Walk into the back office of most mid-sized European banks and you’ll find the same thing. Screens filled with Excel sheets. Analysts toggling between legacy platforms. And invariably, employees entering financial data into multiple platforms, each with distinct logins, formats and interpretations of the same information. 

A client’s loan review kicks off. The relationship manager circulates PDFs of financial statements, which are printed, highlighted and again manually entered into the bank’s risk model. Elsewhere, the same data is re-entered into the loan origination system. A single mistyped figure goes unnoticed, causing a delayed deal weeks later. This isn’t a story from 2005. It’s still happening now inside banks managing billions in commercial credit.

Despite all the noise about digital transformation, credit risk management processes remain stitched together with legacy tools, manual workarounds, and institutional memory. The real issue isn’t that banks don’t want to use modern technology, like artificial intelligence (AI), rather that few have the foundations to use it well.

“You can’t create intelligence out of chaos,” says Tom Byrne, Lead Go-to-Market Strategist at nCino. “Before anything else, banks need clean, connected, real-time data. And most don’t have it.” He would know. Before joining nCino, Byrne worked on major transformation programs for large European banks, where he sawfirsthand how fragmented systems and siloed data can stall even the most well-intentioned innovation.

The Real Cost of Fragmentation

The problem isn’t ambition. It’s architecture. Over years of tech layering, banks have built a patchwork of disconnected systems. Origination lives in one place, monitoring in another. Offline systems and manual work around are still the glue holding it all together.

The cost of this shows up everywhere. In some deployments, nCino’s internal data show that spreading times have dropped by over 80%, saving hours of underwriting time. Analysts report processing financial statements in as few as 5 to 15 minutes in addition to improving the quality of their risk assessment. The cost of not modernizing shows up everywhere. Today’s clients want services from their banks to rival the digital experiences they get elsewhere in their lives, which means your employees need the tools to deliver products at the right time, and with speed.

But speed is just one side of the story. Risk is the other. According to nCino’s European Credit Risk Report, just 1 percent of banks can access the data they need to review their loan portfolio daily. Nearly half, 46 percent, only see that data once a month.

“If you’re updating your view of a customer once a month, you’re not managing risk. You’re reacting to it,” Byrne says.

Where AI Actually Fits In

When it comes to modern technology, there’s a lot of hype around AI. Byrne is quick to bring it back toreality. Implementing AI isn’t about machines replacing humans. Getting the most out of this new technology is about orchestration.

“AI’s superpower today is context,” he explains. “It pulls from multiple sources, makes sense of it, and shows what actually matters.”

One clear example: document ingestion. Spreading financial statements used to mean hours of manualinput. Now, AI reads, extracts, validates and pushes structured data where it needs to go, increasing accuracy and diminishing human errors. 

Once data is in shape and leveraged for these use cases, AI can begin to highlight patterns and pull complex analytics. “AI isn’t optional,” Byrne says. “But using it well means fixing your data first. That’s how you unlock its value.” Insights from AI-powered analytics like proactive risk triggers and pricing model recommendations enable banks to adjust strategy, sometimes dramatically.

Decision-making AI will come, but Byrne says the guardrails need to stay firm.

“Everything has to be explainable. Regulation demands it. And we build with that principle in mind.”

Why Banks Are Finally Moving

So, what’s shifting? What will push banks to finally modernize?

In many cases, banks are modernizing because the inefficiencies are now impossible to ignore. Time tocash is too slow. Manual work is too costly.  

Others are reacting to regulation. Retrofitting old systems to meet new rules is painful, and moving to more modern technology solves for this now and brings long-term upside. More and more, the real reason banks are shifting is to be ready for whatever comes next.

That’s where nCino comes in. As a foundational software platform, nCino enables banks to go beyond a system upgrade and truly get value from their data. 

The Bottom Line

Modernization is not about following trends; it is about addressing the operational inefficiencies that hinder banks and elevate their risk.

Artificial intelligence cannot resolve chaos on its own. It requires a solid foundation, which includes structured processes, clean data, connected systems, and a unified platform that integrates everything in real time.

The edge isn’t in the data you have. It’s in how quickly you can act on it and get the value to your customer.

Join us on June 13th in Stockholm for an exclusive breakfast seminar exploring how leading commercial banks are modernizing credit risk and lending, and what it takes to stay competitive in a changing market. Register to attend here.