FINAL REPORT OF PROJECT WORK-II

Title of the Project: Calculating RAROC for Corporate Accounts in Bank of Baroda

ByJagjeet kumar

GuideMr.Alok BANERJEE(Chief Manager)

Project Work Undertaken at: Bank Of Baroda

Report submitted in partial fulfillment of the requirements for the award of

Post-Graduate Diploma in Banking and FinanceBy

National Institute of Bank Management, Pune, 2007-08

CONTENTS

Acknowledgement:

Objective

Chapter-I…………………………Introduction

Chapter-II………………………..Review of literature

Chapter-III………………………Data & Methodology

Chapter-IV………………………Results, Analysis & Interpretations

Chapter-V………………………..Conclusions & Recommendations

Chapter-VI………………………Executive Summary

Chapter-

ACKNOWLEDGEMENT

I sincerely acknowledge my indebt ness to Mr.Asit Pal (General Manager, Risk Management Department, Bank of Baroda) for giving me opportunity to conduct my project on calculating the RAROC (Risk Adjusted Return on Capital) for the Corporate accounts. He has been constant source of inspiration and guide throughout the project. I am also deeply thankful to Mr. A D M Chawli (Deputy General Manager, Risk Management Department) for giving me necessary guidance and access to resources to conduct my project. I would also thank my guide and mentor Mr. Alok Banerjee for constant guidance. I am also especially thankful to Dr.Ashish Saha(Director,NIBM) ,Prof.Kalyan Swaroop(Dean NIBM) and Mr Arindam Bandhopadhaya (NIBM Faculty ) and other faculties of the institute for constant guidance and teaching us the subject so that I could do this Project. I am also grateful to Mr. R.K.Rana (AGM) Mr. H S Patil, Mr. D Mahabal and Mr. Ratnesh Mishra from the Risk Management dept for their continued support. For collection of the data I have to approach different departments. So I also thank Mr. Awasthi (DGM recovery) Mr. Upreti, Mr. Upadhe, Mr. Man Mohan Jha from the ASCROM cell and Mr. Batra, Mr. Bhatia, Mr Prasant and Mr. Rajesh from wholesale banking department MR Govil from the planning dept.

Last but not the least I am thankful to all my fellow colleagues and friends for giving me friendly environment and support. In this final round I also thank my family who took a lot of pain and perseverance so that I can do this Project and complete the course.

Objective

The main objective of the project is to calculate RAROC for the corporate accounts based on the data provided by the Bank. The RAROC has emerged as the powerful tool to measure profitability of the Bank. It incorporates the cardinal principle of finance i.e. Risk and Return and combines them the Economical Capital requirement of the Bank based upon the quantum of risk taken in the business. This kind of the study has become important as traditional methods of profitability measure like ROA, ROC, etc don’t take into account the quantum of risk undertaken by the Bank in its day-to-day business. After BASEL-II implementation the requirement of Capital is linked with the Risk undertaken. So we may say that RAROC is basically BASEL-II compliant performance measure for the Banks. This integration of Capital along with the business expansion and risk undertaken becomes more relevant for Banks as they are not going to Capital market so frequently particularly for PSBs where any further Capital infusion requires Govt's commitment also. Though RAROC concept is generally applied at firm level and it incorporates all kinds of the Risks, i.e. Credit, Market and Operational risks and Banks economic capital based on the Credit, Market and Op Var. But my study is limited in scope to calculating RAROC for the selected corporate accounts. This limitation is obvious due to the fact there is constraint of resources like data, time and manpower and software. One of the aims of the project is to compare RAROC with that of cost of capital determining performance of Corporate accounts at both bank level & business unit levels. In decision making RAROC may be applied as a thumb rule as •If RAROC > Cost of capital, there is a value addition•If RAROC < Cost of capital, value is destroyed •If RAROC = Cost of capital, value is maintained

INTRODUCTION

Risk adjusted return on capital (RAROC) is a risk based profitability measurement framework for analyzing risk-adjusted financial performance and providing a consistent view of profitability across businesses. However, more and more (RAROC) is used as a measure,

whereby the risk adjustment of Capital is based on the capital adequacy guidelines as outlined by the Basel Committee (currently Basel II).

Broadly speaking, in business enterprises, risk is traded off against benefit. RAROC is defined as the ratio of risk adjusted return to economic capital. Economic capital is a function of market risk, credit risk, and operational risk. This use of capital based on risk improves the capital allocation across different functional areas of banks, insurance companies, or any business in which capital is placed at risk for an expected return above risk-free.

RAROC system allocates capital for 2 basic reasons

1. Risk management 2. Performance evaluation

For risk management purposes, the main goal of allocating capital to individual business units is to determine the bank's optimal capital structure (i.e., economic capital allocation is closely correlated with individual business risk).As a performance evaluation tool, it allows banks to assign capital to business units based on the economic value added of each unit.Some of the benefits are listed below

Segment wise Risk profile generation: Incentives based on RAROC RAROC based planning• Pricing strategy of the loans• It will show how much risk adjusted return different segments of

the business are giving when we compare them with Economic capital based hurdle rate (RAROC).

• It will provide which segment is creating the shareholder’s wealth and which segments are destroying them.

• The Economic Capital is also expected to be less when we take the diversification benefit than the for the standalone case.

• Business decision making• Restructuring & Revamping. Product performance

appraisalOverview of Typical RAROC Model REVIEW OF LITERATURE Commercial Banks are typical financial intermediary who accepts deposits from the Public and invest in form of the loans, investments in bonds or equities, etc. For mobilization of the deposit they pay interest to the depositors and also they have operation cost associated with the operation. The investments and the loans granted by the Banks yield interest which typically covers the cost of fund and operations

cost besides yielding sufficient margin to the shareholders of the Bank. But all things do not go as planned. It has been observed that the Banks are typically exposed to risks emanating from the Market variables like interest rate movement, equity price volatility, volatility in forex markets, derivative spread and losses etc giving rise to Market risk. On loan front the Banks are basically exposed to the default or no payment of the interest as well as principle of the loans. This is called Credit risk. Besides these two types of the primary risk another type of risk which has become prominent now a day is Operational Risk. This risk is due more to control and checks system failure i.e. poor Management. Formally we may define these risk categories as follows:Credit Risk: Credit Risk arises from default when an individual, company, or government fails to honor a promise to make a payment. Ex-Counterparty credit risk, Loan credit risk, Issuer Credit Risk, Settlement credit risk, etc.Market Risk: Market Risk arises from the possibility of losses resulting from unfavorable market movements. So it is Risk to losses due to changes in the perceived value of an asset, without any contractual failures. Ex- losses in equity market, forex market, bond market, etc.Operational Risk: The most general definition of operational risk is that it is the risk of losses due to factors other than market risk and credit risk. Basel committee defines it as “The risk of direct or indirect losses resulting from inadequate or failed internal processes, people and systems or from external events”The typical loss reward distribution of these three types of risks are shown in following page

BASEL Committee has in recent recommendations (BASEL-II) has emphasized over the management of these risk Banks face. For the measurement and management of the different risks BASEL-II has advised the following approachCredit Risk

Standardized Approach

Internal Rating Based Approach (IRB-Foundation)

Internal Rating Based Approach (IRB-Advanced)

o Market Risk

Standardized Approached (Maturity)

Standardized Approach (Duration),

Internal Risk Based Approach (VaR)

o Operational Risk

Basic Indicator Approach

Standardized Approach

Advanced Measurement Approach

RBI has also applied the recommendations of the BASEL-II in phased manner. So from 31.03.2008 our Bank has to comply with BASEL-II recommendations as prescribed by RBI. So Banks are required to have Capital for each of these risk class. This requirement of Capital has

necessitated the performance measure which gives the Shareholder the commensurate return vis. a vis. risk taken by the Bank. RAROC is such measure which measures the risk return reward and compares it with the cost of capital of the Bank.

But before going on lets define few terms which will be useful in understanding RAROC concept.

Credit Risk: It is defined as the non fulfillment of the contractual obligation by the counterparty/obligor. This non-fulfillment may be due to obligor inability or unwillingness and may be also classified as exogenous or endogenous factors related to the borrower (systematic or unsystematic). The credit risk also arises due to concentration of exposure in certain sector of the economy (CONCENTRATION RISK). Concentration risk is mitigated through the exposure norms related to individual and group companies and industry /sector exposure limit.The credit risk is also dependent on the economic cycle and world over it is observed that the Defaults increases as the economy slows down.

Probability of Default (PD):- It is defined as the probability of non –payment of the loan as well as interest by the counterparty/obligor fully or partially. The PD is calculated with the help of credit rating migration matrix. It is usually measured for next 1-year rating process is done usually once in a year. The factors affecting the PD are internal to the obligor as well as external. Credit Rating is important tool to measure the PD.

Loss Given Default (LGD): It is the fraction of the EAD that will not

be recovered if default occurs and is calculated as a percentage of the

exposure at the date of default. LGD is facility specific and depends

upon the collateral quality, seniority, legal framework, economic cycle

etc.

LGD = 1 – Recovery Rate/EAD

When we discount the recovery to the date of default then it is called the economic LGD.

Exposure at Default (EAD): It represents the expected level of usage

of the facility when default occurs. This factor also depends upon the

type of facility, borrower’s history and his liquidity conditions.

EAD = Outstanding + (CCF Free Limit)

Outstandingd – Outstandingd–1

CCF = ——————————————

Limitd–1 – Outstandingd–1

Expected Loss (EL): It is the anticipated average loss over a defined period of time. It is akin to cost of doing business and has to be recovered from the borrowers as risk premium. The expected loss is taken as the mean of credit loss distribution. This is calculated as EL=EAD*PD*LGD

Unexpected Loss (UL): Unexpected loss is potential to exceed the expected loss and is a measure of the uncertainty in the loss estimate. It is measured as follows

UL=EAD*√(PD*σLGD² +LGD² *σPD²)

Where σLGD² is Variance of LGD and σPD² is variance of PDAlso σPD² =PD*(1-PD) due to binomial distribution of PD

Economic Capital (EC): Economic Capital is the measure of risk and is based on a probabilistic assessment of potential future losses at a selected confidence level.

So EC =m x Capital required to cover worst-case loss (Minus expected loss) due to credit risks.

m is often a multiplier determined by the bank based on its desired credit rating, its required confidence threshold (say at 99% or 99.97 %) and the actual observed distribution of losses.

EC=N‾1(99.97%)*ULP –ELP (For AA rated banks)

Cost of Capital (COC): Cost of Capital also known as Hurdle rate is the amount of return shareholder demand for taking risk. It can measured based on the CAPM model

Hurdle Rate, R=Rf+β(Rm-Rf) Where β is the slope of regression line running between market return and stocks return. These returns can be estimated based on the Market index and share price closing value.Mathematically the RAROC is defined as below

Risk-Adjusted Income RAROC = Economic Capital at Risk

These terms may be further explained as below-

Risk Adjusted Income= + Financial income (Interest revenue + Fees)

- Cost of Funds (FTP costs) -Non-interest Operating Expenses - Expected Credit losses

DATA & METHODOLGY

DATA COLLECTION: The data for RAROC Calculation required was mainly obtained from the ASCROM system of the Bank. The ASCROM system gives details like Branch, Borrower name, Limit Sanctioned,

Outstanding Balance, Asset Classification, Credit Rating, etc.The other sources of data were collected from the recovery dept ,wholesale Banking dept, NSE website, etc.

For calculation of PD base year 2000 was taken and all funded facilities above Rs 20 Crores accounts were listed. Ideally this cut off limit should have been say Rs 50 Crores or Rs100 Crores but due to the fact that number of such acounts was small so for better statistical accuracy I have stick to Rs 20 crores as funded exposure at the end of March from year 2002-2007. The variables like asset class, name of the account, credit rating, Branch, Zone, etc was noted in EXCEL sheet (Annexture1).

For calculation of LGD 103 accounts the reference cut off was Rs 1 Crore for all recovered/settled accounts during the period 2005, 2006 and 2007(Annexture2).

For EAD calculation the outstanding balance above Rs 20 crores as on 31.03.2007 was taken. Since the RAROC was calculated at outstanding as on 31.03.2007 it does make sense. However, it is advisable to collect more comprehensive data for EAD calculation along with CCF and unutilized commitments.

For calculation of Yield data was collected from the sanctioned files of the Corporate Loan over the period from 2002-2007.Altogather 117 cases were studied and noted down (Annexture3).

For the Cost of Capital calculation the closing share price of the BOB on NSE was collected for the period from 01.04.2006 to 31.03.2008.For beta calculation the S&P500 Index closing was selected for the same period (Annexture4).

For Cost of fund and Operating expenses Banks Audited BS of 2007 was taken as reference source and cost was determined based on the published data.

The primary assumption behind the sanction of the loans is that funds are profitably deployed and these loans yield enough return not only to satisfy the depositors and meet the Operating expenses but also generate enough income for the shareholder. Many a times the big corporates get the Sub-BPLR loans and in absence of proper risk reward mechanism it becomes difficult to determine the profitability of decision taken, though our gut feeling says that the sanction process is profitable. RAROC helps in concretizing this gut feeling.

Tools adopted in this study are simple EXCEL based technique which can be comprehended easily and also there are no advanced software to do such study at present.

Analysis, Results, & Interpretations

PD Calculation: For PD calculation the no of accounts at the beginning was segregated among the different rating categories and it was determined how many got slipped into default categories (Default category is as NPA as per regulatory definition). This data was collected for the years 2003,2004,2005,2006 and 2007(Annexture-5). As can be seen from the sheet the no of accounts defaulting is highest in year 2004. In total there were 6 defaults over the period and out of these 4 were in B and C categories. This result is in conformity with our

assumption that the good rated accounts have less PD. The PDs for the relevant years are 0, 2.78%, 0.88%, 0.65% and 0.44% respectively. One interpretation of reduction in PD in later 3 years is that Economy has been very buoyant after 2004 and it also reinforces our hypothesis

that in expansion phase the no of defaults are less. The yearly PD is then multiplied with the weights of the No of accounts in the pool (709) and then the mean weighted PD is arrived at. In our study this comes to 0.85%.The variance of PD comes to 0.84%

The Rating Migration was also studied on 102 corporate accounts as on 31.03.2002 as base and their behavior during the next five years i.e. upto 2007.These accounts were classified as per rating categories and year to year rating migration juxtaposed(Annexture-6). This methodology is commonly followed for the study of the bonds default characteristics. So the accounts were sorted as per the rating categories of the first year and the subsequent ratings were also noted. So the accounts remained in the same rating category or upgraded, downgraded or even defaulted. In few cases the accounts were withdrawn without default. For such Rating withdrawal the study has considered them as rating retained in their original grade as suggested by the Edward Altman in his book Managing Credit Risk(page218-220). The yearly PD has been calculated as shown in Transition Matrix for different years (Annexture-7). Here the methodology used is similar to calculation of pooled PD. As can be seen the retention rate in rating category is highest for good accounts and is low for the lowly rated accounts. Also the rating migration is along the diagonal axis implying the rating retention characteristics.

The same data pool is analyzed for cumulative 1-year, 2-year, 3year, 4-year and 5-year rating migration and default (Annexture-8). Here in the 5 –year migration matrix we observe that the rating withdrawal has mostly occurred in AAA and AA accounts (good quality customers have left the Bank more than the bad quality customers), which is the matter of concern as the no of relatively low quality accounts have increased and in the process the credit quality has deteriorated. Here also overall diagonal concentration of rating category is observed but in last migration matrix (5 year cum PD) as we can see there is considerably divergence towards the mid-rating segment. This finding is in consonance with rating Transition Matrix for 5 years as given on page 222 of the above mentioned book.

LGD Calculation: For the LGD calculation the study has taken 103 accounts as sample and the date on default, date of compromise, years in default, recovery amount, recovery cost, etc were determined. These amounts were discounted to the date of default taking 10%

average discount rate (Bank uses 10% as discount rate). Then the economic LGD is calculated for the individual accounts. The pooled LGD can be taken from aggregate figures as shown in Annexture-2.

RAROC Calculation: RAROC calculation is given in Annexture-9 .The workings are self explanatory. First EAD is taken as Rs1 and then the calculation is done. The Expected Loss is 0.59% and the unexpected loss is at 2.3%.Thus we see the unexpected loss is much more than the expected. At 99.97% confidence interval Economic Capital is calculated at 6.97% which is less than the 9% CAR as regulator prescribes. Since, the RAROC calculation typically follows the Advanced IRB approach for capital calculation. It shows how Banks will be able to save on the Capital if they have robust system of the risk management. In our study the RAROC comes to 13.48%.The EL, UL and EC for the exposure of Rs 304.67 billion (as on 31.03.2007) is also calculated When we compare this RAROC with the Cost of Capital we find that our RAROC was higher than the cost of capital. So we may say that the corporate accounts are giving profitable returns. However even minor change in yield in the loan accounts or credit quality deterioration may result into higher Economic capital, reduced RAROC.The scenarios are as follows:

Wtd PD=0.85% σpd=0.84% LGD=69.23% σLGD =24.14%EAD=1 EL=0.59% UL=2.30%

EC@99.97%(Internal CAR) = 6.97% Yield=8.34%COF=4.77% OPex =2.05%RAROC=13.48% At Yield@8% RAROC=8.60%COF=5.25% RAROC=6.59 %(< COC)OPex=2.50% RAROC=6.95 %(< COC)PD=1.25% RAROC=11.12%LGD=80% RAROC=13.50%At EAD (31.03.2007) =Rs 30468.03 crEL=Rs 1784.95 Cr UL=Rs 6993.03 CrEC=Rs 2122.56 crCOC (Hurdle Rate) =7.70%

So we can say that the RAROC is highly sensitive to yield on advances, COF and OP ex.

Recommendations

Finally we conclude the study with hope that Bank will have to move to Advanced IRB approach and it will have enough quality data to move towards RAROC implementation, not only in credit but also for other areas of risk management. Some important points are as below.

Bank needs strong MIS system and Costs involved in each segment. Further it should be the endeavour for the Bank to use RAROC as signal for taking decisions which involve risk and Capital.

Also our Bank is using internal CRISIL model for the risk rating of the accounts since 2006. In many accounts two or three ratings are available. So sample validation of the parameters like PD, LGD, and EAD should be done on these accounts. As these parameters are highly dynamic and hence needs constant up gradation.

For LGD and EAD estimation Bank wide study should be taken up.

The segmental funding pattern of the loans should be identified and costs incurred should be estimated.

It is pertinent that organization should become more vertical in structure so that costs involved can be calculated more accurately (Activity Based Costing).

Executive Summary

In the end I point down the steps followed by me for the RAROC calculation:

Initial step was to determine the methodology to be followed and quality and quantity of data to be collected.

Then literature was surveyed to determine the variables to use. Then data was collected using ASCROM, recovery history,

sanctioned files, Banks, NSE and other websites. The raw data was cleansed and particular outliers were left out. Then Excel based calculation was done to calculate the different

elements of the RAROC and then the RAROC was calculated. In transition matrix we observe diagonal rating structure which is

in conformity with rating migration marix given by S&P and Moody’s.

The calculated RAROC was then compared with the cost of capital and found that the Corporate Accounts RAROC is higher

than the cost of capital. This is important because this tells us that these corporate accounts are adding value to the shareholders wealth.

Limitations: I have not taken sanctioned limits as cut off due to the fact that

that information is not so reliable in ASCROM. The choice of Rs 20 crores has been taken on individual

judgment so as to have a sufficient pool of data points. Only funded limit is considered, as information regarding the

non-fund limits is not so reliable in ASCROM. The data for losses of Rs20 Crores and above are few and hence

proper recovery pattern cannot be drawn easily, so I will use Rs 1 crores and above data for NPA and recovery estimates.

References: De servigny and O.Renault, 2004,Measuring and managing

credit risk,S&P ,Mc Grow -Hill. A.Bandopadhaya, A note on measurement and

management of credit risk,NIBM Anthony Saunders and Cornett,Financial Institution

Management:A Risk Management Approach,chapter 11,12,5 th ed.

Altman,Narayanan and Cauette,Managing Credit Risk Credit Risk + of CFSB Phillip Jorian,Value a Risk BASELII :International convergence of Capital

measurement and Capital Standards :a Revised framework(BCBS,June2006 revised)

Websites: www.gloriamundi.com www.elsevier.com

www.fic.wharton.uppendu.fic www.erisk.com www.defaultrisk.com www.rbi.org