: There are 200 customers on the books of Bank XYZ who deposit $1000 each on 1st January, 2016. These borrowers keep their deposits with the bank for 1 year and do not withdraw their money before that. The bank pays 5% interest on the deposits plus the principal to the depositors after 1 year. On the very same day, an entrepreneur comes asking for a loan of $ 200,000 for financing his business idea. The bank gives away the amount as loan to the entrepreneur at an interest rate of 15% per annum, under the agreement that he would pay back the principal plus the interest on 31st December, 2016. Therefore, as on 1st January, 2016 the balance sheet on Bank XYZ is:

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Consider two scenarios:

Scenario 1: The Entrepreneur pays off the Principal plus the interest to the bank on 31st December, 2016

This is a win – win situation for all. The pay-offs were as follows:

 

Entrepreneur: Met the capital requirements of his business through the funding he obtained from the bank.

Depositors: The depositors got back their principal, with the interest (Total amount = 1000 + 0.05 * 1000 = 1050).

Bank: The bank earned a net profit of 10%. The profit earned by the bank is the Net Interest Income = Interest received – Interest Paid (= $30,000 – $10000 = $20,000).

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Scenario2: The Entrepreneur defaults on the loan commitment on 31st December, 2016

This is a drastic situation for the bank!!!! The disaster would spread through the following channel:

 

Entrepreneur: Defaults on the whole amount lent.

Bank: Does not have funds to pay back to the depositors. Hence, the bank has run into liquidity crisis and hence on the way to collapse!!!!!!

Depositors: Does not get their money back. They lose confidence on the bank.

 

Only way to save the scene is BAILOUT!!!!!

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The Second Scenario highlighted some critical underlying assumptions in the lending process which resulted in the drastic outcomes:

Assumption1: The Entrepreneur (Obligor) was assumed to be a ‘Good’ borrower. No specific screening procedure was used to identify the affordability of the obligor for the loan.

Observation: The sources of borrower and transaction risks associated with an obligor must be duly assessed before lending out credit. A basic tenet of risk management is to ensure that appropriate controls are in place at the acquisition phase so that the affordability and the reliability of the borrower can be assessed appropriately. Accurate appraisal of the sources of an obligor’s origination risk helps in streamlining credit to the better class of applicants.

Assumption2: The entire amount of the deposit was lent out. The bank was over optimistic of the growth opportunities. Under estimation of the risk and over emphasis on growth objectives led to the liquidation of the bank.

Observation: The bank failed to keep back sufficient reserves to fall back up on, in case of defaults. Two extreme lending possibilities for a bank are: a. Bank keeps 100% reserves and lends out 0%, b. Bank keeps 0% and lends out 100%. Under the first extreme, the bank does not grow at all. Under the second extreme (which is the case here!!!) the bank runs a risk of running into liquidation in case of a default. Every bank must solve an optimisation problem between risk and growth opportunities.

The discussion above highlights some important questions on lending and its associated risks:

 

  1. What are the different types of risks associated with the lending process of a bank?
  2. How can the risk from lending to different types of customers be identified?
  3. How can the adequate amount of capital to be reserved by banks be identified?

 

The answers to these questions to be discussed in the subsequent blogs.

Stay glued to our site for further details about banking structure and risk modelling. DexLab Analytics offers a unique module on Credit Risk Modelling Using SAS. Contact us today for more details!

 

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Introduction To Credit Score Cards: Its Use in Crisis

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The incident we are about to describe took place during 2009 circa at a party, a year in which the world was going through one of its worst financial crisis for the longest time. Every average bloke on the streets was aware of terms like mortgage-backed securities (MBS), sub-prime lending and credit crisis, after all these are the reasons for his plight.

 

Introduction To Credit Score Cards: Its Use in Crisis

 

But at this party we are speaking of, I was fortunate enough to meet with an informed and highly compassionate elderly woman, and after a few minutes of discussion the topic came to what we here do for a living. She wanted to know more about credit scorecard systems. As I further went on to explain the details of how this system works, her expression changed from being just plainly curious to angry to pained. Continue reading “Introduction To Credit Score Cards: Its Use in Crisis”

Credit Risk Managers Must use Big Data in These Three Ways

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Credit risk managers must use Big Data in these three ways

While the developed nations are slowly recovering from the financial chaos of post depression, the credit risk managers are facing growing default rates as household debts are increasing with almost no relief in sight. As per the reports of the International Finance which stated at the end of 2015 that household debts have risen to by USD 7.7 trillion since the year 2007. It now stands at the heart stopping amount of a massive USD 44 trillion and the amount of debts increased in the emerging markets is of USD 6.2 trillion. The household loans of emerging economies calculating as per adult rose by 120 percent over the period and are now summed up to USD 3000.

To thrive in this market of increasing debts, credit risk managers must consider innovative methods to keep accuracy in check and decrease default rates. A good solution to this can be applying the data analytics to Big Data. Continue reading “Credit Risk Managers Must use Big Data in These Three Ways”

Facts about Remittances for Credits and Rent Losses – Part 1

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Facts about Remittances for Credits and Rent Losses – Part 1

 

A valuation store, built up and kept up by charges against the bank’s working salary, is what we know by The Allowances for Loans and Lease Losses (ALLL). As an assessment measure, it is an evaluation of invalid sums that is utilized to decrease the book estimation of credits and rents to the sum that is relied upon to be gathered. The ALLL frames a piece of Capital of Tier-2; henceforth it is kept up to cover misfortunes that are plausible and admirable at the time of assessment. It does not work as a support against all conceivable future misfortunes; that assurance is given by the Capital of Tier 1. For building up and keeping up a satisfactory payment, a bank ought to:

Continue reading “Facts about Remittances for Credits and Rent Losses – Part 1”

Banking Business And Banking Instruments- Part 2

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Banking Business And Banking Instruments- Part 2
 

In the last blog we had discussed three types of banking instruments, namely the Current account, Savings account and Certificate of Deposit.  In this blog we discuss credit cards. Credit cards are the most expensive and profitable type of loan that a bank can extend. A credit card is a card issued by a financial institution giving the holder an option to borrow funds, usually at points of scales. Credit cards charge interest and are primarily used for short-term financing. Interest usually begins one month after a purchase is made and borrowing limit is pre-set according to the individual’s credit rating. Credit cards have higher interest rates than most consumer loans, or lines of credit.

Continue reading “Banking Business And Banking Instruments- Part 2”

BASEL Accords: A Basic Understanding

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BASEL accords are a set of agreements set by the Basel Committee on Banking Supervision(BCBS) which provides recommendations on banking regulations in regard to credit risk, market risk and operational risk. The purpose of the accords is to ensure that the financial institutions have adequate capital on account to meet obligations and absorb unexpected loss. There are three versions of BASEL: BASEL-I, II and III. BASEL-I is relatively more simple compared to the later versions, in the sense that, its scope of definition of risk was limited only to credit risk. BASEL-II is a more advanced version of its predecessor in defining the scope and domain of banking risk. It points out three main areas of risks: Minimum Capital Requirements, Supervisory Review and market discipline. These are called the three pillars of BASEL. The focus of BASEL-II has been to strengthen the international banking requirements as well as to supervise and enforce these requirements. BASEL-III is the recent most version of the BASEL accords and most banks seeks compliance with it by the end of 2018. BASEL-III discusses the three pillars professed by BASEL-II in a more detailed manner by increasing the scope of the three pillars. In this blog we will discuss the three pillars of BASEL accords and the opportunities they generate in the analytics industry.

Pillar 1: Minimum Capital Requirements

BASEL-II emphasises that banks must have adequate capital to cover the three areas of risk exposure: Credit risk, Operational Risk and Market Risk. Credit risks are those which arise from the default on the loans made to obligors. The default occurs when obligors fail to make required payments. Operational Risk arises from failed internal processes. It includes legal risk, but excludes strategic and reputation risk. Market risks arise from losses on and off balance sheet position arising from movement in market prices. Statistical models are extensively used to develop predictive models for identifying the credit, operational and market risks. Probability of Default (PD), Loss given Default (LGD) and Exposure at Default (EAD) models are built to identify the inherent credit risk in the bank’s portfolio. Market risks are modelled using Value at Risk (VaR) and Economic Capital (ECAP) models. Building these models require a sound understanding of (i) the relevant business for which model development is done (ii) statistical techniques like Logistic Regression, Linear Regression, Time Series Analysis (both basic and advanced) (iii) segmentation techniques like CHAID, CART, Cluster analysis etc. and (iv) a very good understanding of soft wares like SAS, EXCEL and R.

Pillar 2: Supervisory Review

It provides with a framework to deal with risk related to systemic, pension, strategic, concentration, liquidity, legal and reputational. The accord combines all these risks under the title of residual risk. The aim of this pillar is to give better tools to the regulators. Black-Scholes-Merton of option pricing forms the basis of modeling for most of these risks (especially systemic risks). In order to develop this type of model you are required to have sound knowledge in terms of simulation Stochastic processes.

Pillar 3: Market Discipline

Market discipline supplements regulation as sharing of information facilitates assessment of the bank by others, including investors, analysts, customers, other banks, and rating agencies, which leads to good corporate governance. The aim of Pillar 3 is to allow market discipline to operate by requiring institutions to disclose details on the scope of application, capital, risk exposures, risk assessment processes, and the capital adequacy of the institution. It must be consistent with how the senior management, including the board, assess and manage the risks of the institution.

Banks require being compliant with all the three pillars of BASEL accords for prudently managing their risks. Hence Systematically Important Financial Institutions like Wells Fargo, HSBC, American Express, Bank of New York Mellon etc. look for resources with sound understanding of these pillars and the statistical knowledge required building models for their captive risk management process. Managing banking risk is perhaps the safest business to invest in as the extent of risks and regulatory compliance for banks are increasing overtime. Over the next few blogs we will try to understand the capital structures of banks and development of different BASEL compliant models for different pillars and capital tiers of banks.

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