Finastra announced the launch of Repair Recommendations – a new AI-powered capability within AI OperatorAssist. This move will help banks respond more quickly to growing payment activity by adding smarter decision-making into their existing workflows.

Traditional payment processing issues like errors and disruptions cost the industry billions yearly, hinder seamless transactions, and increase manual effort. By implementing Repair Recommendations, teams will be able to resolve issues faster, manage higher volumes more smoothly, and increase success rates without added complexity or manual burden.

How Repair Recommendations Will Help Banks Operate More Efficiently

• Reduces the time and effort required by payment operations teams - including wire-room operators, exception and repair specialists, and technical support staff - to manage and resolve payment exceptions.
• Simplifying complex repair scenarios leads to more consistent exception handling, reduced error rates, and increased operational capacity.
• The cloud-native feature will identify payment discrepancies, analyze underlying causes and provide industry-standard schemes and network rule-validated recommendations - such as Swift, Fedwire, SEPA, UPI and Nexus - to ensure accurate and compliant corrections.
• Decreases dependence on specialized expertise and accelerates onboarding for new staff by offering reliable repair guidance.
• Enables banks to manage higher payment volumes more efficiently as demand rises for real-time cross-border capabilities, infrastructure modernization, and digital commerce.

Executive Perspective

Barry Rodrigues, EVP, Payments at Finastra, said "With Repair Recommendations, we're empowering banks to upgrade their payment operations – reducing resolution times and minimizing errors. As payment volumes increase, AI can help deliver immediate value by accelerating repairs, streamlining onboarding, and strengthening resilience. We're helping banks to scale their operations, and deliver faster, more reliable services to their customers."

"Manual processes continue to pose a major operational risk for financial institutions," said Robin LoGiudice, Strategic Advisor, Datos Insights. "Despite automation advances, payment teams still spend extensive time sourcing data and diagnosing exceptions, making operations costly and slow. AI-powered, validated, scheme-aware recommendations accelerate the gathering, extraction, and analysis of payment information, enabling faster exception resolution while improving efficiency and precision."