Applied AI: The fix for outdated payments systems

Imagine you’re operating a long-distance passenger train. You’ve carriages full of happy customers. Business is going well.

The problem is, you’re running on old tracks. They’ve served you well for years, but they’re worn and slow by today’s standards.

Up ahead, a new high-speed rail line has opened. It’s faster, safer, more efficient.

If you stay on the old tracks, customers will start choosing other train operators you get places quicker. So, you need to switch.

But here’s the problem: you can’t stop the train.

You’ve got hundreds of passengers onboard, expecting a smooth ride. There’s no time for a full system shutdown. So, you have to shift your train onto the new tracks while still in motion. That means finding a new way to connect to the new rail, reconfiguring switches, and updating your systems in real-time.

It’s complex, expensive, and risky. And the engineers who laid the original track are long gone.

Upgrading to the new rails will be hard. Getting it wrong could derail everything.

Sound familiar?

The pain of payments modernization

Just like changing rails mid-trip, banks have to replace old systems, meet ever-changing regulations, keep up with customer demands, and sometimes migrate their entire payments operation – all without disrupting their day-to-day operations. 

Think of the migration to ISO 20022. Or connecting to new instant payment schemes like FedNow or SEPA Instant. These projects take several years, cost tens of millions, and cause untold stress. You can’t just pause operations to integrate with these schemes. You have to upgrade systems, manage downtime, and train teams without upsetting your customers. 

The traditional approach to modernization relies heavily on manual processes. Huge chunks of a project involve reading regulatory updates, summarising information, writing epics, and user stories. Mistakes can crash systems, cause missed deadlines, and incur financial penalties. 

It’s not cheap. It takes a while. And it’s really, really hard to do. 

The Applied AI advantage

Applied AI is changing that.  

Applied AI is the tailored use of artificial intelligence to solve complex, real-world problems. These tools consume years’ worth of proprietary project and company data, regulatory documentation, system requirements, and business goals in seconds. 

They automate repetitive tasks, map project risks, and reduce the time it takes to implement change. This can help banks like yours tackle challenges head-on. 

Through techniques such as retrieval-augmented generation (RAG), natural language processing (NLP), and multi-agent models, Applied AI goes beyond ChatGPT and other off-the-shelf tools. It’s especially useful in regulated, data-heavy industries like banking, where accuracy matters. 

So, instead of spending months and years to change your systems, you can use AI-enabled experts to do the work for you in a fraction of the time.  

Practical benefits of AI in payments modernization

How does it work?

Accelerated analysis and planning

AI tools sift through regulatory standards, technical specifications, and legacy system documentation. They find the problems, map a solution, and figure out the quickest way to upgrade your systems. By automating complex analytical tasks, what used to take months now takes weeks. 

Improved data quality and consistency

Data quality is a big issue in legacy systems. Consider the ISO 20022 structured address migration. Banks have to upgrade libraries of messy customer data to meet the new standard. That would’ve taken ages. But now, AI can identify inconsistencies, suggest corrective actions, and standardize data to fit new platforms. It ensures you hit the deadline with smoother migration and fewer post-migration errors.

Reduced project costs and duration

By automating repetitive tasks, reducing manual errors, and providing precise guidance, AI lowers both the duration and cost of modernization projects. Banks can redirect resources from routine compliance and testing to strategic areas. 

Real-world application: AI-enabled migration

We helped a global bank define functional requirements for their Verification of Payee vendor selection. AI did the heavy lifting, with humans approving the outputs. The result? It took 3 hours, not 3 weeks.

Applied AI is a strategic imperative

As a bank, you face a big decision: maintain traditional, labor-intensive way to respond to regulatory changes and payments modernization. Or, adopt AI early to get there faster, and for less.

The approach you choose can impact your success. 

So if you’re still traveling on old tracks, upgrading to new rails, and wondering how you’ll meet the next set of requirements, you’re not alone. But you don’t need to go it alone either.

Let RedCompass Labs help you modernize mid-journey — safely, quickly, and without alarming your customers. Talk to one of our experts today.