Background
On 27 January 2020, the CSSF published its first ML/FT risk analysis on the collective investment sector (the “Analysis”).
In 2019, in order to link the national risk assessment (“NRA”) of money laundering and terrorist financing (“ML/FT”) to the entity-level ML/FT risk assessments that the CSSF performs annually on investment fund managers operating in Luxembourg, the CSSF already began an analysis of ML/FT risks affecting the collective investment sector.
The Luxembourg’s NRA concluded in its first publication back in December 2018 that the collective investment sector carries a high inherent ML/FT risk.
Substance of the report
The aim of the Analysis, apart from the establishment of a link between the NRA and the investment fund managers ML/FT risk assessments, is to develop a more granular and systematic perspective on the risks faced by the collective investment sector, to elaborate supervisory actions and identify specific sub-sectors, products and activities which present a higher risk of ML/TF.
The assessments made in the Analysis follow the general CSSF risk assessment approach defined in the CSSF’s AML/CFT risk assessment policy and focuses on the collective investments sub-sector. In this respect, a separate entity-level risk assessment for each regulated undertaking for collective investment and a clustering for three main classes have been made, namely: UCITS ManCo, AIFM and self or internally-managed UCI.
The Analysis provides for a non-exhaustive list of threats and risk mitigating factors that should be taken into account by the actors of the collective investment sector.
The Analysis furthermore gives high level recommendations to enhance the regulatory and supervisory framework.
Purpose
The CSSF, through the explanations and examples given in the Analysis, expects supervised entities involved in the collective investment sector to reflect the findings and conclusions from this sub-sector risk assessment into their frameworks.
The Analysis should help actors of the collective investment sector to better identify the risks they are facing in matters of ML/FT and to take all measures appropriate to effectively mitigate those risks.
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