Consumer Compliance Outlook
Improving and Using HMDA Data in Your Compliance Program
The deadline for covered institutions to submit their 2009 Home Mortgage Disclosure Act (HMDA) data is March 1, 2010. Given the importance of HMDA data to a number of supervisory processes, including examinations and applications, as well as for public policy purposes, it is essential that HMDA data be submitted accurately and on time.
This article outlines four steps institutions can take to help ensure that their HMDA data are accurate. It also discusses various ways in which institutions can use their HMDA data in assessing fair lending compliance and CRA performance. The steps can be adapted according to the size of the institution and the formality of its compliance program.
IMPROVING HMDA DATA
Step 1: Controlling the Input
The compliance officer should periodically evaluate HMDA data to ensure that all relevant product lines are included and that the data include all loan applications that are originated, denied, or withdrawn. Examiners often identify product lines inadvertently omitted from the loan application register (LAR). For example, residential loans secured by multi-family dwellings are often underwritten and serviced by an institution's commercial lending area and must be included on the LAR. Staff in the commercial lending area may not be familiar with or aware of HMDA reporting requirements. As a result, commercial multi-family loans can inadvertently be omitted from the bank's HMDA LAR.
The compliance officer should also identify data that have been subject to a quality control or self-monitoring effort. Those product or business lines that have not been subject to self-monitoring should receive enhanced scrutiny during the data review.
It is important to note that effective October 1, 2009, the Board amended Regulation C, the implementing regulation for HMDA, to define a ratespread loan as a HMDA loan subject to Regulation Z whose annual percentage rate exceeds the average prime offer rate for comparable transactions by 1.5 percent for first-lien loans or 3.5 percent for second-lien loans.1 This revised rate-spread reporting test applies to loans for which applications are taken on or after October 1, 2009 and for all loans consummated on or after January 1, 2010 (regardless of their application dates). This new, lower benchmark will likely increase the number of rate-spread loans that institutions report on their HMDA LAR. The revised rules do not apply to loans for which applications were taken before October 1, 2009 and that were consummated in 2009. For those loans, HMDA reporters are required to identify first- and second-mortgage liens that exceeded the yield on comparable Treasury securities by 3 percent for first-lien loans and 5 percent for second-lien loans, respectively.
Step 2: Minimizing Errors
As institutions focus on improving the accuracy of their HMDA data, they should be aware of common errors with the following data fields: (1) borrower's income, (2) rate spread, (3) loan purpose, (4) property location, and (5) loan amount. With the exception of the borrower's income field and the rate-spread field, these issues typically arise because of errors recording data in the field rather than omitting them.
For the borrower's income field, §203.4(a)(10) of Regulation C requires that the borrower's gross income relied on in making the credit decision be reported. However, institutions frequently report the borrower's net income in this field. For the rate-spread field, some institutions fail to report data because the loan administration employee does not have a good understanding of the definition of a rate-spread loan. Institutions must be careful to employ the new definition of a rate-spread loan, as discussed in Step 1, which will likely increase the number of rate-spread loans banks report on their HMDA LAR.
Internal controls are an important tool for identifying and correcting errors in HMDA data. The scope of the controls depends on the bank's risk assessment of the HMDA data submission. For less complex programs, or for well-developed programs, institutions may be comfortable with their data collecting and reporting methods and may not require additional review. On the other hand, larger, more complex institutions, or institutions with a history of reporting errors, are at greater risk of HMDA errors and should ensure that data not subject to self-monitoring are comprehensively reviewed prior to the annual March submission. Even data subject to self-monitoring should be spot checked, as an internal control, to verify that the selfmonitoring is working.
Step 3: Submitting the Data
Compliance officers should allow themselves sufficient time to prepare the HMDA LAR before the March 1 submission date. Starting the process of reviewing the HMDA data in January should ensure sufficient time to correct any noted errors before submitting the data on March 1.
After the LAR is submitted, Federal Reserve Board staff review the data in late March through early April and may identify possible reporting errors. Institutions that fail the quality edit tests are contacted to resolve reporting issues. Board staff inquiries about HMDA data issues require immediate attention, and the HMDA LAR is not complete until all edits have been verified and/or resolved by the institution. The compliance officer should identify the business units or product lines from which the submission errors originated because this affects the risk analysis, training, and self-monitoring program for these respective areas.
Step 4: Training Staff
The compliance officer should identify training gaps based on the results of data review activity. For example, if geocoding or reasons for declination pose data-quality problems, training should focus on these problem areas. Training should also be used to update employees about regulatory changes related to the filing of HMDA data, such as the recent Regulation C amendment to the definition of a rate-spread loan. Employees with input access to the HMDA LAR, and/or employees involved in self-monitoring and other review activities, require the most training, but all employees involved in the collection of LAR data need periodic training as well.
USING HMDA DATA TO ASSESS FAIR LENDING COMPLIANCE AND CRA PERFORMANCE
The compliance officer should evaluate HMDA data from both a fair lending and CRA perspective. This evaluation should mirror how HMDA data are used by examiners for CRA and fair lending evaluations. Many banks have complex data analysis tools to evaluate lending patterns. However, even without using robust data analysis tools, the compliance officer can perform a simple and effective analysis by using spreadsheets to sort HMDA data. For example, the compliance officer can sort HMDA data by census tract to determine the geographic dispersion of lending among the various census tracts in the institution's assessment area, including low- and moderate-income tracts.
The compliance officer can also review the borrower income distribution. If the data indicate disparities, the compliance officer should communicate this to management. A HMDA data sort based on declined applications could reveal correlations with race, sex, or some other prohibited basis. The compliance officer should investigate and address any observations in a proactive manner with management, who could examine the data more closely and perhaps consider increased outreach, second review programs, or other appropriate measures.
Finally, the compliance officer should always compare the data to the most recent CRA performance evaluation. This simple step can show the compliance officer how HMDA lending activity affects the institution from a CRA perspective.
Based on the results of the data evaluation, the compliance officer should update the institution's HMDA, fair lending, and CRA risk assessments. If, for example, the HMDA data revealed numerous errors in accuracy, the compliance risk assessment should be updated to identify a weakness in the control environment for inputting HMDA data. The lowered confidence in input controls would result in a higher residual risk in the activity, with more control resources being applied to that activity to correct the weakness. Similarly, a data evaluation that showed that the institution was lending to all census tracts and income levels in its assessment area (including low- and moderate-income) could reflect increased confidence in the control environment and lower residual risk in the CRA program and result in correspondingly fewer resources allocated to that activity.
In any case, the compliance officer should focus resources, such as training, monitoring programs, and increased testing, toward activities that have demonstrated either data-quality or lending patterns that do not fit the institution's stated goals and objectives for CRA and fair lending. By linking the application of resources to areas of demonstrated risk exposure, the compliance officer achieves a more efficient use of limited resources and lowers the institution's compliance risk profile.
Following the steps outlined in this article will help compliance officers enhance their HMDA reporting programs and meet HMDA's regulatory requirements for their institutions. Specific issues and questions should be raised with the consumer compliance contact at your Reserve Bank or with your primary regulator.