The New Lending System - Putting common sense into compliance and risk assessment

Lenders must recognize that the time has arrived for them to re-examine how they make loans and the basis for their policies. In particular, they need to consider how much weight thier models place on borrower characteristics and habits, loan collateral factors and the terms and conditions under which the loans are being made. Let me cite some specifics.

During my 35-year career in credit and banking I have reviewed literally hundreds of scorecareds for a variety of types of loans in many different industries. I never once saw a system where renters were given anywhere near as many points as borrowers who owned, or were buying, their homes. If I may digress for a moment, growing up in San Francisco, my folks never owned thier home - we always rented. As a result, we were never vulnerable to real estate depreciation, the cost of maintaining a home, property taxes, or causalty insurance (in San Francisco, earthquake insurance is very expensive and has huge deductables). In his entire life, my Dad was not exposed to the risks and costs of owning a home and he never missed a payment and always paid in full. Nonetheless, according to the models, we were less creditworthy.

Fact: Given today's real estate market, and the trend of borrowers to de-leverage, it is doubtful that any credit scorecard developed over the past several years is still valid. The problem is not just because we find ourselves digging out of an economic crisis - although that would probably be reason enough. The time when static models using fixed point assignements to score and qualify loan applicants has passed. In today's, and tomorrow's, environment, many scorecards would be obselete by they time they were constructed and implemented!

The changes we are witnessing are structural in nature and they will continue to evolve for months and years to come. The only real way to cope with such a fluid situation is to develop and deploy an adaptive model. In contrast to a credit scoring model, an adaptive model would be able to continuously refresh its information based upon observed loan performance and also incorporate the most recent trends relative to combinations of primary lending factors (i.e. the Five C's of Credit) occuring in the loan applicant pool. Furthermore, the bigger picture reveals that today's credit scoring models and systems take information out of context--that is they fail to first construct a comprehensive view of the borrower before attempting to evalue his/her application for a loan. For example:

1) Owning a home is different from buying a home (i.e. owning a portion of the home). A key aspect is the borrower equity position in the property and its current appraised market value, and percent appreciation/depreciation in value over time.

2) Another common factor is years on job, where the magic number is 24 months or greater. Unfortunately, this ignores the reason for a job change and the differential in salary. Why should someone be considered a higher risk for taking a job where they will earn more money?!

3) Delinquent payments is another area that has been over-emphasized. Why should a consumer have to wait 24-36 months for the record of a delinquent payment to roll off their credit file when tha cause, perhaps illness or job change, has been effectively been remedied ? Must the punishment continue without just cause?

4) Suppose a model determines that for every ten percent increase in the payment-to-income ratio when it exceeds a threshold percentage (say 15 percent), the likelihood of loan default will double. Certainly one has to question if that result holds true for everyone. Would the same result be true for borrowers living paycheck-to-paycheck with no savings versus borrowers having little or no other debt with a high savings rate?

Empirical results reflected in loan underwriting modles that seem to make sense in general, fall apart when put into specific context. Furthermore, when times are good, lenders tend to under-estimate the risk, and when times are bad, they tend to over-estimate the risk associated with making a loan. What lenders need is a system that objectively and comprehensively allows them to accurately assess the risk of making a loan no matter where they are in the economic cycle. Scorecards, and other "rear-view" models will always take the lender, and the borrower, over a cliff when a recession hits. They are incapable of spotting turning points. In contrast, a Comprehensive Credit Assessment Framework (CCAF) that is forward-looking, adaptive, transparent, and that leverages reason in addition to all relevant data, can provide lenders with exactly what they need to properly assess credit risk, qualify borrowers for affordable loans, and help get the nation's economy back on track!