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Benefits of Interagency Data Sharing

Access to timely and meaningful data is critical to Ginnie Mae’s Mortgage-Backed Securities (MBS) program. Traditionally, Ginnie Mae’s approach to data collection has been to solicit data directly from its issuers. One of Ginnie Mae’s most significant undertakings has been implementing a Mortgage Industry Standards Maintenance Organization (MISMO)-compliant Pool Delivery Dataset for issuer reporting of single-family pool issuances. The dataset requires issuers to deliver pool and loan data via an industry data standard, with net new data requirements for digital mortgages and other special products.

Most recently, Ginnie Mae has explored alternative avenues for obtaining data. One successful strategy was partnering with insuring agencies— Federal Housing Administration (FHA), U.S. Department of Veterans Affairs (VA), and U.S. Department of Agriculture (USDA)—that agreed to allow Ginnie Mae to use their data on negotiated terms. This type of agreement, usually formalized as a memorandum of understanding, establishes the permissible uses and protocols for sharing, protecting, and storing data.

The benefits of interagency data sharing are extensive. For one, data sharing allows different agencies to access and use the same information, reducing the duplication of efforts and the need to start from scratch. Second, data sharing enables quicker response and coordination among agencies during emergencies, such as natural disasters or adverse market occurrences.

Specifically for Ginnie Mae, sharing data elevates the organization’s ability to see a comprehensive view of its MBS portfolio, leading to better decision-making, programs, and policies that mutually benefit Ginnie Mae and the insuring agencies and public they serve. Ginnie Mae’s data-sharing agreement with FHA is a great example of reciprocal benefit. Through its agreement with FHA to obtain demographic data, Ginnie Mae can match its pool and loan data to FHA borrower characteristics to uncover rich insights that inform strategies for managing HUD’s mission. This “One HUD” collaboration is mutually beneficial to both FHA and Ginnie Mae, because it supports evidenced-based decision-making around Ginnie Mae’s MBS program that guarantees the availability of capital for FHA loans.

One of Ginnie Mae’s most impactful uses for shared data has been its Low-to-Moderate Income (LMI) disclosures. Through data-sharing agreements, Ginnie Mae negotiated using FHA, VA, and USDA borrower income data to disclose LMI metrics at the MBS level. This disclosure enhancement is a major step forward in Ginnie Mae’s environmental, social, and governance efforts.

From an operational standpoint, the most significant quantifiable benefit to agency data sharing is the time that can be saved. For Ginnie Mae to initiate new data collection, it must comply with the Paperwork Reduction Act requirements (PRA), calling for agencies to seek approval from the Office of Management and Budget before collecting information from the public. Agencies must demonstrate that the information they collect is necessary, useful, and the least burdensome to respondents. The approval process, which includes public comment and review, can take 6 to 9 months. Issuers’ development to the new data requirement and Ginnie Mae’s technical activities to ingest and process the new data can further extend the implementation timeline.

Rather than initiate the PRA process for direct data collection, Ginnie Mae can, when appropriate, work with insuring agencies to use their data. Because Ginnie Mae already has existing data agreements with all insuring agencies, a request for new data from an insuring agency can often be negotiated as an amendment or update to an existing agreement, which makes for a streamlined and nimble path to closing critical data gaps. In most cases, the shared data have already been subject to data verification processes, increasing the likelihood of accuracy and reducing the possibility of errors and discrepancies.

It is important to note that both parties to the agreement must mutually and carefully concur on the appropriateness of use (if the data can be shared at all), especially when data are sensitive. In all cases, Ginnie Mae works with insuring agencies to balance the benefits of data sharing with concerns about data privacy, security, and ethical risks.

Ginnie Mae has made great strides in building an information-rich data program that optimizes operations and analytics. Agency data sharing has become a successful part of that overall data strategy. As Ginnie Mae continues to work with its insuring agencies, new data-sharing partnerships will certainly emerge that advance common goals for affordable homeownership. ​​