All banking professionals are familiar with the acronym CAMELS (Capital Adequacy, Asset Quality, Management, Earnings, Liquidity, Sensitivity), the risk rating system used by bank regulators. HMDA data can play a role in this rating system. Specifically, I’d like to focus on the “A”, Asset Quality. Using HMDA data, we can uncover the unknown risk factors associated with mortgage assets that a company may encounter which could lead to capital adequacy adjustments. Capital requirements needed to protect against performance risk is beyond the scope of my discussion. However, presenting an alternative approach to asset management using HMDA data is worth discussing.
Ignoring fair lending and regulatory risks (traditional HMDA analysis has this covered), I’ve come up with a top-line evaluation framework to identify “Asset Quality” risks that should be controlled and a part of stress testing. Fortunately, I use LendingPatterns™, a software tool that has transformed a mountain of raw data into informed analysis with easy to generate reports to identify critical areas of risk exposure.
My risk avoidance mantra is to ensure the best by assuming the worst.