Freddie Mac recently released a study Research Note pdf based on their analysis of appraisal valuations. It’s worth taking a look. The following sentence from the report summarizes the findings:
Our preliminary modeling results suggest that even when taking structural and neighborhood characteristics into consideration, a property is more likely to receive an appraisal lower than the contract price if it is in a minority-minority tract (MMT).
With HMDA, we cannot see whether the appraisal price is lower than the contract price. We only see the appraised value. However, there is a related concern which one can analyze with HMDA data and using LendingPatterns™, and that is whether applicants in MMTs are more likely to be denied on the basis of collateral than applicants in majority-White census tracts. We know that insufficient collateral value is not the only reason for using the collateral denial code.
Note that collateral may be denied for zoning issues, environmental issues, physical deficiencies, and so on, but focusing on the collateral denial reason code is as close as we can get with HMDA to the issue of differences in appraisals.
How to Determine Collateral Denial Risk
The way the LendingPatterns™ analysis would work is as follows. You will see the differences between denial rates based on insufficient collateral for applications located in MMTs and those from majority-White majority tracts. LendingPatterns™ will test these differences for statistical significance using a z-test. Results that come back with a p-value less than 0.05% should be treated as either a moderate or high fair lending risk. As a follow-up, compliance staff should investigate to determine if appraisers are properly and impartially developing property estimates.
I will add to the conversation some analysis I did for all lenders. The top metro area for collateral denials is Chicago-Naperville-Evanston, IL (16984) Metropolitan Division. Within that area, the proportion of applications denied on the basis of collateral is statistically significantly higher in MMTs than in majority-White tracts. Similarly, lenders can analyze their own data across their entire footprint or within specific markets.
How we can help you
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