JPMorgan Unveils AI-Powered Tool to Combat Payment Fraud in Corporate Transactions

JPMorgan Payments has introduced a new artificial intelligence-powered solution aimed at enhancing fraud detection in corporate transactions. The Account Confidence Score (ACS), generated using machine learning, enables treasurers and corporate finance teams to assess the risk of fraud before initiating payments, according to Finextra.

The ACS leverages insights from over 15 billion historical JPMorgan Payments transactions, analyzing multiple variables such as account age, activity recency, geographical patterns, transaction history, exposure to known fraud, payment frequency, and account linkages. Based on this data, the AI model assigns a score ranging from 0 (low confidence) to 1,000 (high confidence).

To help clients act on the score, JPMorgan provides a simple Red, Amber, or Green risk status, paired with recommended actions. These may include further account verification and practical guidance to avoid common financial threats such as business email compromise, payroll fraud, invoice fraud, and account takeovers.

Greg Hodges, Head of Trust and Safety at JPMorgan Payments, emphasized the tool’s role in addressing the increasing complexity of the digital payments environment: “The Account Confidence Score underscores our commitment to equipping our clients with the right tools and solutions to navigate the ever-evolving complexities of the digital payments landscape, especially as businesses face unprecedented fraud threats.”

The launch reflects JPMorgan’s ongoing investment in AI and security innovation as financial institutions grapple with growing cyber risks and sophisticated fraud schemes.