The notion that the best way for banks to modernize their core systems is to rip them out and replace them with new ones is not only outdated—it’s also inefficient.
Consider a study by IBM that found 94% of banking overhauls exceed their deadlines, resulting in delays that negatively affect the project’s ROI.
Fortunately, the rise of AI means that there are other paths to transformation. In this new era, leading financial institutions are focusing less on decommissioning outdated software and more on how new technology can help them extract data and create value from existing systems. It’s a savvy move that enables organizations to leverage what they have, while still modernizing for the future.
“We’ve been so focused on moving from legacy systems to newer systems, when the real opportunity is in how we use the data and improve the process,” says Jaymini Hirani, Financial Services Lead at Celonis.
Data is everywhere, but where’s the intelligence?
Modern banks rely on hundreds of systems and applications. For example, a single payment may come in contact with 200 different systems as it traverses from initiation and authorization to clearing and settlement.
Some of those systems represent the latest technology. But others are likely legacy software, core banking systems, or even Excel spreadsheets managed by specific employees. As a result, the related data is siloed within systems and applications, making it difficult to access.
In this environment, interactions and handoffs between teams become increasingly complex, and the risk of errors increases, resulting in delays and manual workarounds. The fragmented nature of the data also limits transparency, which can impede productivity and, more importantly, lead to regulatory concerns.
The latter is especially important now, as banks face mounting regulatory pressure to increase visibility into their systems to justify decisions and prove operational resilience.
While overhauling all of the systems and applications the bank relies on and replacing them with a more unified solution might seem like the best way to solve the problem, it often simply relocates it. “The end goal isn’t eliminating systems,” Jaymini says. Instead, it’s “making sure people are using the data to drive value or whatever outcome they’re seeking,” she adds.
Process Intelligence changes everything
Process Intelligence offers a different, more effective approach to centralizing and accessing data. In lieu of replacing systems, Process Intelligence extracts data from banks' various source systems, applications and devices to create a digital twin of banking operations. It then applies advanced mining and machine learning to build a data foundation that reveals how processes are really working. The digital twin is then enriched with context — like business rules, KPIs, benchmarks, models, and enterprise architecture — to mirror the bank's as-is reality.
Going back to the payments example, Jaymini notes that process Intelligence enables banks to predict when and whether a payment will require an investigation or repair.
With data easily accessible to the right teams and roles, banks can act on it quickly, reducing risk, improving the customer experience, and driving strategic decisions. “That sort of intelligent decision-making is possible when you have all the data in one unified place,” she says.
Visibility that drives value
Process Intelligence helps change the question from “how do banks access data?” to “how can they derive value from their data?”
Banks that can confidently answer the latter question will be able to:
- Streamline their customer onboarding and improve the overall customer experience. For example, customer onboarding often requires banks to request multiple documents from customers over multiple days. Process Intelligence can uncover ways to reduce customer burden and accelerate the process.
- Drive operational efficiency across the organization. By leveraging an “analyze, design, and operate” strategy, banks can identify opportunities for process improvements, then design AI tools to extract data from systems and implement AI agents to manage and optimize processes.
- Improve and streamline transactions. Process mining identifies bottlenecks and inefficiencies within transaction lifecycles. Leading banks can use that information to automate workflows, eliminate redundancies, and more.
- More easily scale risk, control, and finance functions. In another example, a central data layer enabled by Process Intelligence makes it easier to manage system permissions, track data usage, and ensure the organization meets regulatory requirements. “It’s not just about pounds and pennies saved, it’s also about the impact you can have on customers and colleagues,” Jaymini says.
Celonis makes Process Intelligence possible
Process Intelligence is empowering banks to shift from a system-focused technology strategy to one that’s rooted in outcomes and values. And through an anaylse, design and operate approach enabled by Celonis, banks are unlocking significant value in the process.
“With Celonis, the world’s top financial institutions can leverage the data hidden within all of their systems, improving visibility, compliance, customer experience, efficiency, and so much more,” Jaymini says.
Interested in learning more from Celonis experts about the benefits of Process Intelligence and how it helps you maximize your AI ROI? Check out this webinar.
