FATF Examines Collaborative Analytics and the Need for Privacy

An AML risk information sharing platform in trial operation in China allows FIs to check whether a customer is labelled high risk by other FIs without any customer data being exchanged. 

The FATF (Financial Action Task Force) has published a new report exploring the use of data pooling and collaborative analytics to facilitate AML/CTF efforts.

The report forms part of the FATF’s project to explore how technological innovation can make AML/CTF efforts more effective. It was finalised at last month’s FATF Plenary.

“Technological advances in recent years allow financial institutions to analyse large amounts of structured and unstructured data more efficiently and identify patterns and trends more effectively,” the FATF says.

The report examines commercially available or emerging technologies that facilitate advanced AML/CFT analytics within regulated entities, and technologies that allow collaborative analytics between FIs.

“By pooling data and using collaborative analytics, financial institutions can better understand, assess, and mitigate money laundering and terrorist financing risks,” the report says.

“This will result in a more dynamic, effective and efficient identification of these activities, and help the private sector comply with anti-money laundering and counter terrorist financing requirements in a timelier and less burdensome manner.”

Data pooling and collaborative analytics can also reduce false positives and help prevent criminals from exploiting information gaps as they engage with multiple domestic and international FIs, each having a limited and partial view of transactions, the report says.

However, such techniques may also infringe on the protection of individual and fundamental rights. “Therefore, it is imperative that any exchange of information respects national and international legal frameworks for data protection and privacy.”

The report also highlights the potential use of privacy-enhancing technologies (PETs) – which rely on a range of different cryptographic tools to protect data and privacy.

PETs are intended to enable multiple parties to interact meaningfully to achieve an application goal, without revealing underlying private information to one another or to third parties.

The report highlights an AML risk information sharing platform currently in trial operation among China FIs. The platform integrates blockchain, digital identity, and PETs, allowing participating FIs to encrypt high-risk customer information, including digital identity numbers and risk labels, and then upload it to the blockchain.

When a participating institution inquires about the customer, a match is made on the blockchain through a secure computing platform, and the AML risk information is extracted and returned in cipher text to be decrypted.

The processing unit immediately deletes any records of the computations to ensure privacy, while alerting the inquiring FI if an individual is also high-risk at another FI or being inquired about by other FIs. No actual exchange of customer data between FIs takes place.

The report is available here.

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