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Credit risk management presentation

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This presentation provides complete study ofcredit risk management,how it was performed in yester years ,how it is taken care nowadays and what is the road ahead in future

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Credit risk management presentation

  1. 1. Credit Risk Management in Banks
  2. 2. A Project Report Harsh Raj ( 16PGDMBFS23 )
  3. 3.  Indian banking is the lifeline of the nation and its people.  There have been many downturns in the economy and in the recent past the global economy has undergone a huge turmoil situation but then also Indian Banking sector has been able to hold its same position.  The main business of any bank across the globe is dependent on credit or loan  Today, Indian banks can confidently compete with modern banks of the world and Indian banking is looked out for all over the world  The Reserve Bank of India is a very pioneer institution which controls the whole banking sector in a very proper and well organized way.
  4. 4.  The global economic scenario is not in a good shape at all  After the US subprime crisis and the fall of Lehman brothers; after that crisis banking sector worldwide has not been able to get out of this shockwave.  Total economic growth is also slowing down due as a result lending from banks are also slowing.
  5. 5.  The incidence of Non- performing assets (NPAs) is affecting the performance of the credit institutions both financially and psychologically  The threat of burgeoning credit risk is looming  NPA is a disorder resulting in non –performance of a portion of loan portfolio leading to no recovery or less recovery/income to the lender.NPA represent the quantified “Credit Risk”.  Indian banks now have close to Rs 6, 00,000 crore bad loans.
  6. 6.  The main aim of the credit policy is Indian Bank is to provide adequate credit flow to the productive sectors of the economy and cater to them for their betterment.  Aims at priority sector lending.  The bank rate, the base rate, CRR , Repo Rate is the parameters which the RBI uses to control the liquidity in the market.  there is a chance of growth government wants the people to take more and more loans; it want to infuse liquidity in the market.  Currently due to burgeoning NPA’s the credit policy has been stringent. Banks has been vigilant while giving out loans.
  7. 7. We have taken the current NPA’s from the balance sheets with respect to its loans and advances.
  8. 8. We found that there is strong correlation between loans and advances and NPA , So banks should be very much cautious about lending out loans. y = 0.0002x2 - 14.828x + 568039 R² = 0.98 0.00 200,000.00 400,000.00 600,000.00 800,000.00 1,000,000.00 1,200,000.00 1,400,000.00 1,600,000.00 0.00 20,000.00 40,000.00 60,000.00 80,000.00 100,000.00 120,000.00 L o a n s & A d v a n c e s NPA Series1 Poly. (Series1) Graphical Representation
  9. 9. A credit risk is the risk of default on a debt that may arise from a borrower failing to make required payments. The Indian banks has already incurred huge losses for the same, almost there is a total bad loan of Rs.6 trillion according to a survey and the banks are expecting to experience more on this regard, there has been an alert situation.
  10. 10.  Asset Loan Quality  Asset Liability Mismatch  Fraud  Backdated Credit Risk Management Policy
  11. 11. It is the practice of mitigating losses by understanding bank’s capital adequacy and loan loss reserves at any point in time.The major goal is to maximize risk adjusted rate of return by maintaining credit risk exposure within acceptable parameters.
  12. 12. While giving out any loan the Bank’s needs to assess the credit risk in a proper way. It is very important you do a proper decision making of the same before giving out the loan.This is basically the part of decision making. Assessing credit risk requires us to model the probability of a counterparty defaulting in full, or in part, on its obligation.
  13. 13. Three scenarios arises now  Extend credit and you get returns. ………. (1)  Extend credit but loan is not re- payed (loan turns bad) ………. (2)  Refuse credit ………. (3) (1)+ (2) can be clubbed to get the total cost which turns out to be = (Revenue-cost) x (1-p) - cost x p [where cost is the cost of the loan] =0 if the credit is refused. [ p is the credit defaulting probability] Now it depends on bank’s discretion which way to go depending on the decision tree, if extending credit yields a positive result then it should go with it. But if the result is negative the bank should refuse the credit. This totally depends on bank’s research and findings while giving out a loan.
  14. 14. Value at Risk orVAR is used to calculate to find the level of financial risk within a firm in our case it will be Bank for a certain period of time.This is basically a statistical technique that is widely used by the banks to assess the total financial risk that it possesses.  Calculated through the statistical method of Covariance.  Generates a Normal Distribution Curve.  It has a certain level of confidence that the loan given out will not turn bad.  Helps the bank to track which kind of its asset are at risk
  15. 15. It is a visual tool which tags a client’s account to the risk portfolio.When these individual risk profiles are aggregated, we can get an overall idea of the credit risk profile of the receivables portfolio. It brings up following advantages: Easily understandable  Compels development of risk mitigation plans appropriate for each of the risk profiles Tracks changes of receivables over time.
  16. 16. Released in Dec 2010 as part of BASEL 3 accords Three pillars are: 1.Minimum regulatory risk requirement for RWA 2.Regulating frameworks 3.Increase bank’s transparency Guidelines for Effective credit risk management: 1.Establishing effective credit risk environment 2. Sound credit granting process should be followed. 3. Maintaining good credit administration, risk measurement and monitoring processes. 4. Banks supervisors should ensure they have effective system in place for identification, measurement, monitoring and control of credit related risks.
  17. 17.  Mortgage backed securities and collateralized debt obligations. Result-huge losses due to price of investments and adverse effect on counterparties ex-Lehmann Brothers  Over the counter derivates having long maturity periods Result-counterparties exposed to risk for long periods After 2008 crisis  Limiting over-the-counter exposure and asking for more collateral from brokers to protect against default and hedge themselves from the same.  Monitoring credit risk and it’s exposure to counterparties more closely.  Business governance  Credit risk as the topmost priority  Credit risk analysis using better technologies and forecasting techniques.  Complying to BASEL 3 norms.
  18. 18. Managing Credit Risk 1. Credit Portfolio Models 2. Internal Ratings 3. Exposure limit 4. StressTesting Mitigation 1. Risk based pricing 2. Covenants 3. Credit insurance 4. Credit derivatives 5. Collaterals
  19. 19.  Expert Systems  Check credit worthiness through internal & external ratings-ex CRISIL,ICRA etc  Proper Database Management  Credit Scoring Model Altman’s Z Score Model If Z<1.8 high probability of going bankrupt If 1.8<Z<2.99 it lies in grey area If Z>2.99 it indicates a healthy firm
  20. 20.  managing structure of balance sheet (assets and liabilities) such a way that net earnings from interest is maximized within the overall risk preference.  ALM Strategies 1. Spread Management 2. GAP Management 3. Interest SensitivityAnalysis
  21. 21.  Focusing more on holistic approach making credit risk important part of enterprise risk  Increase IT spending on risk and compliance systems  Centralized Data warehouse like enterprise data-warehouse.  Business Intelligence model and big data analytics  Using new software like SAS,IFRS etc  Outsourcing IT risk and compliance work to IT and consulting giants like TCS,EY,PWC etc.
  22. 22.  Inefficient Data Management  Non group wide risk management framework  Constant rework  Insufficient risk tools  Inconvenient manual reporting
  23. 23.  Full compliance to BASEL 3 norms.  Analyzing credit risk matrix effectively.  Asset Liability Management  More awareness and training to bankers about credit risk and it’s management  Better model management  Automated reporting process connecting all databases  Enterprise wide risk management and efficient use of DSS.  Use of modern analytical tools like SAS,R etc  Use of proper knowledge management database  Better KYC and CIBIL score check  Robust stress testing  Better Data visualization techniques and business intelligence model
  24. 24.  Better credit risk management improves overall performance and secure competitive advantage .  Reduces financial risk and generate greater revenues.  Better profitability  Chief goal of risk management-adopt universal and best practices followed worldwide

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