Moving Past Legacy Technology
Banks’ modernization efforts lie along a spectrum. Some institutions have already integrated features such as real-time payments and instantaneous fraud detection, while others still use legacy cores. These latter banks often cobble together solutions through middleware to offer these functionalities but not in the most efficient manner.
The primary bottleneck for many banks is their legacy technology. Without progress in modernizing systems, issues are inevitable.
Batch processing allowed institutions to systematically scrutinize transactions for fraud and other risks, making it easier to mitigate and remedy such issues. However, with the advent of real-time payments, this system has become outdated. Small businesses prefer delaying payments until the last possible moment, which necessitates instant payment options that current legacy cores might struggle to handle efficiently.
Different Risks for Different Banks
This situation presents distinct risks for various types of banks. Larger institutions have the financial resources and skilled personnel needed to keep pace with emerging payment technologies.
For instance, a bank like JPMorgan has consistently stayed ahead by embracing new technologies such as blockchain and developing their own developer portals. These bigger banks can be proactive in identifying what makes sense for them, deciding which technologies to implement, and hiring the necessary talent.
In contrast, smaller banks often lack both resources and specialized talent to undertake such projects independently. However, they do have access to modern payment platforms through core banking providers like Fiserv and Jack Henry.
Taking Responsibility for Fraud
The shift towards real-time payments also means an increase in real-time fraud. Banks must develop capabilities to manage both scenarios effectively. Agentic commerce introduces new vectors of risk, but it’s unclear how this responsibility will be assigned.
If banks still rely on batch processing, they won’t be able to offer real-time payment services, and their fraud detection tools might also be inadequate for monitoring and mitigating real-time activity.
Companies like OpenAI, Mastercard, and Visa are developing agentic payment protocols that can handle these transactions. However, it remains uncertain who will ultimately bear the responsibility for successful payments and potential fraud or errors.
Banks are increasingly opening up their APIs to third-party developers. This means processing payments on platforms provided by fintechs or technology companies, raising questions about accountability when a payment goes awry.
Opportunities for Treasury Services
Banks looking to modernize treasury services face the challenge of siloed data and processes. Artificial intelligence (AI) could play a role here, but centralizing this data is crucial. Modern technologies rely on accessible, readable, and digestible data to automate treasury processes.
Treasury services solutions align well with large language models,” explained Matthew Gaughan. These solutions are data-centric, rules-based, and consistent, which makes them ideal for third-party or proprietary AI systems.”
A business owner seeking historical accounts receivable days could quickly visualize this as a chart, providing vital insights into liquidity optimization.
