1. CREDIT RISK MEASUREMENT
AND RISK MITIGATION
Date:17/03/2016 Presented By: Barendra Ku Bisoyi

2. CREDIT RISK:
Definition: Credit risk is most simply defined as the potential that a
bank borrower or counterparty will fail to meet its obligations in
accordance with agreed terms.
 The goal of credit risk management is to maximise a bank's risk-
adjusted rate of return by maintaining credit risk exposure within
acceptable parameters.
 When bank lend money they are expose to credit risk.
 If too many peoples default in returning money then the bank may
face problem.
 Example: Vijay Malaya's company kingfisher airlines default to
returning the money so banks face problem because the lending
money is very high. Similarly if two three more big organizations
default to returning the money then the bank may face problem.

3. TYPES OF LOAN:
 Inter bank loan: If bank lend to another bank for a specified term is
known as inter bank loan .
 Corporate loan: If bank lend money to an up and running company
or corporate then it is called corporate loan.
 Retail loan: If bank gives loan to individuals rather than institutions or
for small businesses called retail loan.
o The retail loans may be for education ,agriculture ,personal , car
purchases, home purchases, medical care, home repair, holidays,
and other consumer uses.
o Credit card and overdraft is also a retail loan.
o Overdraft should be also a corporate loan.
 Soabring loan: If bank lend money to government for a specified term
is known as soabring loan.

4. ROLE OF ANALYTICS
 By using Analytics we can answer the following questions.
 Whom to lend ?
 What to lend ?
 How much we can lend ?
 What are the tenure of months for lend ?
 Whether we need collateral or not to give loan ?
o These are the problems we need to resolve by using analytics.
Steps followed by bank to reduce risk in a loan:
 Initially bank asks document to check the details to understand
whether the loan is a good credit or bad credit.
 They check income level ,credit worthiness, how much interest they
can charge ,recovery rate ,value of the loan ,net worth ,value of the
mortgage , etc.
 Banks decide the interest rates based on the credit ratings means if
you have good credit rating then bank charge low interest rate
otherwise they charge high interest rate on your credit.

5. MEASUREMENT OF CREDIT RISK:
 Credit Risk is measured based on “Advanced Internal Rating
Approach”. By measuring the “Expected Loss”, credit Risk is
quantitatively measured.
 According to Basel the banks need to compute credit risk based on
three parameters/measures.
1. Probability of default(PD) : It is describing the likelihood of
a default over a particular time horizon. It provides an estimate of
the likelihood that a borrower will be unable to meet its debt
obligations.
 In numerical value probability of default presented in 0 and 1 .
 Probability of 1 means default and probability of 0 means not default
. So it is a number between 0 and 1.
2. Loss given at default(LGD):The amount of funds that is lost by a
bank or other financial institution when a borrower defaults on a
loan.
 LGD is a number between 0 and 100 it calculated in percentage.
 It means percentage(%) of loan amount i.e default.

6. 3. Exposure at Default(EAD):along with loss given default (LGD) and
probability of default (PD) - is used to calculate the credit risk capital
of financial institutions.
 The expected loss that will arise at default is often measured over
one year. The calculation of EAD is done by multiplying each credit
obligation by an appropriate percentage. Each percentage used
coincides with the specifics of each respective credit obligation.
 So exposure at default is a rupees for bank to the customer.
What is Default ?
 Default means fail to fulfil an obligation, especially to repay a loan.
 According to bank definition default means 90 days past due(DPD). If
you are not paying your EMI for 90 days then you consider as a
defaulter.
 This is the rule for default even if i pay on 91th day then also it will
not consider.
 After 90 days the loan became a non performing asset .

7. CREDIT RATING:
 A credit rating assesses the credit worthiness of an individual,
corporation, or even a country.
 Credit ratings are calculated from financial history and current
assets and liabilities.
 A credit rating tells a lender or investor the probability of the subject
being able to pay back a loan.
 A poor credit rating indicates a high risk of defaulting on a loan, and
thus leads to high interest rates.
 For soabring loans ,inter bank loans ,corporate loans and retail loans
the rating agencies gives the details of the rating.
 The factors which may influence a person's credit rating are:
 ability to pay a loan interest
 amount of credit used saving patterns
 Credit Rating Agencies are the main authority to assign rate of credit
for the companies who issue debt.
 Credit rating model: 1st Indian corporation(Domestic model)
1st American corporation(International model)

8. CREDIT RATING AGENCY IN INDIA
 Credit Rating Information Services of India Limited (CRISIL).
 Investment Information and Credit Rating Agency of India
(ICRA).
 Credit Analysis & Research Limited (CARE).
 Duff & Phelps Credit Rating India Private Ltd. (DCR India)
 Onicra Credit Rating Agency of India limited(ONICRA).
 Credit Information Bureau India Limited -(CIBIL)
 High Mark Credit Information Services
 SME Rating Agency of India Ltd. (SMERA)
 Brickwork Ratings India Private Ltd
 Fair Issac Corporation(FICO)

9. 1.CRISIL (Credit rating and information services
of India ltd.) :
 it is a global analytical company providing ratings ,research and risk
and policy advisory services.it is the largest credit rating agency in
India.
 CRISIL’s majority shareholder is STANDARD and POOR’s.
 CRISIL has also spearheaded the formation of the Cari CRIS, the
world's first regional credit rating agency.
 Credit rating services offered by CRISIL are the followings.
 CRISIL launches Education Grading, beginning with business
schools
 CRISIL Rating enhances access to funding for SMEs; Announces
20,000th SME Rating
 CRISIL Ratings launches Solar grading
 CRISIL Research launches Gold and Gilt Index
 CRISIL Global Research & Analytics receives NASSCOM Exemplary
Talent Practices Award.

10. 2.ICRA ( Investment Information and Credit Rating
Agency of India Limited) :
 ICRA is a Public Limited Company, with its shares listed on the
Bombay Stock Exchange and the National Stock Exchange.
 Moody's continues to be the largest single shareholder in ICRA.
ICRA has a pan-India presence and has offices in 8 locations.
 ICRA's Grading of Initial Public Offerings (IPOs) is a service aimed at
facilitating assessment of equity issues offered to the public.
 The emphasis of the IPO Grading exercise is on evaluating the
prospects of the industry in which the company operates, the
company's competitive strengths that would allow it to address the
risks inherent in the businesses and effectively capitalize on the
opportunities available as well as the company's financial position.

11. 3.CARE(Credit analysis and research limited)
 CARE Ratings commenced operations in April 1993 and over nearly
two decades, it has established itself as the second-largest credit
rating agency in India.
 CARE was registered by SEBI as per Securities & Exchange Board
of India Regulations 1999.
 CARE Ratings has also emerged as the leading agency for covering
many rating segments like that for banks, sub-sovereigns and IPO
gradings.
Rating Services:
 With regard to rating services offered by CARE or Credit Analysis &
Research Ltd, the agency carries out rating of the following debt
instruments:
 Structured obligations
 Commercial paper
 Debentures
 Fixed deposits
 Bonds

12. 4.DCR(Duff & Phelps credit rating india limited):
 It was founded in 1932 to provide high quality investment research
services focused on the utility industry.
 Duff and phelips strengthened its valuation capabilities with the
acquisition of Standard & Poor's Corporate Value Consulting
business .
5.Onicra Credit Rating Agency of india limited:
 Bangalore based Onicra Credit Rating Agency is one of the leading
Credit and Performance Rating agencies in India.
 It provides ratings, risk assessment and analytical solutions to
Individuals, MSMEs and Corporates.
 Milestones Onicra operates as a financial services organisation. Its
products and services include Individual Credit Rating, SME rating,
Employee Background Screening, Customer Profiling & Rating
(CPR), Associate Rating and IT solutions, across the telecom,
banking, health, insurance, education and auto sectors.

13. 6. Credit Information Bureau India Limited -
(CIBIL):
 It is an Credit Information Company which maintains records of an
individual‘s payments related to credit cards and loans. The
information about users credit cards and loans is later used by the
CBIL to generate Credit information reports which are used to
approve loan applications.
7.Brickwork Ratings India Private Ltd:
 Brickwork's ratings for large corporate customers, SMEs, banks,
financial institutions, state and local governments, help investors
understand the complexity of the investment world.
 Brickwork is founded by bankers, credit rating professionals, former
regulators as well as professors, is committed to promoting Financial
Literacy.
8.Fair Issac Corporation(FICO):
 Fico is a rating agency who rates for individuals.

14. Top 10 credit rating agencies in the world are
1. MODDY’S
2. Standard & Poor’s
3. Fitch
4. DBRS
5. Egan-Jones
6. A.M Best
7. Japan Credit Rating Agency Limited
8. Rating and Investment Information Inc
9. LACE Financial
10. Realpoint LLC

15. 1.MODDY’S: It is the bond credit rating business of Moody's
Corporation, representing the company's traditional line of business
and its historical name. Moody's Investors Service provides
international financial research on bonds issued by commercial and
government entities.
 The company ranks the creditworthiness of borrowers using a
standardized ratings scale which measures expected investor loss in
the event of default.
 Moody's Investors Service rates debt securities in several market
segments related to public and commercial securities in the bond
market.
2. Standard & Poor’s:
 As a credit-rating agency (CRA), the company issues credit ratings
for the debt of public and private companies, and other public
borrowers such as governments and governmental entities. It is one
of several CRAs that have been designated a nationally recognized
statistical rating organization by the U.S. Securities and Exchange
Commission.
 S&P issues both short-term and long-term credit ratings.

16. Credit Rating Grades:
• The credit rating agency company rates borrowers on a scale from
AAA to D.
• Intermediate ratings are offered at each level between AA and CCC.
Investment Grade:
 AAA(Highest Safety):An borrower rated 'AAA' has extremely strong
capacity to meet its financial commitments. Such investments carry
lowest credit risk.
 AA(High Safety): An borrower rated 'AA' has very strong capacity to
meet its financial commitments. It differs from the highest-rated
borrower only to a small degree. . Such investments carry very low
credit risk.
 A(Adequate Safety):An borrower rated 'A' has strong capacity to
meet its financial commitments but is somewhat more susceptible to
the adverse effects of changes in circumstances and economic
conditions than borrower in higher-rated categories. Such
investments carry low credit risk.

17.  BBB(Moderate Safety) : An borrower rated 'BBB' has adequate
capacity to meet its financial commitments. However, adverse
economic conditions or changing circumstances are more likely to
lead to a weakened capacity of the borrower to meet its financial
commitments. Such investments carry moderate credit risk.
 BB(Moderate Risk): An borrower rated 'BB' is less vulnerable in the
near term than other lower-rated borrowers. However, it faces major
ongoing uncertainties and exposure to adverse business, financial,
or economic conditions, which could lead to the borrower's
inadequate capacity to meet its financial commitments. Investments
with this rating are considered to have moderate risk of default
regarding timely servicing of financial obligations.
 B(High Risk): An borrower rated 'B' is more vulnerable than the
borrowers rated 'BB', but the borrower currently has the capacity to
meet its financial commitments. Adverse business, financial, or
economic conditions will likely impair the borrower's capacity or
willingness to meet its financial commitments. Investments with this
rating are considered to have high risk of default regarding timely
servicing of financial obligations.

18.  CCC: An borrower rated 'CCC' is currently vulnerable, and is
dependent upon favourable business, financial, and economic
conditions to meet its financial commitments.
 CC: An borrower rated 'CC' is currently highly vulnerable.
 C(Very High Risk) : highly vulnerable, perhaps in bankruptcy or in
arrears but still continuing to pay out on obligations. Investments with
this rating are considered to have very high risk of default regarding
timely servicing of financial obligations.
 D Default : has defaulted on obligations and most of the credit rating
agencies believes that it will generally default on most or all
obligations .
Investments with this rating are in default or are expected to be in
default soon.

19. WORLD COUNTRIES BY STANDARD & POOR'S
SOVEREIGN RATING

20. Bond:A debt investment in which an investor loans money to an entity
(corporate or governmental) that borrows the funds for a defined
period of time at a fixed interest rate.
 Bonds are commonly referred to as fixed-income securities and are
one of the three main asset classes, along with stocks and cash
equivalents.
 Example:
 Suppose the above one is the bond of ITC which gives the following
information.
 It means ITC has 1000 rupees bond which gives 8% return.
 Maturity/Tenure: It’s the time of maturity like 03/03/2014.
 AAA is the grading means highest grade of safety on investment.
 Face value and coupon rate also important aspects of a bond.
 So the bond depends upon the above rates.
AAA 03/03/2014
8% 1000
ITC

21.  The bonds are followed prevailing interest rate means
the average interest rate currently charged by lending institutions.
 So all the above concepts determine the price of the bond.
 How can a person invest on bonds based upon their age ?
 So there is a thumb rule in mathematics to invest money in bonds
depend upon respective age group.
 For example a person whose age is 24 years
100-24
=76
 It means the person need to invest 76% in bonds and 24% in stock.
 Avenue of bonds are commodity ,gold ,silver ,forex ,stock , real state
,etc.
 Bonds are also fixed in income securities.
 Age calculation:
(System date – DOB)/364.5 it gives us exact age.

22. What information bank looks before the loan ?
 Bank divided the information into three parts:
 Loan related date
 Customer data
 Other products usage data
• Customer Data:
 Occupation: Any body comes under the following occupation
category.
•Government Service
•Private service
•Self employed professional
(like qualification of his
professional.Ex: Doctors,
Advocate,
Cricketer,Actor,Etc
•Student
•House wife
•Retired
•Unemployment
(These category borrowers
belongs to no income level
group.)

23.  Marital Status:
 Dependent:
 Age
 Gender
 Location
 Income
Single
Married
Widowed
Separated
Spouse
Children's
Guardians
Parents
Etc

24.  Loan Related Data:
 Margin: It comes in percentage of the total project amount.
 Example: If the valuation of the total project is 40 lakhs then u need
to pay 5 lakhs then the bank will pay rest of 35 lakhs because bank
consider 5 lakhs as margin to observe whether u are able to pay the
amount or not.
 Co-applicant: Co applicant is a joint borrower ,bank will ask for co-
applicant to reduce the credit risk.
 Prime Collateral: It means bank asks for some document which can
quickly converted into money.
 Example: Fix deposits and LIC are considered as a prime collateral.
 EMI: It is the equated monthly installment which the borrower need to
pay in every month.
 EMI by income: It tells the bank that what percentage of income they
can go for EMI.
 Higher the income lesser the risk similarly higher outstanding is more
risk.

25. Note: Always buy appreciation asset in borrowed money .
 Never buy depreciation asset in borrowed money.
 So government employees are more safer then the self employed in
case of giving loans.
 So in case of loans and money lending bank follows the above age
distribution model.
 It means this age group people is safer between 30-50 years
otherwise more younger and more older peoples face difficulty to pay
the loan.
 Similarly higher the margin of the total project means lower the risk.
Young Old
30-50 yr.

26. What bank looks for credit risk according to Basel ?
1. Default definition
2. Type of default
3. Credit risk default
4. Three measures of credit risk(PD,LGD,EAD)
5. Different type of loans
6. Employment type
7. Margin
 After that they divided the data into three categories like
1. Loan related data
2. Customer data
3. Other products usage data
Note: The model built for home loan is not intended for application
scorecard and hence cannot be used for loan dispensation.

27. CAPITAL:
 As per Basel every bank should set aside the capital for every loan
on the books.
 Computation of capital used probability of default, loss given at
default and exposure at default.
 For example home loan data consist of 18345 unique records by
facility id spread across 34 different location.
 Out of which 852 are defaulters and rest of all are non defaulters.
 So we have non numeric variables like gender,occupation,marital
status
MODELLING:
 Building the model using logistics regression (prediction model):
 For calculating probability its numbers like 0 and 1 .
 We can also calculate number of favorable by dividing the number of
favorable with total no of data's.
 We can also calculate the number of odds by dividing favorable with
unfavorable.

28.  Example: In case of dice probability of 3 is 1/6.
 Similarly in case of dice odds of 3 is 1/5 ,where 1 is favorable and 5
is unfavorable.
 Hazard: Rate at which the event happens is known as hazard.
 The log of odds of default can be predicted with reasonable
accuracy given borrowers details like loan related ,demographics
related and other products related.
 Log of odds means logit .
 The log of odds is estimated using the maximum likelihood
estimate(MLE) as a linear combination of explanatory category.
Y = logit(X) =B + B (X1) + B (X2) + B (X3) +. . . . +B (Xn)
 Where ‘B’ is the parameter estimate X1,X2,X3 are explanatory or
independent variables like age, loan, amount, etc and Y is the
dependent variable.
 These estimates can be checked for accuracy using model fit
statistics.
0 1 2 3 n

29.  The predict power of the model can be verified empirical through
decline analysis and concordance .
 The log of odds obtained above can be converted into probability
using the function exp(logit(X)) / (1+exp(logit(x)).
 A comprehensive list of variables consumed by the model1 are all
the 35 variables like income, age , gender, emi , interest rate , joint
loan ,annual income ,loan amount ,loan tenure ,loan outstanding
,term deposits.
 Similarly except age, gender all including in model 2 what are
available in model1.
 Maximum likelihood means what is the probability of defaulting the
loan.
 So -2loglikelihood (-2logL) is less then the model is better.
Maximizing the likelihood = minimizing the likelihood -2logL
 Dividing into 10 groups of all the loan holders for example 18354
loan holders . So the first group is 1835 ,which has the highest
probability of default.
 The order is descending means lower the order is less probability of
default.

30. Example: Suppose in the 1st part 452/1387 = 25% default.
 In 10th part is 812/17542 = 4% defaulter.
 So the number of defaulters in 1st stage is 6 times more then 10th
stage.
 By using this model we can find to whom we can promote the loan
through mails ,phone ,sms , etc.
 Decile Analytics and Confusion matrix is empirical proved that
the model is good.
 The above example is a confusion matrix example.
 But log likelihood is a statistical method to prove a model is good.
 Blunder rate in a model should be low.
 Example: if the model says defaulter but the borrowers are not
defaulter then its good .
 If the model says non-defaulter but they are defaulter then this is not
a good model or it’s a blunder for the bank.

31. Black Test: It is done for the customer who are not available in the
model.
 Probability of outstanding is called the expected loss (Express this
loss as percentage of total loss).
 Expected loss is how much loss occurred before the collateral been
taken is called loss given at default(LGD).
 Example: If my rate is 80% of default and someone's rate is 20% the
expected default is expressed as default of 50%.
Percent Concordant:
 This is also an empirical proved model.
 It means out of 160000 customer we made a sample of 18375
customer pair where one is defaulter and other is not . Now if we
check the no of actual defaulter add all and express it in ‘%’ is
concordant.
Percent Discordant: (It is also an empirical proved model)
 It means from the pair the non defaulters express in’%’.
 So Decile analytics ,confusion matrix ,Discordant and Concordant
are the empirical proved methods.

32. Note: In case of loan defaults no body have probability of ‘0’ to
default ,so bank takes 0.03 as default and its Basel rule.
Bankers formula for loan:
 The risk mitigated exposure (E*) is obtained for each loan is
calculated using this formula.
E* = max{0,[E*(1 + He)- (X(1-Hc-Hfx)]}
E* = Exposure value after mitigation.
Capital requirement(K)=LGD *N[1-R]^ - 0.5* G(PD)+(R/(1-R))^0.5 *
G(0.999)]-PD*LGD
K = capital required for one rupee of exposure.
R= Asset correlation obtained
For example: If I fail then what is the probability at you fail .’R’ can given
by banks.
G(0.999) is the inverse standard normal variant for value =0.999
N=Cumulative normal value.
RWA=K*12.5*E*

33.  So from the above study we can conclude that PD is the analytics job
but LGD is calculated by banks which is arithmetic.
 For banks from where the capital comes to keep aside ?
 Answer: 50% of capital comes from shareholders capital and the
other 50% of capital can come from other sources of money.
 Shareholders capital comes from previous profit or from current
shareholders capital.
 Example: If I need to keep 12 paisa as capital from 1 rupee
exposure then bank need to keep 6 paisa as 50% of capital from
shareholder capital.