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Measures that May Reduce the Problem of Adverse Selection and Moral Hazard in Bank - Coursework Example

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The paper "Measures that May Reduce the Problem of Adverse Selection and Moral Hazard in Bank" is a good example of finance and accounting coursework. A situation in which one party in a transaction has more or superior information compared to another is known as Information asymmetry. In banks, this situation arises when the borrower knows more about the prospect of the business (its riskiness) than the bank…
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Extract of sample "Measures that May Reduce the Problem of Adverse Selection and Moral Hazard in Bank"

TITLE: "As a Risk Manager you have been asked to suggest measures that may reduce the problem of adverse selection and moral hazard in your commercial bank." Table of contents Introduction:- 2 Causes and solutions for Informational asymmetry in banks:- 5 Conclusion:- 13 References:- 14 Introduction:- A situation in which one party in a transaction has more or superior information compared to another is known as Information asymmetry. In banks this situation arises when the borrower knows more about the prospect of the business (its riskiness) than the bank. This information asymmetry leads to two main problems: - Adverse selection which occurs before the transaction takes place and can be defined as a process where bad choices are made instead of good ones due to information asymmetry for example bank selecting the borrower who has a higher probability of default that is it is more risky a similar example has been discussed in context of second hand car market by Akerlof in his paper “market for lemons.” Akerlof in his paper showed that adverse selection can generate a vicious cycle that could even lead to closing down of the entire market for that product. Moral hazard occurs after the transaction is complete and can be defined as the chance of the party with more information in the transaction behaving in a way that can cause damage to the other party. E.g. a bank in order to get higher returns may give loans to risky borrowers, hoping that in case risks turn negative, the Central Banker would bail out the bank. Mark V. Pauly in his paper The Truth about Moral Hazard and Adverse Selection(2007) talks about moral hazard and adverse selection in the context of health insurance and how information asymmetry in the insurance sector results in these problems these problems are very similar to what we find in the banking sector we can connect the adverse selection of risky borrowers in banks to risky policy buyer in insurance and moral hazard problem of using these policies excessively in the insurance sector with banks giving excessive loans on collateral as discussed by JP. Niinimäki in his recent paper “The Truth about Moral Hazard and Adverse Selection?” Now let us see the this problem in the current context where the information asymmetry increased between the borrower and the lender and this was due to the downturn that started in the housing market this downturn led to an increase in the default rate in mortgage backed securities (As the value of the houses went south people realised that the loans are more expensive than the current value of the house hence they defaulted.) which in turn led to a reassessment of the whole mortgage backed securities market now the valuation of these loans becomes much more difficult as the risk profile of newly issued loans is different then what we saw in previous loans as a consequence, assets that were previously thought as homogeneous in nature and easy to value suddenly became more diverse and as the degree of informational asymmetry was perceived to widen the investors became much more concerned about a lemons problem. Now the question arises that why did the whole market crash and not just the housing sector the reason as discussed by Charles L. Evans in his speech for the whole market crash and not just the housing market would be that the securitisation process was similar across a wide spectrum of financial liabilities. This may have led market participants to worry about the potential for similar lemons problems to emerge among a much broader class of asset-backed paper, generating contagion across financial markets. In the current situation we can say that the adverse selection issues have been plausibly rampant can we say that a subprime mortgage for sale is a lemon? Or the counterparties in the bilateral trade lemon? In the current situation where the evolution of financial events is taking place at such a great speed many of the institutions that are faced with such uncertainty that they follow worst‐case decision rules that suggests that the uncertainty is Knightian as said by Mr Arvind Krishnamurthy in his paper financial meltdown: data and diagnosis These types of informational problems have plausibly played an important role in the current crisis. Causes and solutions for Informational asymmetry in banks:- Information asymmetry exists in the banking sector since long some of the causes for the same are Information Costs which is the costs associated with gathering and analyzing data so as to produce information needed to select and monitor borrower of funds it is quite expensive to gather and monitor data of the borrowers monitoring essentially means borrower selection, collateral evaluation, contract design, ongoing, monitoring, enforcing repayment, assist in restructuring Allen N. Berger and Robert DeYoung in their paper Problem loans and cost efficiency in commercial banks talks about how important is the efficiency in the information cost to reduce the information asymmetry. Other reason is free riding. Free-riding occurs because entities that do not spend resources on collecting information can still take advantage from the information others have collected. Thereby, the first entity free-rides on the effort of others and is called a free-rider. The example could be that of bank that simply gives loans to a firm as it has got a loan from another bank. Hence, the former bank assumes that latter bank must have done its homework on the borrower and hence must be in good condition. This free-riding problem further worsens the moral hazard problem, as the lenders may simply not monitor the action of the borrower assuming other banks to do the function. This allows the borrower to take on more risks than it would have been allowed if the monitoring had been done. The informational asymmetry can be broken down into two components Precontract Informational Asymmetry where Borrowers may overstate their credit worthiness to negotiate lower interest rates. If lenders can’t differentiate between high and low credit-risk borrowers, interest rates charged will reflect the credit worthiness of the average borrower. As a result, the borrowers most likely to withdraw their applications will be low-risk borrowers. The resulting borrower pool will be of low-quality and high-risk Precontract information asymmetry involves two kinds of information problems which are Adverse selection as discussed earlier adverse selection is a consequence result from firm or individual aim at applying some policy toward one group of people but wrongly benefit other groups. Taking a simple example, in banking industry, bank might wish to raise interest rate for business project that are risky to avoid not being pay back but when the bank raise higher interest rate it is only the most risky borrower who come to as for fund from bank. Why? Because they already known that such high interest rate they will be unable to pay Another classic example of this is The Market for Lemons (Akerlof 1970) Consider a market for second hand cars in which the sellers of cars have more information about the quality of the car than a buyer Given that quality is unobservable, buyers may be reluctant to buy a car if there is a possibility that the car is a “lemon” ( a bad car) Hence, the market for used cars may be thin even though there are many buyers and sellers. Mr Krishnamurthy in his paper comments that there is adverse selection on the location of the most toxic assets which can heighten counterparty risk. Moreover, given uncertainty over valuation of the most complex credit assets, market participants may fear that if they transact they will be left with a “lemon.” Thus this diagnosis is consistent with the lack of liquidity in markets. Informational problems may also be apparent in Knightian decision rules by agents who are faced with new assets that they find hard to value, or a new environment; decision rules that protect against worst‐case scenarios. Thus this explanation is also consistent with the high risk aversion we see in the market. Moreover, adverse selection problems can explain why banks are unable to raise equity finance. Investors will infer that the banks that choose to raise equity finance are lemons. On the other hand this explanation likely overstates the case for liquidity problems, when we know there are true solvency problems. For example, since the capital problems are so widespread, we can imagine that every bank may need to raise equity finance, in which case investor pricing will be based on the average quality of the pool rather than on lemons pricing. Duplicated screening which refers to situations in which individuals can resolve adverse selection at a cost but there is wasteful expenditure of costly screening resources because multiple individuals end up doing the same screening. Madhav V. Rajan and Richard E. Souma in their paper Optimal Information asymmetry talks about the owners payoff, internal information circulation but the most surprising result that they found was that a self-interested manager does not always prefer to maximize his informational advantage. The other part of Information asymmetry is Postcontract Informational Asymmetry and Moral Hazard banks need to monitor borrowers on a regular basis If not bank faces moral hazard costs. Moral hazard costs relate to the risk that borrowers will take actions that are not in the interest of Bank (Jensen and Meckling, JFE, 1976). Example risky projects taken by borrower in this case the upside the borrowers reap and downside is bore by the lender. “All loans are paid if not by the borrower then by the lender” (Kane, 2007) , It is costly to gather and analyze data to monitor borrowers but this has been proved to be very important in recent studies where if monitored efficiently banks can save significant amounts of cost in recovering the loans. It is important and interesting to note that information asymmetry effect is mostly ignored when economy is doing well and vice versa. When economy is doing well, loans are given with least caution, investors invest assuming economy would continue to grow and free-ride on others’ investments etc. whereas the opposite should be the case when times are good the number of opportunities increases and as a result there is large number of projects wanting to cash on the rising economy. As there is large number of projects, the bank should do more homework to separate the good borrowers from the bad borrowers. Similarly, the investors should study the potential risks from each project and invest only in those that match his risk profile. In other words, adverse selection is ignored leading to high chances of moral hazard. As economy slows down, the number of projects decrease and instead of helping to kick-start the economy, banks and other financial intermediaries become highly risk-averse. They refuse to finance even the good projects and as a result the economy slows down further also we see that the policy response to lessen moral hazard in financial markets is one that poses a dilemma to the policymakers. Ideally, the party at fault should suffer the consequences of its earlier actions i.e. policymaker should let the defaulting party either close down its operations or pay a penalty for its actions in the form of losses. This would lead to two things, the party would be more conscious of its actions next time and secondly, it would set an example for others to monitor their actions. But, it is difficult to practice the same also we see that it is easier to penalize the defaulting entrepreneur who invested the loan into a risky project but the same is not the case for other entities especially a bank that has given a loans to risky borrowers who eventually defaulted e.g. if the faulting bank is made to close down, it leads to a bank-run whereby depositors rush to other banks demanding their deposits fearing their banks would also close down. As banks are highly leveraged entities, the entire banking system collapses leading to a possible slowdown in the economy. Hence, it is not always easy for the policymaker to control moral hazard problems. Mostly under political pressure, the banks are bailed out which leads to worsening of moral hazard problem. We have talked about the causes of informational asymmetry now lets talk about how to Reduce Informational asymmetry in Banks the Financial Markets are a critical component of an economy and information asymmetry has to be reduced for it to function smoothly. Measures are taken by both the lender and the regulator to reduce adverse selection these are Reducing costs the Banks can reduce costs associated with precontract informational asymmetry and adverse selection as Banks are more qualified than the individual lender in sorting out the differences in credit worthiness of borrowers and Duplicated screening and information reusability This can be illustrated through the example given below. Consider 100 men and 100 women searching for the ‘‘perfect’’ marriage partner. In order to become fully informed, each woman will need to evaluate each of the 100 men, and likewise for each of the men. Now suppose that each such evaluation (Sampling) results in a fixed cost of say, $25. Then the total cost for all participants to become fully informed would be $500,000 (that is, 2(100 * 100* 25)). Now we introduce the bank (as a broker in this case) action of the broker’s special skills, we assume the evaluation cost per unit remains unchanged at $25. However, the broker will need to examine each of the participants only once. Assuming the information is distributed at negligible cost, the saving due to the introduction of the broker is approximated by $495,000 in the example. Banks can reduce costs associated with postcontract informational asymmetry and moral hazard as the Banks have the benefit of size since Banks hold larger stakes (by aggregating the stakes of small investors) in the borrower; Banks have greater incentive to monitor overcoming the “free rider problem” The larger size of Banks and the fact they are in the business of lending enables them to be more efficient in gathering and analyzing data. Collateral is another way of reducing information asymmetry the lenders often ask the borrowers to submit some form of collateral to mitigate the credit risk. The collateral also reduces moral hazard problem as the lender can sell the collateral in the market in case the borrower defaults. The classic work in this regard is that of Bester (1987) who showed that collateral does away with the need for inefficient credit rationing. Improving Transparency can also help in reducing information asymmetry the regulatory response to lessen adverse selection is to improve transparency in financial markets. The policymakers have made guidelines/regulations across different markets and across market participants to improve transparency in the markets. There are number of examples - disclosure norms, ‘Know your customer’ (KYC) norms, etc. As the financial markets continue to expand with varied financial instruments, addressing adverse selection is a continuous effort and we see new regulations or revisions in existing regulations. Screening and signalling are two ways in which information asymmetry can be reduced at least partially these will be mechanisms that allow the ignorant party to obtain information about the market and level out the information asymmetry. Note that since we are assuming free (and competitive) markets, any mechanism must be voluntary. That is, no one has to reveal her type. Therefore, any mechanism must provide at least some of the people an incentive to reveal their type. The difference between Screening and Signalling is that screening is a cost imposed by the ignorant party and Signalling is a cost voluntarily adopted by the knowledgeable party to distinguish types. Example of screening would be certain amount of cash flow or liquidity ratio or any other test that could distinguish the safe investment from a risky one and depending upon the result the bank can then charge different interest rates from the borrower. On the other hand signalling could be from the side of the borrower example he could be willing to give a higher collateral or a bigger guarantee to the bank this would make the bank feel more comfortable in issuing the loan to the borrower. Various models are used to reduce information asymmetry these are:- Collateral (COL) models given (post-contractual) information asymmetry this is because it aims at reducing the moral hazard. Solution provided by these models is Debt and collateral combined. I.e. The collateral required to issue certain amount of debt. Costly state verification (CSV) models this is also discussed later in the conclusion how states get trapped between popularity and morality. Costly interim information available Solution: Verification by the state and threat for those who don’t abide by the rules Monitoring models: Costly (ex ante) information available but there are ways to reduce the cost through the use of reusable information. Solution: borrower monitors debtor continuously and adjusts the interest as and when the need arises. The adverse selection aspect of the interest rate arises due to the existence of borrowers who have different probabilities of repaying their loans. Banks may use a variety of screening tools to identify good borrowers. According to Stiglitz and Weiss’s (1981) model, the interest rate which individuals are willing to pay may be one of the screening tools. When the interest is high, the average riskiness of borrowers increases, since only those who intend to default of and/or undertake high risks projects will apply. Another way to screen the applicants is to impose collateral requirements. Increasing collateral may have a beneficial effect and lead to lower risks of default, but this is not necessarily the case for all borrows. Wette (1983) argues that the collateral requirements might result in a situation where only firms that have risky projects apply for a loan, since the expected utility of the borrowers is an increasing function of the riskiness of the investment projects. For each possible collateral, individuals can identify the appropriate level of risk T, as the bank imposes collateral requirements the critical value of T growth, since borrowers are willing to take more risk to obtain the required rate of return. Stiglitz and Weiss (1981) assumed that riskiness of the bank’s clients might depend on their current wealth and wealthy individuals are less risk averse; therefore an increase in collateral might attract the particular group of the high wealth risky clients. Nevertheless, Bester(1985) showed that if banks decide on the interest rates and collateral simultaneously rather than separately, obtaining equilibrium without credit rationing becomes feasible. Conclusion:- We can say that the problem of moral hazard and adverse selection originated from imperfect information between economic agents. Then, the solution is to try to create more information and at the same time reducing the cost of getting that information. As we discussed both the causes and solution to these causes one thing that we can deduce from above is that both adverse selection and moral hazard are interlinked. An adverse selection in most likelihood would result in moral hazard e.g. if a bank makes a loan to bad borrower then most likely that borrower would take up projects that are riskier as it has nothing to loose and bring damage to the lending bank. However, even if a good borrower is selected, the intentions may change and he can still bring damage to the bank. Also in the presence of social protection from bankruptcies and in the absence of punishment mechanisms in the post default situations, collateral monitoring will be sub-optimal. In the bad state of nature bail-out costs can be significant for the state or the regulator. We need to develop a regulatory mechanism which helps in mitigating the problem. This has to do with regulatory auditing in the good state of nature when the concerned has resources to pay the fine. The auditing should involve cross checking whether the bank has properly monitored the collateral for successful advances. Under the information diagnosis the best solution is for the government to purchase the most toxic assets which are the cause of the market freeze. By buying all such assets, the government removes adverse selection and Knightian problems. References:- 1. Contemporary Financial intermediation, greenbaum, Thakor 2. Information Problems and Deposit Constraints at Banks, Jith Jayaratne and Don Morgan* November 24, 1997 3. Relationship Banking, Loan Specialization and Competition, Robert Hauswald Kelley School of Business, Indiana University, Robert Marquez Robert H. Smith School of Business, University of Maryland 4. ASYMMETRIC INFORMATION:THE CASE OF BANK LOAN COMMITMENTS, James E. McDonald 5. Understanding Sub-Prime Crisis in Information Asymmetry Framework, Amol Aggarwal 6. Financial Institutions and Markets‎ - by Jeff Madura –P. 16-18 7. Santomero, A.M. (1997), Commercial Bank Risk Management: An Analysis of the Process, The Wharton School of the University of Pennsylvania, Philadelphia, PA, . 8. http://www.creditriskmgt.com/ 9. “Credit Risk in Banking” – May 1-2, 1997, http://www.rba.gov.au/PublicationsAndResearch/Bulletin/bu_nov97/bu_1197_3.pdf 10. Collateral Monitoring and Banking Regulation, Sugata Marjit; Indrajit Mallick 11. Greenbaum, S.I., Thakor, A.V. (1987), "Bank funding modes: securitization versus deposits", Journal of Banking & Finance, Vol. 11 pp.379-401. 12. Remarks by Charles L. Evans in his speech at Swiss National Bank Research Conference 13. “The Lemon market” by Akerlof. 14. The Financial meltdown by Arvind Krishnamurthy, 15. Remarks by Godfrey, Daniel from http://www.coursework4you.co.uk/godfrey.htm. 16. Adverse Selection in the Credit Card Market, Lawrence M. Ausubel 17. Do Customer Relationships Affect Credit Conditions in an Adverse Selection Context? An Empirical Study of the Tunisian Banks’ Behavior, Salma Hachicha Elleuch 18. http://www.ids.ac.uk/go/about-ids/news-and-analysis/february-2009-news/toxic-assets 19. Banks and the Financial Structure http://www.econ.iastate.edu/faculty/bhattacharya/documents/BANKS.pdf 20. Moral hazard meets adverse selection, by John Quiggin. 21. Optimal Information asymmetry by Madhav V. Rajan and Richard E. Souma 22. Problem loans and cost efficiency, byAllen N. 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