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How the Fico or credit score impacts on consumers - Research Paper Example

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A lot of consumers don't appreciate the importance of personal credit scores and how it impacts on their daily lives. Some don’t know that credit scores are available and accessible online. A credit score can have a say on what a consumer is or is not able to do…
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How the Fico or credit score impacts on consumers
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? Affiliation A lot of consumers don't appreciate the importance of personal credit scores and how it impacts on their daily lives. Some don’t know that credit scores are available and accessible online. A credit score can have a say on what a consumer is or is not able to do. For instance, it can determine what one pays for leasing or auto financing, credit card rates, car insurance and mortgages. It can affect things we may take for granted like whether one gets a job or rent an apartment. When applying for credit, the lenders want to know your credit risk level. Buyers or consumers with poor credit (high credit risk level) are turned away by the lending institutions. The current tightening up of the loan and mortgage market makes the situation worse. Customers with less than a 700 credit score are being turned away by car dealers. It is now more important than ever to have a good credit score. Keywords: Credit score, FICO®, consumers, lenders. What is a Credit Score? A credit score is a number that summarizes your credit risk, based on your credit report at a particular point in time (FICO Booklet). Credit reports and credit risk levels can be evaluated using your credit scores by the lenders. Since it’s just a single number, the lenders don’t have to read through the whole credit history report. It is an indicator of how likely you are to pay your bills. Consumers should be aware that lenders use other information to determine one’s creditworthiness along with the credit scores. These include the debt-to-income ratio and job stability. In the United States, credit reports and credit scores are created by three credit reporting agencies namely, Equifax, Experian and TransUnion. Each has its own scoring model. Equifax has the BEACON score, Experian has the Experian/Fair Isaac Risk Model and TransUnion has the EMPIRICA score. Data about a consumer is collected independent of the other agencies, meaning that information can differ across the three firms. Lenders can get the consumer credit scores from the three firms and estimate an average credit score. FICO® scores, created by the Fair Isaac (FICO) Corporation, is another popular scoring method. Its scale ranges from 300 – 850. Majority of people score between 600 and 800. A high score is preferred by the lenders. For instance a score of 720 will get you favorable interests on a mortgage, according to Fair Isaac Corporation. The following table shows how credit scores break out for the American public. Credit Score Percentage 499 and below 2 percent 500 – 549 5 percent 550 – 599 8 percent 600 – 649 12 percent 650 – 699 15 percent 700 – 749 18 percent 750 – 799 27 percent 800 and above 13 percent Components of the FICO Score A credit report contains different types of credit data. It is this data that is used to compute the FICO Scores. Data is grouped into five categories as illustrated below. The percentage represents the importance of each category in computation of your FICO Score. Source: Fair Isaac Corporation Website Items considered in the payment history are account payment information (credit cards, mortgage and retail accounts), Public records (legal suits, bankruptcy, liens and judgments) and delinquency, Severity of delinquency, recency of delinquency and adverse public records, past due items on file and accounts paid on time. Amounts owed is checked for the amounts owing on the specific types of accounts, number of accounts with balances, proportion of credit lines used and proportion of installment loan amounts still owing The line of credit history is concerned with the time duration since the accounts were opened and other account activities that have taken place. New credit category is used to check recently opened accounts, recent credit inquiries, last duration of credit inquiry and positive credit history re-establishment following repayment problems Lastly, types of credit used category looks at the recent information on the various types of accounts, be they credit cards, mortgage and retail accounts. Importance of a credit score to the consumers and credit providers It is very important that each consumer knows his credit score. A 2005 survey by the Consumer Federation of America and the Fair Isaac Corporation found out that about 49% of 1,103 consumers polled don’t know that credit scores show the credit risk level of a consumer. Many consumers or borrowers assume that credit scores benefit only the lenders but this is not true. For instance, credit scores help to reduce favoritism because they give an in-depth analysis of a consumer’s creditworthiness. This enables lenders to focus only on information that relates to credit risk and avoid the personal prejudice of a credit analyst (Fensterstock, 2005). In the Equal Credit Opportunity Act, variables of blatant discrimination such as sex, race, age and religion are not to be included in the credit scoring models. Only unbiased information that is predictive of payment performance is incorporated in the models. Credit scoring also helps to increase the speed and regularity of the loan application process and permits the automation of the lending process for the consumer (Rimmer, 2005). In this case, it significantly reduces the need for human involvement on evaluation of credit and the cost of processing credit (Wendel & Harvey, 2003). Financial institutions can compute the risks associated with giving credit to a particular borrower faster with the help of the credit scores. A study on a Canadian bank by Leonard (1995) found that the time for processing a loan application was shortened to three days up from nine days after credit scoring was used. Time saved here can be used to address more important issues. Banaslak and Kiely (2000) found out that with the assistance of credit scores, financial institutions are able to make quicker, improved, and higher quality decisions. With this, credit scoring can also improve the allocation of resources toward the “first best equilibrium” (Jacobson & Roszback, 2003). Additionally, credit scores can assist financial institutions decide the interest rate to charge their consumers and to price portfolios (Avery et al., 2000). Higher-risk consumers are charged high interest rates and vice versa. Credit providers can also determine the credit limits to set for borrowers based on the consumers’ credit scores (Sandler et al., 2000). These help consumers to control their accounts more efficiently and valuably. In relation to the above, credit scoring models have enabled the growth of the sub-prime lending industry where sub-prime consumers are those with poor credit records and thus high credit risk. Most of these consumers may not meet the prerequisite for usual financing because of credit impairment, difficulty in validating their income, or missing data in their credit histories (Quittner, 2003). One of the main factors in the advancement of sub-prime lending has been automated underwriting, which permits sub-prime mortgage loans to be packaged and sold as investment securities. The early success of specialized financial establishments in this market has motivated additional financial institutions to go into the sub-prime lending market, which is expected to grow as technology in credit scoring presses forward (Perin, 1998). More credit scoring models are being developed because of advancements in technology. As a result, credit card issuers are able to make use of the information generated from the models to put together better collection strategies, thus using their resources more effectively (Cundiff, 2004). , Recovery rates averaged 15.9% in 1999, up from 12.1% in the previous year and 9.1% in 1997 Lucas (2000). Lastly, the insurance industry has used credit scoring to restructure the insurance application and renewal procedures. Credit scores can help insurance companies to make a better forecast on claims and hence to manage risk more efficiently. Pricing of insurance packages is more accurate too. This allows insurance businesses to offer more insurance coverage to more consumers at a more reasonable cost, respond quickly to market changes and increase their competitive edge (Kellison & Brockett, 2003). Criticisms of the FICO Score and other credit scores Credit scores are largely reliable and inexpensive but they have attracted criticisms over time. The accuracy of FICO in predicting delinquency has gone down in recent times, according to a Fitch Study. Unforeseen problems have weakened the credit scoring system, which is relied heavily by lenders and investors in making their decisions. A 2004 survey from the Federation of State Public Interest Research Groups found that 79% of all credit reports contained errors. FICO scores are also being blame for the problem of the subprime mortgage. FICO’s accuracy in predicting the probability of debt repayments was questioned in 2006, at the end of the housing boom. Some institutions, for instance Golden West Financial, have disputed the FICO score and now use a more costly analysis of potential borrower’s possessions and employment history before processing loan applications. It is also said that Fair Isaac approach to credit scoring has not changed much since its inception in 1956. It was overhauled in 1989 and the formula has since remained the same. References Avery, R.B., &, Canner, G.B. (2000). Credit scoring: Statistical issues and evidence from credit-bureau files. Real Estate Economics, 28(3), 523-547. Cundiff, K. (2004). Closing the loop: How credit scoring drives performance improvements along the financial value chain. Business Credit, 106, 38-42. Fensterstock, A. (2005). Credit scoring and the next step. Business Credit, 107, 46-49. Jacobson, T., &, Roszback, K. (2003). Bank lending policy, credit scoring and value-at-risk. Journal of Banking and Finance, 27, 615-633. Kellison, B., & Brockett, P. (2003). Check the score: credit scoring and insurance losses: Is there a connection? Texas Business Review Special Issue, 1-6. Leonard, K.J. (1995). The development of credit scoring quality measures for consumer credit applications. International Journal of Quality and Reliability Management, 12, 79-85. Lucas, P. (2000). Why recoveries are on the rise. Credit Card Management (October) 71-72. Perin, M. (1998). Risky business: sub-prime market growth attracts host of new players. Houston Business Journal, 67, 456-459. Rimmer, J. (2005). Contemporary changes in credit scoring. Credit Control, 26, 56-60. Quittner, J. (2003). Credit cards: sub-prime’s tech dilemma: with delinquencies and charge-offs on the rise, the industry examines the role of automated decisioning. Bank Technology, 16, 19-23. Sandler, A. L., S.E. McGinn, & Barloon, J.L.. (2000). Fair lending scrutiny of credit score-based underwriting systems. ABA Bank Compliance (March/April), 38. Wendel, C., &, M. Harvey. (2003). Credit scoring: Best practices and approaches. Commercial Lending Review, 18(3), 4-7. Read More
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