Traditionally, underwriting focused on applying a static set of guidelines to determine an approve/reject decision. Most of the rules were developed when underwriting was almost exclusively a manual process. Although the industry has embraced the technological improvements offered through standardized credit scoring and Automated Underwriting Systems, recent experience has shown that approach is inadequate to predict delinquency or default.
A significant part of the weakness in the traditional underwriting process is an inability to fully track “layered risk.”
Volumes of the data are collected, but not always analyzed or applied fully. One way to address this issue would be to convert the process to a weighted score on a per-loan basis.
For example, debt-to-income ratios for approval purposes are calculated using gross debt-to-gross income.
Take the case of two borrowers at or near maximum DTI for the program. A borrower whose gross income is a base salary of $10,000 would be treated the same way as a borrower relying on $2,000 base salary, which is to say $5,000 in commission, $2,000 on a second job and $1,000 net rental income.
Yet in the above example the second borrower is arguably subject to greater risk due to economic forces beyond his control.
Understanding what portions of the income are subject to economic factors would allow for more detailed tracking of loan performance based on these factors.
Over time, the performance data gathered would allow refinements to existing guidelines based on actual results.
Likewise, the current system fails to take advantage of existing improvements in technology in favor of outdated manual verification processes. Taking advantage of available direct data connections to employers, banks and creditors would reduce chances of fraud, thereby reducing losses.
Authority to grant exceptions to standard guidelines was normally based on job title or position. Subsequent tracking of the performance of loans with exceptions to guidelines varied from company to company and was rarely accessible to outside investors.
Given the above, the conclusion is that analysis of the actual subsequent performance of loans approved based on exceptions will help to further refine future underwriting standards.
Chad Burance is head of NewOak Solutions.