What financial institutions underestimate about AML transformation

As financial institutions face growing pressure to strengthen anti-money laundering controls while improving efficiency, many are exploring how AI can enhance existing processes. Yet successful AML modernisation requires more than a product decision. It demands a delivery approach that fits the realities of banking.

You joined Discai around a year ago. What attracted you to the company?

My background is in financial services consulting, where I’ve worked on everything from large IT implementations to strategy and transformation programmes. I was attracted to Discai due to the combination of its strong banking heritage with KBC Group, whilst still having the agility and innovation of a young technology company.

That combination is very unique.

I’m also really interested in the impact AI is having on financial services. We’re now seeing that transformation accelerate, particularly in areas such as financial crime and compliance. It’s an exciting space to be working in right now.

What stands out to you about how banks approach AML transformation today?

One thing that often surprises people is how quickly the technology itself can be implemented.

It’s possible to move from an initial conversation to a proof of concept in a few weeks and from proof of concept to production in just a few months. Our onboarding process is highly automated and our platform is SaaS-based, allowing clients to start testing the solution quickly.

The challenge, though, is rarely the technology. Financial institutions operate in highly regulated environments. Before a project can move forward, there are privacy reviews, security assessments, legal reviews, governance approvals and internal stakeholders that need to be involved.

Those processes are important and necessary but they do mean that the journey from initial interest to operational deployment can sometimes take a bit longer. However, our targeted and refined automation processes combined with our deep experience in these areas mean that we’re able to move through a number of these procedures quickly.

Where do organisations typically underestimate the complexity of AML modernisation?

Many organisations initially focus on the technology itself. In reality, the greater complexity often sits around governance, oversight and ensuring the organisation is ready for implementation.

For example, our solution produces a risk score that helps identify potential money laundering activity. Naturally, compliance teams, risk teams and regulators want to understand how scores are being calculated and whether those scores can be explained.

That means organisations need clear model ownership, validation processes, governance controls and stakeholder alignment before moving into production. These are all standard practices within financial services, but they still require planning and coordination.

So, AML modernisation is much broader than a software decision.

What does a successful implementation look like?

A successful implementation is one where clients see measurable value in their day-to-day operations.

The real measure of success is whether institutions are able to identify more suspicious activity while reducing unnecessary investigative work. If compliance teams spend less time reviewing false positives and more time focusing on genuine risk, then the implementation is delivering value.

Equally important is ensuring the solution fits naturally within existing processes. A key part of implementation is identifying how the solution fits within the operating model so that adoption feels practical rather than disruptive.

The goal is not simply to deploy the technology into their systems, but to also ensure the solution becomes part of the day-to-day decision-making process and delivers tangible operational benefits. For adoption to work in practice, the solution needs to be both usable and trusted by the teams working with it.

But personally, success depends on bringing together technology, governance, data and importantly, people, in a way that fits the company’s operating model.

What are the most common challenges you find during implementation?

Data is always an important consideration, but it is rarely the blocker organisations initially expect.

Most financial institutions today are not starting from scratch. Over recent years, significant investments have been made in data governance, infrastructure and data quality initiatives. As a result, organisations are generally in a much stronger position than they often realise when beginning an AML transformation programme.

The focus is therefore less on achieving perfect data upfront and more on understanding the available data, working with it in a structured way and progressively improving over time.

Successful programmes treat data preparation as part of the implementation journey rather than a prerequisite that must be fully completed before work can begin. A phased approach allows organisations to start generating value while continuing to refine and enhance their data foundations.

The key is having the right expertise around the table to assess what is available, identify opportunities for improvement and create a practical path forward. In most cases, organisations are much closer to being implementation-ready than they initially assume.

How does Discai help keep projects on track?

A structured and collaborative delivery approach is key.

Like most modern technology companies, we use agile methodologies that allow us to work closely with clients throughout the implementation journey. Regular reviews and checkpoints help ensure that issues are identified early rather than emerging much later in the project.

We also place a strong emphasis on sponsorship and stakeholder engagement.

Throughout my career, one of the biggest factors behind successful projects has been having the right executive sponsor. Strong sponsors help align stakeholders and overcome obstacles while still maintaining momentum during the implementation phase. They are able to bring clarity to the process, which is crucial when competing priorities emerge.

When that alignment exists, implementation becomes significantly smoother for everyone involved.

Financial institutions often worry about disruption. How do you minimise operational impact?

Every change, especially when dealing with large financial institutions, introduces some degree of disruption, particularly within compliance functions where stability and control are understandably valued.

That’s why flexibility is such an important part of our delivery model.

Some institutions choose to integrate AI-based solutions deeply into their current workflows. Others prefer to introduce it alongside existing systems and gradually expand its role over time.

The important point is that clients are not forced into a single implementation model.

They can adopt the solution in a way that aligns with their infrastructure, risk appetite and operational priorities.

A phased or pilot-based approach allows institutions to evaluate the solution, build confidence and demonstrate value before committing to broader deployment.

Security and privacy are major concerns for financial institutions. How do you address them?

Security and privacy are foundational.

Before discussing functionality, clients need confidence that their data will be protected and handled according to strict security and governance standards. That’s why certifications and security controls are so important and the fact that Discai has the strength of being ISO 27001 certified means that clients know that we take security standards very seriously.

Financial institutions are right to ask detailed questions about data protection, segregation and governance. They want to understand exactly how their data is managed and how models are built.

These conversations naturally occur at the start and are a standard part of the process. We recognise their importance and work closely with clients to provide the transparency and assurance they require.

What role does trust play in successful transformation?

Trust is central to every transformation programme.

Clients need confidence that their chosen partner understands both the regulatory environment and the operational realities of financial crime prevention.

One of the reasons why clients are drawn to us is the strength and depth of expertise across the organisation. Virtually all members of the Discai team have worked for many years directly in banking, compliance and financial crime functions themselves. They understand the challenges clients face because they have experienced them first-hand.

That shared understanding helps create productive conversations and accelerates confidence throughout the onboarding process.

What advice would you give organisations considering AML modernisation?

Don’t be intimidated by the process.

Modern AML transformation does not have to be a large-scale commitment. Many institutions start with a proof of concept or pilot that allows them to evaluate the benefits in a controlled, low-risk environment.

The key is to approach it as both a technology initiative and a change initiative. Consider the data, the governance, the stakeholders and the operational processes from the beginning.

Most importantly, work with partners who understand both the technology and the realities of implementation.

In many cases, meaningful improvements can be achieved without large-scale transformation. Starting small, focusing on outcomes and building step by step makes the process of AML transformation far more manageable than many organisations may initially expect.