On Compliance: HMDA outliers

first_img 6SHARESShareShareSharePrintMailGooglePinterestDiggRedditStumbleuponDeliciousBufferTumblr Use a statistical approach to determine whether your credit union’s data is likely to draw a fair lending review.by: Dana GinsburgThe term “HMDA outlier” is used by the National Credit Union Administration and other regulatory agencies to describe part of their criteria for selecting financial institutions for fair lending reviews. Unfortunately, it can be a daunting task for a compliance officer to get a handle on the CU’s Home Mortgage Disclosure Act data and answer the question: “Is my credit union a HMDA outlier?” This article shares a straightforward methodology, using public HMDA data, to identify HMDA outliers.NCUA’s 2013 Fair Lending Examination Program and Compliance Assistance states: “Federal credit unions that are HMDA outliers and demonstrate the potential for higher fair lending risk are subject to a fair lending exam in accordance with the FFIEC exam procedures.” In that guidance, NCUA also states that it will review the credit union’s annual HMDA report, and if that review indicates the credit union’s lending practices fall outside the normal range with regard to pricing, denials, withdrawals, or lending terms (when compared to other financial institutions) the credit union will be considered a HMDA outlier.A Data-based ApproachIn keeping with the NCUA guidance, ComplianceTech suggests using a statistics-based approach to determine whether a federal credit union is a HMDA outlier. This approach computes an average score (such as for denial rate, pricing and lending term) for a group of “peer” lenders, and then determines which of the individual lenders’ scores are far enough from the average to be considered an outlier. continue reading »last_img


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