How can data be better leveraged to improve AML reporting efficiency?

Alice Lehnert: Data scarcity does not represent the real issue. Information already exists across different databases, e.g. with management companies, transfer agents, or distributors. The real question concerns access: why can firms not retrieve the right data at the right moment?

That difficulty reflects a data architecture problem rather than a data problem. Operational experience inside these data flows consistently highlights three structural weaknesses.

The first is fragmentation. Data often sits in silos that were never designed to communicate. When a questionnaire requests figures such as customers involved in high-risk activities, teams must manually extract, cross-reference and reconcile information from different sources. The effort varies depending on the structure, looking for example at a private equity fund with a limited investor base or a widely distributed UCITS, but the underlying problem remains the same.

Katja Krieg: A second weakness concerns manual input. AML reports, risk assessments and regulatory questionnaires should emerge from structured data pipelines rather than random documents and files. If numbers cannot be traced back to a source system, they represent assertions rather than evidence. Much of our work with clients therefore focuses on transforming compliance reporting into a clean data retrieval exercise. A third difficulty comes from reactive data collection, with many entities mobilising information only when a questionnaire becomes due.

Alice Lehnert: Real efficiency will not emerge from repeating that same approach. Sustainable reporting requires well-designed and maintained data architecture capable of feeding multiple AML reports. Good architecture compounds benefit over time; poor architecture compounds inefficiency.

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“Maintenance is always cheaper than repair.”

How should AML processes adapt to evolving regulatory reporting requirements?

Alice Lehnert: Regulatory evolution often receives the blame, yet the real challenge again concerns data structure. If the architecture remains sound, firms do not need to worry about every new reporting requirement. Supervisory logic rarely changes. Regulators simply want proof that control processes function effectively, and strong data architecture naturally produces that evidence.

Katja Krieg: Two developments illustrate this shift. First, the European AML framework increasingly moves from national interpretation toward a single EU rulebook directly applicable across member states. Such harmonisation requires clear data mapping. Second, AML reports are no longer narrative documents. Supervisors now request numbers: risk scores by customer type, product, geography or distribution channel, as well as operational control indicators.

Katja Krieg: This transformation does not imply enterprise-grade infrastructure for every entity. The key question concerns proportionality: what framework fits a specific investor base, risk profile and delegate structure? Determining what is sufficient and holds up under scrutiny requires judgement.

Alice Lehnert: Firms least exposed to regulatory reporting difficulties share one characteristic: current data, strong governance and responsive mapping. When new regulations appear, they simply adjust existing architecture instead of launching new projects.

What is your vision for AML reporting and data strategy over the next five years?

Alice Lehnert: The coming years will distinguish organisations that develop data architecture as a genuine capability from those still treating data as an administrative burden. That difference will become visible as efficient infrastructure frees resources previously absorbed by reporting tasks. Compliance professionals will therefore become more data literate and (hopefully) spend less time on administrative work.

Katja Krieg: What we build with clients today is the infrastructure that makes this transition manageable. Success relies on combining two elements: a deep understanding of regulatory frameworks and operational expertise in sourcing and maintaining reliable data sets. Organisations capable of combining both will hold the strongest position in the years ahead.

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