A compliance team, in the traditional telling, is the brake on the car. It is the function that says no - to the onboarding that the relationship manager wants to close today, to the product launch that legal has approved but compliance has not, to the client the front office has been cultivating for three years. It is the saddest room in the building, to borrow a phrase offered with some self-awareness by the chair from Transform Finance's Amsterdam summit.

A panel session in the afternoon set out to challenge that characterisation - not by denying that compliance creates friction, but by arguing that the friction, applied intelligently, can be the foundation of something considerably more valuable: a customer relationship built on genuine understanding rather than a one-time box-ticking exercise.

The case was made from several directions, and it was more persuasive than the premise might suggest.

As the 4th Annual FinCrime Leaders Summit Europe, Amsterdam, was under Chatham House rules, no speakers or organisations have been attributed.

The Brake That Makes Speed Possible

The reframing begins with an observation about what KYC actually is, when it functions properly. It is not a regulatory cost imposed on an otherwise frictionless business relationship. It is the process through which an institution comes to know, with confidence, who its customers are and what they do. That knowledge - if collected once, maintained accurately, and shared intelligently across the institution - is the foundation of every subsequent interaction: credit decisions, fraud detection, AML monitoring, sanctions screening, and the increasingly demanding expectations of regulators who want institutions to demonstrate not just that they collected information, but that they used it.

The problem is that most institutions have not organised themselves to derive that value. KYC data sits in document stores, periodic review queues and relationship manager notes. It is not shared laterally to the fraud team that needs behavioural context, or to the AML function that needs to understand why a transaction is unusual given this specific customer's profile, or to the relationship manager who could use it to identify a genuine commercial opportunity. It is collected for compliance. It is used almost exclusively for compliance. Everything else it could enable remains locked inside the filing.

"Static data analysis is a repetitive, boring thing," one practitioner said. "The real value is in dynamic deltas - changes to a customer's profile, changes in their transactions, changes in their behaviour. That is where insight lives, not in a snapshot taken at onboarding."

The AMLA Opportunity

The introduction of the AMLA framework, widely discussed at the summit in terms of the burdens it imposes, contains within it a set of provisions that push the industry towards exactly this more dynamic, intelligence-led approach.

The prescriptive data requirements that have attracted criticism are, at the same time, a forcing function for data quality improvement. Institutions that have never built a retrievable UBO database will be required to build one. Institutions that have stored KYC information in unstandardised document formats will be required to structure it. The discipline that regulators are imposing, however uncomfortable its immediate costs, produces as a by-product the data foundation that effective AI-powered risk management requires. Post-remediation banks are, somewhat paradoxically, better placed than newer institutions that avoided the pain and now lack the baseline.

Article 75, which creates a legal framework for cross-border public-private intelligence partnerships, has a KYC dimension that was noted in passing but deserves more attention. Institutions that share typology intelligence with peer banks and with law enforcement do not just improve the collective detection of crime - they also develop a more sophisticated understanding of what genuine risk looks like, which in turn calibrates their own customer risk assessments more accurately. The institutional that knows what a money mule recruitment campaign looks like in their market is better placed to recognise an ordinary small business customer as exactly that.

The Customer as Participant

The most distinctive argument in the session came from a practitioner at a newer institution whose job title - combining financial crime prevention with customer experience and complaints - had apparently prompted comment from everyone she had ever mentioned it to.

Their argument is that the customer is not an obstacle to KYC. The customer is the most important participant in it. In most cases, the information institutions need to assess risk accurately and update it dynamically can only come from the customer. The question is whether the institution has designed its processes in a way that makes providing that information feel like a collaborative act, or a bureaucratic imposition that adds friction without apparent purpose.

The distinction matters practically. Customers who understand why their bank asks the questions it asks are more likely to answer them accurately, more likely to update their information when it changes, and more likely to report suspicious contact rather than comply with it. Customers who experience KYC as an adversarial process are less likely to do any of those things.

One institution described a move towards full transparency about its KYC requirements - publishing its policy requirements online so that prospective customers could understand precisely what they would need to provide before they began the onboarding process. It attracted attention at the summit partly because it runs against the conventional wisdom that KYC procedures should not be made public. But the argument for transparency is not naive: a customer who knows what is expected, and understands why, is not a less controllable customer. They are a more cooperative one.

From Eight Hours to Eleven Minutes

The session included a case study from an operating leasing company that had, in partnership with a compliance orchestration platform, reduced the end-to-end processing time for a KYC file from eight hours to eleven minutes. Not for a simplified customer category - for all customers, including corporate entities, across two jurisdictions.

The mechanism was orchestration: a layer of automation that routes the case through the appropriate checks in the right sequence, identifies missing information, surfaces it for analyst attention and returns the completed package to the queue in a fraction of the time previously required. Three analysts now manage 25,000 client relationships. The institution's conservative modelling suggested that without automation, achieving the same compliance standard would have required six times as many people - not hired into the compliance function, but spread across relationship management, client services and account management teams that would have been consumed by the information-gathering burden.

The commercial implication was stated directly. "Do you want to be efficient towards the client? Or do you make it fast and then sort it up afterwards?" The answer the institution chose was speed with rigour - delivering an experience that feels frictionless to the customer while maintaining the compliance standard that regulators demand.

This is not a simple formula. It requires clean data, integrated systems, well-designed workflows and a governance structure that ensures automation does not create gaps in substantive risk assessment. But the case study demonstrates that the trade-off between compliance quality and customer experience is not as fixed as the industry has historically assumed. It is, in many cases, a product of legacy system design and organisational inertia rather than inherent necessity.

The Analyst With AI

The closing thread of the session was a familiar one: the role of the human in a KYC process that is increasingly augmented by AI. The concern is that junior analysts who never develop foundational skills (because AI handles the groundwork) will eventually be unable to validate what the machine is doing.

The counterpoint, equally clearly expressed, is that AI-assisted KYC analysis is measurably better than unassisted analysis - more consistent, more thorough, faster - and that the analyst's role evolves accordingly. One practitioner cited research showing that trained users of AI compliance tools gained four to five hours of productive capacity per day compared to untrained users who gained roughly ninety minutes. The tool was the same. The outcome depended on how the human engaged with it.

"The analyst without AI will lose to the analyst with AI," one speaker said. "That is the only framing that matters."

It is also, perhaps, the best argument for treating KYC as something other than the brake on the car.

This article is part of Transform Finance's coverage of the 4th Annual FinCrime Leaders Summit Europe, Amsterdam 2026. This article reflects a session held under Chatham House rules. To respect those conditions, comments have not been attributed to individual speakers or organisations.