RedCompass Labs has launched a ‘world’s first’ multi-agent AI solution designed to accelerate payments to new heights.
AnalystAccelerator.ai seeks to assist banks’ challenges in adopting compliant AI tools for payment modernisation. Business analysts can reduce manual work on a typical payment modernisation project by up to two-thirds (68%) according to RedCompass Labs.
The AI solution also helps to solve regulatory and project documentation updates that used to take weeks can be completed in under a day, helping to save banks millions of dollars and months of manual work.
Regulatory compliance is one of the main focuses of AnalystAccelerator.ai as banks are set to manage multiple incoming standards, such as ISO 20022 and new rules surrounding SEPA Instant in Europe, and FedNow in the US.
In trials with a tier one bank struggling with the new SEPA Instant Payments Regulations, AnalystAccelerator.ai helped reduce the time it took to create business requirements from the standard 25 business days, to 45 minutes with two hours for human review and edits, delivering a 99.5% time saving, meeting regulatory deadlines.
Tom Hewson, CEO at RedCompass Labs, commented: “The launch of AnalystAccelerator.aimarks a pivotal moment. The rate of change in payments has never been this fast – and will never be this slow again.
“Meanwhile, deep payments expertise is sparse, leaving banks around the world struggling to keep pace. This has led to a decade-long trend of payment system outages and significant customer impact.
“But with AnalystAccelerator, banks can get ahead. AnalystAccelerator can more than double a bank’s output while maintaining costs or maintain output and cut costs in half. The choice is ours. Complex, costly projects like SEPA Instant, ISO 20022, FedNow and RTP are simplified and streamlined.”
AnalystAccelerator.ai works by pairing an AI agent with a business analyst and taps into RedCompass Labs’ regulatory and project specific documentation. The AI-agents then learn and adapt in real-time, enhancing productivity while retaining high levels of security and privacy.
“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),” added Hewson.
“AI agents can check, review, and prepare documents for publication, ready for final sign-off by people. Multi-agent AI models work 24/7, allowing workers to focus on more strategic tasks, free from the mundanity of manual work.
“Workers simply check in to review, approve, and reassign jobs to the agents. The productivity and time benefits are enormous.”
