How technology can help mortgage lenders combat repurchase risk

When individual mortgages are originated by lenders like banks or credit unions, they may
bundle groups of these mortgages together into financial vehicles called mortgage-backed
securities (MBS) that are then sold to investors on a secondary market.

This allows investors to gain exposure and returns from the mortgage market, while the lenders gain immediate capital to issue new mortgages.

However, if a mortgage in an MBS bundle defaults or contains errors, there is a “repurchase
risk.” This means the entity that assembled and sold the MBS is obligated to buy back any non-performing or defective mortgage loans. This ensures their bundle retains its credit rating and market value.

If too many mortgages default, the MBS can lose significant value. As a result, lenders aim to include reliable mortgages in their securities and have technology to assess credit risk, detect fraud, and monitor performance — in order to avoid forced buybacks or losses for investors that diminish market confidence. In Q1 of 2023, there were $459 million in repurchases on about $68 billion in Fannie Mae loan-acquisition volume, or a 68 basis-point repurchase rate.

Emerging technologies are proving essential to reducing repurchase risk and improving
confidence in mortgages sold on secondary markets, enhancing transparency and security of loan data transfer to minimize errors.

For example, automated underwriting powered by artificial intelligence (AI) and machine learning allows lenders to more accurately assess risk and detect potential fraud during the application process, leading to higher-quality loans less likely to default.

Lenders are also utilizing predictive analytics on borrower behavior to identify early signs of trouble and take preventive action through improved loan monitoring systems.

With automated tracking enabling quicker interventions as needed, these technological capabilities help drive down default rates, ensure smooth payments and significantly mitigate repurchase risk. By leveraging such innovations, lenders can greatly strengthen investor trust in bundled mortgage products.

Cutting-edge data technologies are invaluable for mitigating repurchase risk across sectors,
especially in mortgages. For instance, certain firms now employ automated direct-source data connections to validate applicant details in real-time, confirming income, employment, assets and other information at the moment of origination. This prevents falsities upfront.

Additionally, enhanced data access enables lenders to monitor loan performance factors on an ongoing basis. Via API connections, loan data is streamed into systems allowing staff to catch early warning signs of borrower distress, like missed payments on other credit accounts. This data empowers lenders to take timely preventive and corrective actions with struggling borrower before complete default.

Between advanced application fraud checks and early intervention on emerging trouble signs, these data capabilities attack repurchase risk from both sides, further safeguarding mortgages for downstream investors.

Employing such technological safeguards carries major advantages across mortgage lending stakeholders. With reduced defaults and minimized repurchase requests, lenders can reap higher profits on sold mortgages while strengthening investor trust in associated securities. This helps attract ongoing investment capital into the housing sector.

Consumers also benefit as improved loan quality and lower perceived default risk opens lending access, allowing originators to offer more borrowers mortgage financing, often at better interest rates.

By cutting risk through data and automation, these innovations allow for mortgage market growth, fueling a win-win for both lenders and everyday borrowers seeking to purchase homes. The enhanced market stability and consumer access further establishes technology’s power to drive positive change in lending.

Technology is transforming how mortgages are originated, bundled and sold on secondary
markets to mitigate repurchase risk and improve stability. Through automated underwriting,
direct source data verifications, and API-driven performance monitoring, lenders can
significantly reduce defaults and errors in loan pools.

With lower repurchase risk, lenders enjoy greater revenue potential and investor confidence in the mortgage instruments they bring to market. Further boosted by early warning systems that enable targeted borrower interventions, these capabilities don’t just move risk off lender books, but actively prevent it at scale.

The results are profitable loan growth and expanded consumer access. Government agencies like Fannie Mae and Freddie Mac both have integrated these capabilities into the loan origination process to confirm the reliability of data from day one through closing and the eventual sale of the loan.