Reevaluating the Impact of AI on Mortgage-Backed Securities: A Product & Development Perspective

Introduction:

The AI Shift in Mortgage-Backed Securities & Fintech

The mortgage-backed securities market has long been a crucial component of the U.S. economy. Nonetheless, inefficiencies in risk assessment, pricing, and data processing have held back its full potential. The potential integration of AI into these processes promises improvements in speed, accuracy, and decision-making.

Recently, I worked on a project to build a live dashboard aimed at streamlining real-time TBA (To-Be-Announced) prices. For those unfamiliar, TBA is a mortgage-backed security transaction format where buyers and sellers agree to trade loans that will be delivered later, without identifying the specific loans at the time of the trade. This mechanism helps lenders sell their loans efficiently and provides stability for investors, thereby contributing to the housing market's health.

In my role, I served as a bridge between the product and development teams, ensuring that the development process incorporated sound financial logic behind TBA pricing, as well as the necessary data and queries for optimal implementation. While this project did not directly involve AI technologies, it is a crucial foundational step toward exploring how AI can be integrated into the MBS sector in the future. The aim is to remain innovative and aligned with the advancements adopted by market participants.

This experience underscored an important lesson: the impact of AI in MBS is not solely dependent on technology but also on effective integration into existing business workflows.

The Current Challenges in MBS and Structured Finance

Despite technological advancements, the MBS market continues to grapple with inefficiencies that AI aims to address, including:

- Traditional models failing to adapt to real-time market shifts.

- Analyst reliance on historical data rather than real-time predictive insights.

 - Continued dependence on outdated infrastructure.

- Extensive documentation processes that slow transactions and increase costs.

In addition to these industry-wide challenges, there are significant internal challenges to AI implementation:

- Product teams often lack deep technical knowledge of AI, resulting in misaligned expectations.

- Developers sometimes create AI models without a thorough understanding of financial intricacies, leading to poor adoption.

- AI implementation requires compliance with stringent regulations, making full automation challenging.

How AI Could Transform MBS

AI has the potential to transform the MBS sector, with effectiveness depending largely on successful implementation. One key area is AI-powered risk modeling, where machine learning can analyze extensive borrower and economic data to improve default predictions and minimize risk exposure. This capability allows for real-time adjustments in pricing and risk assessments. Additionally, institutional investors are increasingly using AI-driven trading to expedite decision-making based on real-time data and predictive analytics. AI also enhance compliance and regulatory monitoring by processing large volumes of legal and regulatory documents, automating compliance processes, and reducing human error. The Securitized Products team has put ongoing efforts on automating processes to increase operational efficiencies, which will help streamline workflows, and build attractive products.

Overall, the integration of AI in these areas could lead to a more efficient and effective MBS market. As of late 2023, firms like Fannie Mae and Freddie Mac are starting to incorporate AI into loan risk modeling and securitization. Further, Fintech companies are now leveraging AI to reduce processing times and improve trade execution through predictive models.

In conclusion, while my recent project did not harness AI directly, it sets the stage for future innovations that can leverage artificial intelligence to address the challenges faced by the MBS market and enhance its overall efficiency. The journey ahead requires a thoughtful approach to integration, ensuring that the right technology is effectively woven into the fabric of existing workflows for maximum impact.

Contact arkelino.hila@spglobal.com for a demo of the new TBA dashboard.

Reference: Fannie And Freddie Leaders Talk About Artificial Intelligence - The Mortgage Note