Accountancy Europe submitted its feedback on the EU Anti-Money Laundering Authority’s (AMLA) draft RTS on the assessment of the inherent and residual risk profile of obliged entities in the non-financial sector.
Accountancy Europe recognises the need for supervisory data to help supervisors understand ML/TF risks across the supervised population and support effective risk-based supervision. However, we consider the proposed dataset very extensive and disproportionate, while the value of many data points for understanding ML/TF risk remains unclear. The RTS should focus on data that genuinely supports effective risk assessment.
Accountancy Europe highlights several key recommendations in its submission, in particular:
We caution against relying too heavily on quantitative indicators to assess ML/TF risk. A numerical data point, considered in isolation and without sufficient context on the obliged entity, its clients, services and circumstances, may provide limited insight into the actual level of risk.
The significant effort required to collect, aggregate and report such data should therefore be weighed against its supervisory value. Data collection should focus on information that genuinely helps supervisors identify and understand ML/TF risk. Greater use of bandings and more targeted, risk-focused questions could in many cases provide sufficient supervisory insight while reducing unnecessary data collection.
The approach does not sufficiently reflect the heterogeneity of the non-financial sector. Some data requirements are exceptionally detailed and risk adding regulatory burden, particularly for very small businesses, without improving supervisors’ understanding of risk profile.
Some data may not be maintained separately due to overlapping services, while certain data points are not relevant to all obliged entities. Many data points would require new reporting processes, potentially creating a disproportionate burden for low-risk firms. At the same time, small size does not necessarily mean low AML/CFT risk, and any simplified approach should therefore be driven by risk assessment rather than primarily by size.
Quantitative measures do not necessarily provide a meaningful indication of the quality or effectiveness of AML/CFT controls. For example, the number of training hours or completion rates do not demonstrate that training remains relevant, risk-based or effective. Information on the type of training provided may be more useful for supervisory purposes than numerical information alone.
The approach would create significant implementation burdens, including the collection, validation and reporting of data that may not currently be maintained in an aggregated format and the implementation of the necessary systems or tools.
The proposed annual reassessment cycle also appears disproportionate and would create significant recurring costs. The implementation of the RTS will therefore require sufficient lead time and investment in IT systems.
