Using AI to transform payment processing and repairs

In the digital world of banking and finance, smooth payment transactions and processes are core to success. Manual payment repairs, often labor intensive and error prone, are a prime candidate for transformation driven by artificial intelligence (AI). Implementing AI in payment repair services enables financial institutions to boost efficiency, reduce costs, and improve employee engagement.

Advantages of AI-driven payments

Operational teams often face delays in resolving payment discrepancies due to manual processes, which negatively impacts cash flow and customer satisfaction. AI can speed up issue resolution by automating routine repairs and reducing operational friction. With real-time error analysis and correction, AI helps make funds available faster, optimizing liquidity and transaction processing speed.

Another key benefit of AI is its ability to cut costs tied to manual interventions. Payment repairs traditionally require significant human oversight to identify and fix errors, along with layers of approvals. Automating these tasks reduces the need for extensive human resources, lowers operational costs, and enables organizations to redirect savings to other strategic initiatives.

When operational teams are overwhelmed with repetitive tasks, employee morale can decline. The application of responsible AI strategies and enabling technologies empowers teams to move away from mundane operations and focus on more rewarding aspects of their roles.

At CGI’s North American Payments Summit in Toronto last June, David Bergeron from the National Bank of Canada referred to this as "professionalizing the workforce.” He envisions a future where employees supervise AI-driven processes instead of handling data entry. As AI handles routine repairs, employees can focus on complex data analysis, process optimization, and customer engagement. This shift increases job satisfaction and fosters a culture of innovation.

For successful AI implementation in payment operations, AI models must be trained on the diverse standards and protocols governing payments, including legacy formats and modern ISO standards. As Bergeron noted, “Achieving high straight-through processing rates once relied on deterministic algorithms, but AI presents an opportunity to leap forward.” By ensuring AI comprehends payment variations and intricacies, institutions can maximize its effectiveness in payment processing and repairs.

Applying the right data

For AI to drive efficiency through historical analysis, it must distinguish between straight-through processing (STP) and situations requiring human intervention for exception handling. This can be achieved using a comprehensive dataset to train AI models—one that encompasses both successful STP payments and those needing intervention.

Payments with error-free paths can be pattern-modelled, while anomalies, such as mismatched account details, can be flagged for human oversight. By analyzing these scenarios, AI models learn to identify both success and failure patterns, improving future payment processing. This results in increased accuracy and efficiency, as well as reduced transaction errors.

A key challenge in AI adoption is securing sufficient datasets, which is why the global push for payment systems modernization has focused on unlocking data access. CGI All Payments, as an API-enabled, ISO native platform, has become one of the cornerstones of our clients’ modernization efforts.

It’s also important to keep in mind that the payment data required to train AI models often includes non-public personal information (NPPI). Prioritizing data protection compliance and integrating data protection best practices in solution development to safeguard sensitive information when using AI is imperative.

Further, barriers to real-time data sharing between banks will hinder the development of industry-wide AI models, and sanitized data will limit the usefulness of “off-the-shelf” AI solutions. Success in AI-driven repair automation will likely depend on ongoing, direct collaboration between financial institutions and trusted technology partners.

Ensuring AI governance and risk management

To drive continuous improvement, AI must evaluate the outcomes of its repairs. By shifting from reactive to proactive, AI can provide feedback to payment systems and organizations, aiming to eliminate future repair needs at the source. However, while automation increases productivity, it also introduces the risk of undetected errors. Robust monitoring and validation processes are vital to identify and address irregularities.

Daniel Szmukler of the Euro Banking Association warned at CGI’s North American Payment Summit, "You cannot let the machine entirely take the decision process." By implementing strict governance to assess AI repair performance, organizations can ensure that systems adapt to evolving operational needs.

In adopting AI-driven solutions, it’s important to avoid the pitfall of training AI to merely replicate legacy processes, which can limit efficiency gains. Instead, AI should be seen as an opportunity to re-envision payment repair processes, integrating innovative practices that go beyond historical methods.

For example, many payment repairs end with a credit to a generic “branch account,” requiring someone at the branch to determine the final customer routing. AI alone may not recognize that auto-routing to a branch account isn't true STP, and thus, analysis of subsequent intra-branch accounting activity may be required to adjust its algorithms. Experienced staff will provide critical oversight as repair AIs are trained.

AI for payments: A transformative opportunity

Integrating AI into payment repair operations offers a transformative opportunity for financial institutions. By speeding up fund access, reducing costs, and boosting employee engagement, AI helps teams work more efficiently. However, to fully realize these benefits, organizations must invest in training and governance to ensure regulatory compliance and drive continuous improvement. Embracing AI enables banks to streamline operations and position themselves for success in a competitive financial landscape.

CGI is collaborating with financial services institutions to drive business outcomes across operations, including payment operations, through AI. To learn more about our AI work and solutions in banking, feel free to reach out to me, or visit cgi.com.