Waiting for mortgage approvals has often been a lengthy, nerve-wracking process for many homebuyers. As technology advances, however, financial institutions like TD Bank are embracing innovative approaches to meet client needs. TD Bank’s recent deployment of its agentic artificial intelligence (AI) platform is designed to drastically reduce the wait time for mortgage applications, taking pre-adjudication times from 15 hours down to a few minutes. By leveraging AI, TD hopes to streamline its processes and offer a smoother experience for its clients.
TD Bank previously focused on numerous initiatives aiming to improve client experience and service efficiency. As one of North America’s leading banking institutions, TD has continually sought to align with technological advancements. With a network that serves over 28 million clients, the introduction of AI technology into its core processes marks a continuation of these efforts while competing against other lenders implementing similar technologies.
How Does Agentic AI Work?
The new agentic AI model by TD Bank primarily targets automating and optimizing mortgage workflows. By classifying borrower documents, extracting financial data, validating data, performing checks, and alerting to inconsistencies, it attempts to simplify the underwriting process. The result of these automations is a detailed summary for human underwriters to review, enhancing decision-making efficiency. According to Mohit Veoli, Senior VP of Real Estate Secured Lending at TD, “This system delivers confident decisions earlier in the homebuying process.”
Will More Lenders Follow Suit?
With AI-infused processes demonstrating noticeable efficiencies, other lenders may also be prompted to adopt similar systems. Better.com has already embraced AI with its voice agent Betsy, handling nearly 100,000 mortgage-related calls monthly and resolving over a third with no human involvement. These initiatives highlight a trend where AI plays a crucial role in operational competitiveness.
Financial targets are strategically linked to these technological advancements. TD Bank CEO Raymond Chun has set a vision to generate $1 billion in annual AI-driven value by 2025, balancing between savings and revenue growth. He predicts 2026 as being instrumental in integrating agentic AI fully. This sets the stage for broader AI application across different sectors of TD’s business operations.
While technological advancement offers several benefits, risks remain around AI-led assessments, especially in complex areas like income validation. Mismatches between payroll and bank deposit data could lead to cumbersome rework, and TD’s model incorporates discrepancy detection aiming to counteract similar issues.
The robust framework monitored by TD’s Trustworthy AI team continues to evaluate these systems post-deployment. This governance is recognized in the industry, positioning TD as a leader in responsible AI use. Luke Gee, TD’s Chief Analytics and AI Officer, mentioned that the bank is constructing a “hybrid future where our colleagues and AI work together to help our clients get to a ‘yes’ faster.”
Looking at the broader impact, by improving the speed and accuracy of mortgage processes through AI, TD positions itself to gain a competitive advantage in the lending landscape. As more banks gravitate towards AI-driven models, sustaining client trust through transparency, accountability, and regulatory adherence will be vital. For readers, understanding the considerations around AI in finance highlights future trends in mortgage and real estate service provisions.
