Bank of Montreal is turning artificial intelligence into a sales tool for its commercial bankers, using third-party software to pull and interpret customers’ accounts-payable and payments data so relationship managers can have more targeted, advisory conversations with middle-market clients. The Montreal-based lender has already deployed the technology in the U.S., will start a pilot in Canada “in a couple of months,” and plans a broader rollout by the end of 2026, executives said.
BMO is working with Codat, a vendor that connects via APIs to more than 20 accounting and enterprise-resource-planning systems — including QuickBooks, Oracle, NetSuite, Sage, Microsoft Dynamics, Workday and Xero — and uses machine learning to categorize transactions and surface opportunities for the bank’s Treasury and payments sales teams. For systems without a direct API integration, Codat offers an “intelligent upload tool” clients can use to supply raw files, according to Codat’s chief revenue officer, Joey Rault.
“Getting customers to share data is an innate pain point that we see all over banking,” Rault said. Codat’s models look for supplier payment patterns, payment methods and other signals that can indicate where a business might benefit from switching how it pays vendors — for example, moving check payments onto a card or ACH to improve controls and working capital. Where the vendor is inferring data, such as guessing a payment method from invoices, it flags that uncertainty so bankers can verify it with clients.
Rose Grande, head of North American corporate card product and programs at BMO, said the system helps the bank scale the “trusted advisor” role across more relationships. By enriching bank data with Codat’s intelligence, sales teams can quantify opportunities — showing a client how much they spend on corporate cards today and how much more could be captured, with attendant benefits like cash back or rewards — and map those changes to cash-flow outcomes such as delayed outflows or improved working capital.
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Early results have been promising: Grande said several clients that connected through Codat have shifted a portion of their vendor payments away from checks and toward card payments, increasing their spend with BMO by about 45%. That lift benefits both the bank’s share of wallet and the customers, who can receive program advantages without materially worsening their cash-flow position, she added.
Industry observers say the use case typifies a broader trend of banks moving AI beyond internal automation to client-facing intelligence. Bradley Leimer, founder of Leimer One Advisors, noted much of the value in commercial banking resides in payments, cash flow and supplier relationships, but that relevant data is often fragmented across ERPs, accounting platforms, PDFs and CRM notes. “The broader opportunity is not just AI-generated recommendations, but relationship-driven intelligence using permissioned data to understand where the customer may have friction,” Leimer said.
Codat and BMO are also pitching a risk-management angle: checks remain a meaningful share of B2B payments — Rault estimated 15% to 25% globally — and are vulnerable to speed and fraud issues, risks that could grow as fraudsters leverage synthetic imagery and other AI tools. Identifying where checks persist and nudging clients toward modern rails could reduce fraud exposure while offering operational and liquidity benefits.
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BMO’s next steps hinge on the Canadian pilot and the planned 2026 rollout. “So we are fully in,” Grande said, signaling the bank’s commitment to scaling the approach if the pilot confirms initial U.S. gains.
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