I understand your thinking, but what I donâ€™t think you realize is that the type of judgments and research which you think might make sense for mortgage underwriting have been severely inhibited by the financial regulators. ECOA (equal credit opportunity act) and concerns about so called red-lining have made the regulators virtually eliminate all credit criteria that canâ€™t be coded into a machine. The main push behind this effort has been due to regulators worry that non-algorithmic decision making is just a mask for rejecting minority and underprivileged applicants. This is especially applicable to any policy which attempts to be forward thinking. For instance, if an underwriter were to put in a policy discouraging loans to folks in the struggling construction industry, the general counsel would immediately reply â€?show me the precise data that says that there is a historical statistical correlation between construction employment and loan default rates, or else we are going to be accused of implementing a policy of â€?disparately impactingâ€™ Hispanics.â€? One of the consequences of nervousness regarding â€?disparate impactâ€? has been the increased use of statistical score models in consumer underwriting. In terms of how business is done, this reduces reliance on a semi-skilled workforce that leverages relationship, intuition, and local environmental factors and opens up new opportunities for technical folks good at mining data, recognizing data relationships, and creating logistic regression models and so forth. And yes, this does encourage centralization of consumer banking and the development of a highly paid and (maybe) skilled technical manager set in underwriting.
The main downfall of this approach which relies on historical data patterns is that it is easy to lose sight of what is really happening to consumer balance sheets and that recent past results may be anomalous. So in the past situation where consumers could roll over debt due to rising home prices and the increased availability of home equity loans, the banksâ€™ models were â€?trickedâ€? by borrower profiles who were repaying their loans but yet were in unsustainable consumption and borrowing patterns. And because the top underwriting brass are absorbed in their models and far from the realities of the borrowersâ€™ â€?realâ€? situationsâ€“not being able to put the full picture together while sitting across the table from borrowers dailyâ€“a realistic picture that might have stimulated a more conservative underwriting approach did not force itself on credit committees until the loans (thus the data) started going bad.
And by the way, you can see clear proof of the regulatory impact of ECOA laws demonstrated by their non-applicability in small business lending. Relationship and judgmental underwriting remain prevalent in small business lending, even for comparable loan sizes being made to consumers.The last point Iâ€™ll make is that the stupid money behind securitization business ruined everything anyway. Try adhering to rigorous underwriting processes and reasonable pricing/underwriting criteria at a bank while finance company next door has agreements to have all of its poorly priced and researched loans purchased the next day no questions asked. The banks are then faced with the decision to either put in an application process and pricing structure which no consumer will actually vie for (thus losing all market share) or following the leader. This is why tough handed regulation is needed to keep the industry in check because all can be led astray too easily. The follow the leader psychology is the source of every financial panic.