70% of payment-heavy firms plan to add or expand automated payment matching within 12 months.

59% plan to add or expand AI-based fraud detection over the same period.

AI is extending from detecting payment issues into diagnosing discrepancies and recommending repairs.

Much of payment processing already happens without an employee touching the transaction. The “hands-on” interactions come when payments fail to clear, or transactions trigger fraud reviews.

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In other cases requiring manual oversight, payments don’t match the invoices, ledgers or bank records surrounding them.

The August PYMNTS Intelligence report “Payment Protection: Why Firms Still Aren’t Real-Time Ready” found that 70% of surveyed firms plan within 12 months to adopt or expand automation that matches and clears payments against invoices, ledgers and bank statements. Fifty-nine percent plan to add or expand artificial intelligence (AI)-based fraud detection.

Discrepancy analysis adds another task to payments oversight. Finastra’s new Repair Recommendations capability uses AI to identify payment discrepancies, analyze their underlying causes and recommend corrections, with employees reviewing and approving the recommended action.

Payment matching, fraud detection and discrepancy repair address different parts of the same operating workload.

The May PYMNTS Intelligence report “Early Detection: Why Top-Performing Firms Focus on Fraud Before It Starts” found that 88% of 60 surveyed U.S. middle-market firms experienced at least one accounts receivable integrity issue during the previous 12 months.

Seven in 10 experienced ACH returns involving invalid or closed accounts or customer input errors that prevented clearing.

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