Finastra has launched Repair Recommendations, an AI-powered capability within AI OperatorAssist for resolving payment exceptions.
According to the company, the goal is to help banks respond more quickly to rising payment activity by speeding up how transaction errors are identified and corrected. The capability forms part of AI OperatorAssist, Finastra's AI tooling for payment operations.
The operational cost of payment exceptions
Finastra says errors and disruptions in payment processing cost the industry billions annually. They also slow transactions and add manual work for operations teams. The company positions Repair Recommendations as a way to resolve these issues faster, handle higher volumes, and raise payment success rates without adding complexity.
An analyst at Datos Insights said manual processes remain a major operational risk for financial institutions. Despite progress in automation, payment teams still spend considerable time sourcing data and diagnosing exceptions, which keeps operations slow and costly. In the analyst's view, validated, scheme-aware AI recommendations can speed up how payment information is gathered, extracted, and analysed, which supports faster and more precise resolution.
The cloud-native feature identifies payment discrepancies and analyses their underlying causes. It then provides correction recommendations validated against industry scheme and network rules, including Swift, Fedwire, SEPA, UPI, and Nexus. The aim is to keep repairs both accurate and compliant with the relevant scheme.
The tool is aimed at payment operations staff, including wire-room operators, exception and repair specialists, and technical support teams. In addition, through the process of simplifying complex repair scenarios, Finastra expects more consistent exception handling, lower error rates, and greater operational capacity. The company also says the guidance reduces reliance on specialised expertise and shortens onboarding for new staff.
Integration and human oversight
Repair Recommendations is designed to complement Finastra's Global PAYplus and Payments To Go solutions. It builds on the investigative and analytical functions already available in AI OperatorAssist. The recommendations support human decision-making rather than replacing it, and each suggested action is subject to review and approval. Finastra says this approach makes the guidance more reliable and allows continuous refinement. Governance and human-in-the-loop controls remain central to its AI development across the payment lifecycle.
Market context
The launch comes as payment volumes rise, driven by demand for real-time cross-border capabilities, infrastructure modernisation, and digital commerce. Barry Rodrigues, EVP, Payments at Finastra, said AI can deliver immediate value in this environment by accelerating repairs, streamlining onboarding, and strengthening resilience. According to the official, this would let banks scale their operations and provide faster, more reliable services to customers.
The focus on scheme-validated recommendations and mandatory human approval shows how Finastra applies AI to exception management. The tool acts as a decision-support layer within existing processing environments, not an autonomous replacement for operations staff.
