TD AI Automates One-Third of Auto Finance Funding Work

On August 27, 2026, The Toronto-Dominion Bank (TD) said on its third-quarter earnings call that its AI and automation work had automated approximately one-third of the manual funding processes at TD Auto Finance Canada. The bank is also launching digital income verification to deliver credit decisions faster, but it has not separately quantified AI-driven labor savings, cost savings, or changes in operating expenses.[1]

TD is a diversified North American bank with Canadian personal and commercial banking, U.S. banking, wealth management and insurance, and wholesale banking operations. It generates revenue mainly from the spread between lending and deposit rates, fees, and insurance. Its AI credit journey automation is a core operating tool for real-estate-secured lending and auto finance teams. The workflow covers application submission, credit pre-adjudication, document review, income verification, and funding, with the goal of accelerating credit decisions.

How TD expanded AI across the credit journey

The public history of this application begins with a system that was already being deployed. The earliest disclosure in TD's public earnings-call record covered here dates to February 26, 2026, when the bank began scaling an agentic AI solution for real-estate-secured lending pre-adjudication. That was the first public description in the research window, not necessarily the date TD adopted the technology.[2]

By August 27, 2026, management described a broader workflow spanning application submission, document review, and credit decisions. It also included funding and income verification at TD Auto Finance Canada. The application remained in limited production within a single business unit.[1]

What the one-third automation figure shows

The reported one-third figure shows that automation has replaced some specific manual steps. Its scope is limited to manual funding processes at TD Auto Finance Canada, and it measures the share of processes automated. It does not represent a one-third reduction in processing time or expenses.

TD also said it was launching digital income verification to deliver credit decisions faster. However, the bank did not disclose a controlled before-and-after comparison, so the statement does not establish that approval quality or loss rates have improved.[1]

The financial impact remains unquantified

Automating document review, income verification, and funding could reduce manual processing hours and the cost per application, potentially affecting operating expenses. But funding volume, application mix, systems investment, and other process changes could also affect costs. TD has not disclosed AI-specific labor savings, unit costs, or expense changes, and it has not provided a financial bridge connecting this application to credit-risk outcomes.

What can be confirmed is that TD expanded AI from real-estate-secured lending pre-adjudication into a broader credit operations workflow and disclosed a real automation scope in auto finance funding. What cannot yet be confirmed is whether that change has produced lower operating expenses or better credit outcomes. The operating impact would become distinguishable only if TD reports before-and-after processing costs or related expense savings and isolates AI's contribution.

Application assessment

• AI Credit Journey Automation | Business position: Core operations | Deployment stage: Limited production | Scope: Single business unit | Value type: Cost reduction

Sources

[1] Drillr · The Toronto-Dominion Bank (TD) · 2026-08-27 · Earnings call

Original: We're also leveraging AI to enhance the colleague and client experience in TD Auto Finance Canada. We have automated approximately one-third of the manual processes in funding and launching digital income verification to deliver credit decisions faster.

[2] Drillr · The Toronto-Dominion Bank (TD) · 2026-02-26 · Earnings call

Original: We launched the initial scaling of an agentic AI solution to simplify the Ressel pre-adjudication process.