HKMA releases guidance on external data for AML

The Hong Kong Monetary Authority (HKMA) has released new guidance on how to use external data in AML/CFT systems. The report summarises the results of a recent thematic review of Authorised Institutions’ (AIs) end-to-end processes which use information and data from various external sources to prevent risks related to money laundering and terrorism financing.

The 10-page document includes specific and highly actionable recommendations in the following four areas:

1. Integration of information and data from external sources as a means to enhance the targeting and mitigation of specific ML/TF risks
2. Success factors for integrating external information and data to enhance effectiveness of AIs’ AML/CFT systems
3. Need for further collaboration and contribution of case-specific and typological information into the AML/CFT ecosystem.
4. Performance measurements to analyse the efficiency and effectiveness of integration of external information and data into AML/CFT systems.

Somehow unsurprisingly, institutions that use advanced technology to increase the level of external information and data integration demonstrated stronger capabilities to identify higher-risk relationships, suspicious transactions and networks of mule accounts compared to AIs relying on less sophisticated tools.

The guidance also remarks that on-going senior management support and commitment, including attention to resource allocation to related work, is a key element to ensure the success of any AML/CFT initiative. Other important factors include data and process readiness, as previously explored in the HKMA’s “AML/CFT Regtech: Case Studies and Insights” report released in January 2021.

We often hear how closer collaboration and knowledge sharing are essential to protect the industry from emerging fraud and money laundering tactics, especially in light of the new risks generated by the COVID-19 pandemic. In its report, the HKMA highlights some good examples of institutions proactively initiating closer collaboration with fellow AIs and stakeholders in the ecosystem. These include the use of Fraud and Money Laundering Intelligence Taskforce (FMLIT) Alerts to inform the wider ecosystem of new investigative techniques and review results explored by specific FIs.

Finally, while all reviewed AIs recognised the value of integrating external information and data into AML/CFT systems, not all had established a framework to analyse the efficiency and effectiveness of outputs and evaluate outcomes. In this regard, the Hong Kong regulator encourages institutions to promptly develop a performance measurement framework to include both tangible values, such as the number of Suspicious Transaction Reports (STRs) filed, and intangible values, such as the impact or difference made to its customers and benefits to bank staff.