RedCompass Labs unveils AI solution for banks to modernise payments

By Gloria Methri

RedCompass Labs, an expert in payments modernisation, has launched AnalystAccelerator.ai, a multi-agent AI solution engineered to accelerate payment transformation.

Banks worldwide are juggling multiple, multi-year, multi-million-dollar modernisation projects, such as ISO 20022, SEPA Instant in Europe, and FedNow and RTP in the US. Over nine in ten (91%) banks now consider payment modernisation a high priority, but research shows most are struggling to meet demands.

AnalystAccelerator.ai helps banks address these challenges with an applied AI tool for payment modernisation. It is built on knowledge from over 300 payment projects for leading banks and the comprehensive library of global payments documentation.

Using AnalystAccelerator.ai, a business analyst can reduce manual work on a typical payment modernization project by up to two-thirds (68%). Regulatory and project documentation updates that used to take weeks can be completed in under a day, saving banks millions of dollars and months of work.

In trials with a tier-one bank struggling with the new SEPA Instant Payments Regulations, AnalystAccelerator.ai reportedly reduced the time to create business requirements from the standard 25 business days to 45 minutes. With two hours for human review and edits, it delivered a 99.5% time-saving.

Each business analyst is paired with an AI agent that taps into the collective brainpower of RedCompass Labs’ 20+ years of experience in payments modernisation, including regulatory and project-specific documentation. The AI agents learn and adapt in real time, enhancing productivity while retaining the highest levels of security and privacy.

Tom Hewson, CEO at RedCompass Labs, said, “AnalystAccelerator can more than double a bank’s output while maintaining costs or maintaining output and cutting costs in half. Complex, costly projects like SEPA Instant, ISO 20022, FedNow and RTP are simplified and streamlined. Large language models don’t need to be tuned for speed—they can be tuned for accuracy. That is the difference between general generative AI (such as ChatGPT) and applied AI (such as AnalystAcclerator).”

“AI agents can check, review, and prepare documents for publication, ready for final sign-off by people. Multi-agent AI models work 24/7. Workers check in to review, approve, and reassign jobs to the agents. The productivity and time benefits are enormous.”