Truly adaptive banking: Why it pays to be process-led

“You can’t just keep doing what works one time, everything around you is changing. To succeed, stay out in front of change.” So said Sam Walton, Walmart’s legendary founder, and as usual, he was on the money.

Adapt or perish. Bend, don’t break. Proactive not reactive. These sentiments are bound up in the strategies of every successful modern enterprise–particularly right now, and particularly in the banking sector. Not only is the commercial landscape changing fast, the changes are accelerating. When EY put together their Global Banking Outlook 2025, their assessment boiled down to this: “We expect uncertainty to be the watchword of 2025”. So it has proven. Banks are struggling to keep up.

To stay out in front of change banks need to be able to see it coming and address potential issues proactively. They need to become more adaptive. But this isn’t something you can just switch on and off. It involves a major rethink of years-old banking workflows. We’re going to look at why a process-led approach is the fastest route for banks to offset some of the strongest change headwinds.

What’s an adaptive bank?

An adaptive bank is built to anticipate and respond to change rather than simply react to it. This requires a shift both in mindset and in operational model. Adaptive banks actively monitor their environment for shifts in customer behavior, regulations, or technology.

They don’t wait for the next big transformation. Instead they make continuous enhancements to core processes while tackling larger digital transformations. They put technological power tools like AI to work, delivering better customer experiences and smarter, more secure operations.

Rather than viewing change as a periodic challenge to manage, adaptive banks put organizational agility at their core, allowing them to thrive irrespective of the commercial conditions. It's not about holding back the tide, it’s about riding the wave.

Why take a process-led approach to adaptivity?

For banks to become truly adaptive, they must first understand their processes, then connect and optimize them throughout each department. Processes run across and between key banking functions: from Customer Service and Sales to Trade Operations and Risk & Compliance. So by making processes the key mechanism for increasing organizational agility, all departmental interactions and interdependencies are taken into account during process optimization. Processes are a bank’s fastest lever for change, and for reacting to change.

Process intelligence holds the key to this process-led adaptivity for banking. It’s a journey we’ve helped around 70% of the top ten banks in EMEA and North America navigate via the Celonis Process Intelligence Platform. How? By enabling them to understand and optimize their workflows – rewiring their operations to sense and respond to volatility.

This starts with extracting and consolidating raw data from all the systems that support banking processes – old and new, on-prem and in the cloud. Applying advanced process mining and machine learning, Celonis builds a data foundation that shows how the processes really work. This is enriched with business context and AI to give banks a living digital twin of their banking operations and a common language for optimization: Process Intelligence (PI). Which means they have the ability to:

Visualize actual workflow interactions and interdependencies across departments
Overcome any disconnect caused by siloed departments and systems
Analyze the root causes of any process inefficiencies
Pinpoint value opportunities hidden in banking processes.

Instead of waiting for issues to occur, the real-time visibility provided by the Platform allows banks to detect early warning signs and the tools to enhance processes quickly. Now let’s look at how PI can be used to help banks overcome some of the biggest forces of change in the current landscape.

Industry changes making adaptive banking essential

There are three standout forces of change impacting the banking sector that make adaptive banking increasingly important.

#1 – Accelerating customer expectations

Customers expect their banks to provide the same level of fast, intuitive, digital services as their other service providers. They expect instant anywhere access to their accounts and personalized interactions. Decision delays are not tolerated.

With complex customer journeys, legacy systems, and disconnected processes, such expectations can be tough for some banks to meet, particularly for traditional (non-digital-native) banking institutions.

The Capgemini Research Institute’s World Retail Banking Report 2025, for example, showed that only 26% of customers are satisfied with their current card-related banking experiences, with 47% abandoning the application process midway due to a poor experience.

#2 – Banks require smarter, faster operations

Banks face mounting pressure to modernize operations: to meet rising customer expectations but also to cut costs and eliminate inefficiencies in the face of shrinking margins.

But often their infrastructure, teams, and processes can’t keep pace with this need for change. Workflows span multiple siloed but interdependent departments and fragmented tech stacks, impeding smooth handoffs and slowing transaction speeds.

Productivity is often further compromised by a heavy reliance on manual processes, which also puts the brakes on the banks’ ability to respond to market shifts.

#3 – Managing shifting risk and regulatory landscape

Amplified by AI, the fraud and financial crime landscape has been changing (and growing) significantly. In response, global anti-money laundering (AML) / counter-funding of terrorism (CFT) regulations are being tightened regularly and banks have to keep up. In 2024, regulators issued $4.6 billion in fines to financial institutions, with $4.54 billion for AML/CFT violations alone (plus ongoing reputational damage).

Regulatory frameworks are also evolving to reflect fintech disruption, post-2008 risk reforms, and operational resilience concerns. Maintaining compliance is challenging due to proliferating regulations (Basel III revisions, DORA, MiCAR) that vary by market, and fragmented systems that hinder rapid adaptation.

How PI-powered adaptivity helps overcome these challenges

The PI Platform enables banks to tackle each of these major change headwinds, reconfiguring key processes in order to provide that essential organizational agility.

Customer expectations

PI ensures banks can see exactly what’s happening at each customer touchpoint. The Platform helps them decide how to optimize underperforming processes impacting CX, minimize errors, and reduce unnecessary communications while enabling timely follow-ups to prevent abandonment. It uses AI to accelerate decisions and orchestrate process automations.

The Platform is also being used to enhance digital banking experiences, including:

Removing bottlenecks: Through real-time touchpoint monitoring and automated interventions throughout the credit lifecycle, delays can be eradicated while maximizing efficiency and CX.
Supplier SLA adherence: Track and manage the performance of third-party suppliers (such as BPO or underwriting) for compliance against contractual service level agreements.
Responsive customer communication: Deploy automated triggers that adapt to and enhance individual customer experiences, ensuring timely and fair outcomes while supporting customer retention.
Minimizing customer outreach: Deliver clear product information to customers and process owners, with failsafe controls that identify missing information during process execution.

With PI strategies such as these, Celonis has enabled its banking customers to supercharge their CX, including:

A privately held bank reducing its average mortgage funding cycle time by two full days.
A German bank slashing time-to-yes by 50%, improving customer satisfaction.
A European bank speeding up mortgage decisions by 40%.

Smarter, faster operations

PI provides the process-level fix they need to achieve this. Connecting teams, systems, and AI, PI can break departmental siloes and provide the end-to-end process understanding necessary to create smarter, faster, and automated processes. Processes capable of adapting to elevated CX expectations, new regulatory frames coming from DORA or Basel III, and whatever else comes.

Banks have successfully used the PI Platform to:

Minimize cost per trade: Identifying automation opportunities within trade operations to substantially decrease average cost per trade.
Reduce trade amendments: Deploying PI to pinpoint common causes of time-sapping amendments and establish consistent processes across regions and products.
Avoid duplicate transactions: Tracking transaction history to monitor different versions of the same transaction and detect inadvertent double payment processing.
Enhance payment performance: Analyzing settlement data to uncover why transactions settle beyond agreed SLA terms.

This has realized tangible at banking institutions, including:

One bank used PI to connect settlement data across systems, prioritizing high-value payments and reducing wire transfer waiting times by 75%.
An investment bank used PI to reduce manual trade touch points 35%, cutting cycle time and the resources needed to support trade operations.
A multinational bank identified $11.6M of trapped liquidity.
A global investment bank reduced effort across payment teams by ~37 FTE.
A major US investment bank used PI to drive a reduction of 46 days in KYC cycle time, as well as a 47% reduction in payment investigation costs.

The risk and regulatory landscape

PI enables banks to adapt to both the changing crime threat and regulatory compliance. The Platform’s cross-system data consolidation delivers accurate, real-time, end-to-end operational transparency. This enables banks to consolidate information and timelines for regulatory reporting, embed compliance protocols and notifications into new processes to prevent breaches, streamline dispute settlement, and stop fraudulent claims from being approved.

Proven PI use cases for banks’ risk and regulatory challenges include:

Reducing recurring corrections: Identifying patterns of recurring corrections to automate them or alert relevant teams where report generation changes are needed.
Improving reporting timeliness: Actively monitoring required reporting steps to prevent delays or communicate when, where, and why they occur.
Limiting failed regulatory steps: Identifying and eliminating failed regulatory steps while assessing the effectiveness of regulatory controls.
Reducing manual value adjustments: Strengthening validation steps to minimize manual adjustments or reconciliations and identify automation opportunities.
Enhancing KYC workflow: Boosting KYC productivity through automated customer verification, improved due diligence, and optimized resources while identifying process deviations, monitoring compliance violations, and improving reporting traceability.
Streamlining dispute settlement: Eliminating costly reassignment rework that extends cycle times and reducing idle periods that compromise SLA adherence.

These measures have delivered real-world results, such as:

One German bank improved their (mandatory) security order recording consolidation rate by 12%
A Dutch private bank avoided $500M in regulatory fines through process transparency
A top-10 US commercial bank saved $10M+ OPEX in case assignment and handling
A major US commercial bank used PI to reduce its fraudulent claim approvals by 21%
One investment bank reduced SLA breaches for regulatory reporting by 80% and avoided more than $10 million in potential fines.

The AI elephant in the room (PI’s got your back)

Arguably the biggest driver of change (and catalyst for adaptivity) for banks today is AI. One report indicated that one in three banks planned to spend over $25 million on AI in 2025 to improve CX, as well as cost and operational efficiencies. AI’s potential impact is forcing financial institutions to rethink their operations and structures – but also facilitating the change.

But PI has got your back, there, too. It provides the accurate, up-to-date, and comprehensive data foundation that AI relies on to flex its analytics effectively. The PI-powered platform ensures confident AI deployment across use cases like document validation, process automation, and fraud investigations. It ensures explainable, unbiased, accurate AI decision-making.

Banks seeking to pursue an adaptive, AI-optimized future would do well to take a process-led approach, with Celonis Process Intelligence lighting the way.