BMO is turning to Codat to help its sales teams understand mid-market business customers in a way the bank says it could not do at scale on its own. The Montreal-based lender is using the technology to pull payments and accounts payable data, then turn that information into recommendations for relationship bankers.
Rose Grande said BMO could handle customer intelligence work on a very bespoke, one-off basis, but not in a way that could be scaled across the business. With Codat, the bank can retrieve details on what suppliers customers are paying and how they are paying them, then use machine learning to shape suggestions for BMO’s Treasury and payment sales teams. The goal is simple: give salespeople enough insight to have better conversations with customers.
Codat connects to customer data through application programming interfaces and can ingest information directly from more than 20 enterprise resource planning and accounting software programs, including QuickBooks, Oracle, NetSuite, Sage, Microsoft Dynamics, Workday and Xero. Where it has not built an API for a system, it uses an intelligent upload tool so customers can send in raw files. The company then applies machine learning to categorize transaction files and produce personalized recommendations.
The move lands as more U.S. banks are weighing artificial intelligence use cases and moving pilots into production. In American Banker’s AI Talent Shift survey this year, 66% of bankers said AI is a strategic priority for the firm, a sign that the technology is moving from experiment to operating tool in banking.
That shift makes commercial banking a natural place for AI, where much of the value sits inside cash flow, payments, working capital and supplier relationships. Bradley Leimer said banks want to use AI not only to automate internal tasks, but to better understand client behavior, identify unmet needs and make relationship managers more effective. Joey Rault said getting customers to share data remains a basic pain point across banking, which is why tools that can work with customer permissions and existing software are drawing attention.
Grande said BMO wants to be a trusted advisor to its customers, and that the new setup helps the bank play that role more consistently. The real test now is whether that kind of intelligence can be scaled beyond a handful of relationships and into the daily work of more bankers across the franchise.