Tuesday, October 13, 2009

Credit risk assessment for loan decisions: a new approach

1:37 AM Posted by: Slamun Atlanta 0 comments

Risk expert Myles Shevlane believes a number of factors were to blame for the sub-prime mortgage crisis, but a significant root cause factor was the reliance on conventional credit scoring and underwriting practices. The introduction of modern automated underwriting systems along with advancements in analytics, such as use of credit scoring and risk-based pricing, gave the banks a false level of security and encouraged a rapid expansion in sub-prime lending. So now banks face a dilemma: whether to return to a historical human-based lending assessment process or look to stick with the current highly automated scoring-based approach. It has been recognized that development in automated underwriting technology has played a significant role in encouraging lenders to penetrate deeper into the sub-prime loan pool. To a large extent, sub-prime lenders believed any additional risk they were taking on was covered using advances in credit scoring and scoring system policy overlays. This enabled them to effectively price that risk and charge borrowers on the basis of their fully quantified creditworthiness. This has contributed to the rapid development of the sub-prime loan market1 and has created greater access to home ownership for some segments of borrowers, such as low-income and minority households.
The magnitude of the current crisis makes it abundantly clear that there is significant room, and need, for improvement in current credit assessment approaches. There are two fundamental problems that contributed to the weakened underwriting standards and degraded loan quality. First, credit scoring has not done an adequate job of assessing risk in the subprime mortgage market. The majority of the sub-prime mortgages underwriting systems were not, in fact, capturing ‘the full range of risk factors in the market’.2 In particular, their conventional risk models were applied to non-conventional loan products, which are associated with different payment terms and behaviour. Improper use of credit scoring and automated underwriting presented incomplete risk analyses and weakened underwriting standards and policy. The end result has been a drop in loan quality.3 Lenders are now re-evaluating their lending procedures and tightening their lending standards in an effort to improve loan quality. This effort will inevitably involve underwriting technology improvement, which includes strengthening process integrity and upgrading scoring and automated underwriting system components. The system component upgrade will entail evaluation of the adequacy of data, current modelling practices and risk measurement frameworks. Second, there is a blind spot in today’s underwriting practices. That is, current practices over-rely on quantitative models and automated underwriting systems. Technology has a vital role in boosting efficiency and helping to measure and monitor credit risk. The models have their place and part to play. However, we need to control the models instead of the other way around. Loans first need to be properly classified and then risk-rated. Today’s process has that back to front. New and improved ways for addressing limitations of credit-scoring systems and evaluating credit risk will be in demand. Simply recalibrating existing models and
throwing more of the same technology at the problem will not fix it.


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