TD’s agentic AI model prepares mortgage and home-equity line of credit (HELOC) application summaries for human underwriters; TD says early results cut average pre-adjudication processing time from 15 hours to less than three minutes. The system supports underwriting rather than making the final mortgage decision, and the time figure is a company-reported result without published study details.
What TD’s agentic AI does in mortgage operations
TD Bank Group announced on May 21, 2026, that it had launched its first agentic AI model in Real Estate Secured Lending (RESL), initially for the pre-adjudication stage of mortgage and HELOC applications. At this stage, the model prepares a summary memo that a human underwriter can use; TD has not said the model itself approves or rejects applications. TD’s announcement describes the launch as an initial step toward applying agentic AI across the RESL process, from client document submission through funding.
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TD says the system classifies submitted documents, extracts relevant information, calculates income, checks figures against selected policy requirements, performs consent checks, searches for discrepancies, and assembles the findings into a concise summary for the underwriter. In a July 2026 feature, senior machine learning engineer Sandra Aziz described the goal as providing “the right information to a human.”
How much faster TD says the process is
TD reported an early-results change in the average pre-adjudication processing time from 15 hours to less than three minutes. This is TD’s reported figure, not an independently verified customer wait-time guarantee. The May announcement does not publish a sample size or explain the measurement method, so it does not establish that every application will be processed in under three minutes or that the full mortgage approval process takes that long.
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TD also says the process is producing more accurate results, but it has not published a quantified accuracy improvement or an evaluation method for that claim. The available announcements provide no independent study or comparative customer-outcome data.
Does AI approve the mortgage?
No final approval authority is established for this model in TD’s published descriptions. Its stated role is to prepare information and a summary memo for human underwriters, who retain a role in assessing the application. TD’s July feature characterizes the solution as having a human in the loop. Borrowers should not interpret the faster preparation of an underwriter memo as an automatic approval or a promise of faster funding.
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In July 2026, TD said that 100% of new personal mortgages were then going through the process. That figure applies to the scope and timing in TD’s July account; it should not be generalized to every mortgage, all HELOC applications, or TD’s rollout status at a later date.
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What TD says about oversight and safeguards
TD says its Trustworthy AI team oversees integration and evaluates models for privacy, security, fairness, accountability, and explainability. The bank says checks occur before models come into contact with humans and that deployed models are monitored. These are TD’s descriptions of its governance approach; the announcements do not provide a model audit, detailed evaluation results, or a borrower-facing account of how a particular application is handled.
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TD presents the system as a way for AI and employees to work together. Chief Analytics and AI Officer Luke Gee called this a “hybrid future,” while RESL executive Mohit Veoli said the initiative is intended to improve speed and simplicity. The human-underwriter workflow is central to understanding what the announcement does—and does not—mean for applicants.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.How this fits TD’s wider AI strategy
TD says the RESL deployment is part of an enterprise AI strategy focused on combining machine intelligence with human expertise. The bank’s 2025 annual-report strategy page separately discusses faster mortgage pre-approval, pricing, and application processes in Canadian Personal Banking. Those broader strategic statements are not measured outcomes attributable to this particular agentic AI model. TD has also cited a goal of generating $1 billion in annual value from AI in the coming years; that is a corporate target, not value already realized or a mortgage-specific result.
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- SPEAKS YOUR LANGUAGE: Keys clearly labeled in residential mortgage finance terms like Loan Amt, Int, Term, Pmt; this industry-standard calculator is super easy to use on all realty financing matters from finding a loan that works for your client to considering trust deeds investments, or finding remaining balances or balloon payments and more
- CONFIDENTLY AND EASILY SOLVE: Clients' financial questions whether they're buyers, sellers, investors or renters. Increase your perceived professionalism as a new agent, experienced broker or seasoned loan officer. Close more home sales and impress your clients with fast, accurate answers to all their real estate finance questions from PITI Payments to IRR, NPV and Cashflows
- DEDICATED BUYER QUALIFYING KEYS: Enter client's income, debt and expenses to pre-qualify them to only show properties they can afford. Include tax, insurance and mortgage insurance then compare loan options and payment solutions to give your client choices before they make an offer to buy
- FIGURE OUT THE RIGHT LOAN: For your client at the press of a button for jumbo, conventional, FHA/VA, or even 80:10:10 or 80:15:5 combo loans; check to see if ARMs or bi-weekly loans, quarterly payments or if interest-only payments are the answer; giving your client more choices; easily perform what if loan or TVM calculations find loan amount, term, interest or PITI or PI payments
- BECOME AN INVALUABLE RESOURCE: To your clients by reducing their confusion and uncertainty; ensuring they are able to make a purchase offer; knowing they can afford the down payment; and determining which is the right loan for them. Date-math for listings and contracts too. Comes with a protective slide cover, quick reference guide, pocket user's guide, and long-life battery
For borrowers, the practical takeaway is narrower: TD says its system can prepare underwriting information much faster, while human underwriters remain part of the described process. How that changes an individual applicant’s total time to decision, accuracy, or customer experience is not established by the published figures. TD’s July 2026 feature and its 2025 annual-report strategy page provide the bank’s broader account of the initiative and strategy.
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