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From digital transformation to continuous adaptation: How banks are reimagining operations to keep up with constant change
Just a few years ago in 2022, digital transformation spending reached $1.6 trillion. In banking, 75% of the world’s banks and credit unions had already launched a digital transformation initiative, with a further 15% at the planning stage.
Skip to today, and digital transformation spending in banking alone is expected to reach $145.2 billion through 2025.
Now for the uncomfortable question: Are banks seeing relative returns?
The data —plus the hundreds of conversations I’ve had with major worldwide banks over the last decade— suggests not. In fact, in a recent survey of executives from 10 multinational banks, 38% said their transformations have underperformed against KPIs. Meanwhile, 67% said they’ve experienced at least one underperforming transformation within the past five years.
So what are the causes of such low success rates, and how can they be fixed?
I was faced with this question directly when I took on a role leading multiple software and workflow-development teams for one of the largest banks in Portugal. Today, the question remains stubbornly relevant, and I’m helping the world’s top banks answer it with Process Intelligence, as Celonis’ Banking Industry Principal. In this post, I want to tell a bit of my story, and explain why the concept of ‘transformation’ is part of the problem.
Change has changed
Within the last few years, the pace of change in banking has rapidly accelerated. On the Customer and Sales side, banks are scrambling to keep up with new expectations like seamless digital services, minimal wait times, and real-time, personalized communications. Behind the scenes, banking operations are increasingly fragmented, as infrastructure is being outpaced by shifting demands such as settlement-cycle standards and the rise of new asset classes. Meanwhile, the alarming increase in fraud and financial crime, coupled with a rapidly-evolving regulatory framework is piling yet more pressure on banks to tighten controls and regulatory requirements.
Then of course there’s the push to embrace AI in banking, and increasingly Generative AI, which is expected to add up to $340 billion globally across the banking industry.
It’s no surprise that even the biggest names in banking are struggling to keep up with all this change. In such complex organizations as banks, being able to overhaul the business and its processes —AKA, run a digital transformation initiative— for every external hiccup or trend is not an option. I say it’s like trying to turn a supertanker ship with the same agility as a speedboat.
To put it plainly, a lot of digital transformation initiatives are just too rigid. They’re linked to long-term programs and budgets that leave narrow-to-zero room for short-term operational investments. Investments which, ironically, are rarely even seen as investments, but rather expenses.
…And that’s exactly why they fail.
A paradigm shift for transformation
If we can say anything positive about the COVID pandemic, it’s that it revealed the human power to adapt. From global business to our own personal lives, we all needed to quickly adapt to a new reality, new ways of doing things, new ways of behaving, new ways of working, and new ways of doing business. As it happens, banks served as the perfect example of how to pivot the supertanker’s route quickly when needed. For example, most were able to move interactions with customers over to digital channels during the height of the chaos, as soon as not doing so became an existential threat.
But of course, that was a one-time event, where every business had to be mobilized into doing things faster and more efficiently in order to survive. One-time events like those don’t come around often.
Or so we thought.
Then the war started in Europe. And with it, another economic hiccup.
Now we’re in the era of tariff wars, which are already heavily impacting corporate and investment banking risk-management strategies.
The truth is, there will always be seismic shifts that require businesses to respond and pivot in ways they hadn’t anticipated. Couple that with the increasing pace of change in banking specifically, and you can see why rigid transformation initiatives that only focus on long-term programs, while neglecting what’s actually happening in real time, might lead to underwhelming returns.
All of this is why we need to view transformation through a new lens: An effective transformation isn’t about getting to a specific end point. It’s about being able to adapt to change faster, more easily, and more effectively. On a continuous basis.
And that’s exactly what I help the world’s largest banks achieve at Celonis today.
How Process Intelligence enables continuous adaptation
So now you know the vision: continuous adaptation. But how do you realize it?
The ultimate challenge to solve —which isn’t actually a banking-specific problem but an all-industries problem— is what we call the ‘great disconnect’ that exists at the heart of most enterprises. It’s a state of affairs where departments speak their own languages, systems don't play well together, and processes are hard to see and even harder to improve. As these departments, systems, and processes continue to operate in isolation as the business grows, embracing change actually gets harder over time. Sound familiar?
This great disconnect plays out in banks in a number of ways. For example, SLAs get missed, efficiency stagnates, and customer needs go unfulfilled.
To take another example, my first experience with process mining, the foundation of Process Intelligence, showed me with evidence that the inability of a specific department to comply with SLA’s was not caused by inefficiencies within the department itself —although that’s where they were to be observed— but rather, in the handover between departments. In response, and with the help of the same technology, we were then able to bridge the disconnect by:
Giving visibility of the end-to-end process to all involved teams
Defining a global SLA for the process, on top of each team’s SLAs
Continuously monitoring the process and triggering alerts whenever the handover between teams might put the fulfilment of the global SLA at risk
But let’s take a step back and look at how this was all possible. With Process Intelligence, banks transform data from their source systems into a digital twin of their entire business operation, from credit lifecycle, to payments and trades, to fraud and AML, to regulatory compliance, and beyond.
By uncovering how their processes are actually running beneath the surface, across functions, banks can finally weed out the inefficiencies and root causes behind the issues I just described. But that’s only half the story. Process Intelligence also gives them the power of AI to continuously optimize and automate their processes, while seeing the potential impact of business decisions — so when they see change coming, they’re already one step ahead.
To take just one example: by applying machine learning to historical data, banks can predict everything from consumer spending habits to expected credit delinquency, with systems continuously learning from new data inputs.
Where should banks start with Process Intelligence?
This really depends on your bank’s unique challenges. Some of our customers start in Credit Lifecycle, others in Fraud and AML. And of course, there are interdependencies between all functions, from Customer and Sales, to Operations, to Risk and Compliance.
First and foremost, you’ll want to establish an official ‘owner’ of process. That is, a function dedicated to ensuring that the bank’s workflows are actually working at any given time. Based on my experience working in banks, and now working with many of Celonis’s banking customers, it often makes sense to house process ownership in Operations. For one, because Operations are responsible for bringing in other technologies and ensuring they work and are utilized effectively. It’s also Operations who have to anticipate challenges across functions, like whether or not there are appropriate recovery and resolution plans in place, and ensuring those get followed through. Then there’s the task of ensuring customers aren’t going to be harmed by any big changes the bank makes — which also falls on Operations…
But let’s be clear — transforming banking Operations with Process Intelligence is explicitly not an exercise in documenting processes. It’s about connecting processes across the organization, improving them, and making them as adaptive as possible, so the bank at large can get better at embracing change. For example, in Payments and Trading, banks can use Process Intelligence to adapt to T+1 settlement more easily by automatically detecting causes, regions, and types of transactions that are settled beyond SLA. Or use it to identify sources of trade amendments, optimize trade management processes, then standardize them across regions and products. Other customers use Process Intelligence to reduce duplicate transactions by monitoring versions of the same transaction, thereby preventing the risk of double payment processing. Process Intelligence can also transform highly complex cross-border-transaction processes through a single app, reducing time-to-insight while lowering the cost of payments. And that’s just four examples of what it can do for Operations — there are so many more.
It’s time to stop resisting change, and start capitalizing on it with Process Intelligence
If I can leave you with one takeaway, hopefully it’s that enabling continuous adaptation should be a key focus for your bank over the coming years, as it already is for 7 of the top 10 banks in Europe and North America.
But this post has only just scratched the surface of how Process Intelligence is helping banks to become more adaptive. In future posts, I’ll dive deeper into what’s possible in other functions, like Customer and Sales, and Risk and Compliance. Though of course, as Process Intelligence itself is highly customizable to meet individual needs, the best way to learn about what’s possible for your bank is through conversation. I’d love to hear what challenges you’re facing, why you’re struggling to maximize returns on existing transformation initiatives, and show you how Process Intelligence can help.
So: Shall we talk?
