Data Analytics to combat financial crime

Financial crime is gaining ground. The presence of new technologies has given criminals new opportunities for seizing huge amounts illegal gain through insidious methods. Financial crime is bound to get bigger in Industry 4.0.

In light of the developments, The Anti-Money Laundering (AML) and Countering the Financing of Terrorism (CFT) Industry Partnership (ACIP) launched a paper to encourage the adoption of data analytics solutions by financial institutions.

Set up in April 2017, the ACIP brings together both stakeholders from industry and government and provides a dedicated platform to discuss key transnational illicit finance risks confronting Singapore’s financial and non-financial sectors. ACIP also identifies and promotes areas to uplift ML/FT risk understanding in Singapore.

How Data Analytics can Fight Crime

New data analytics methods are widely agreed to be beneficial in AML/CFT. The paper reads, “Through the leveraging of data, existing and rapidly developing technology, and data analytics models, FIs could potentially improve the effectiveness of their AML/CFT measures and address some key weaknesses with the current AML/CFT approaches.”

Major banks shared their experiences in using data analytics techniques to combat financial crime in drafting the paper. There are well-established use cases and more experimental work detailed in the paper. Thus, the paper provides an understanding of the current state of data analytics deployment in the area of AML/CFT.

Mr David Chew, Director, Commercial Affairs Department of the Singapore Police Force and co-chair of ACIP, said, “Data analytics is an invaluable tool in identifying and preventing financial crime, by helping financial institutions sieve through the large volumes of data generated daily to identify suspicious transactions. The industry must be ever vigilant against the abuse of our financial system and we hope that the paper will encourage the industry to build robust data analytic capabilities to strengthen Singapore’s resilience against such threats.”

Details of the Paper

Additionally, the paper has examples of effective improvements to learn from. An example is the 40% reduction in false positives and 5% increase in true positives delivered by a bank’s proof-of-concept conducted on a machine learning solution for transaction monitoring.

Key governance and implementation issues are addressed in the paper since the field is still nascent. Important considerations on the validation, audit and explainability of data analytics models to gain assurance that models built can reliably improve the detection of illicit activities are included.

Areas in AML/CFT analytics for closer industry and private-public cooperation are highlighted. The paper suggests this could yield significant benefits. By working with the Institute of Banking and Finance on dedicated career paths and skills development for AML/CFT analytics professionals, and workshops for financial institutions, MAS and the Commercial Affairs Department can collectively address key policy and operational issues in AML/CFT analytics. This includes model governance and using data analytics to target high-risk areas.

Ms Ho Hern Shin, Assistant Managing Director (Banking and Insurance), MAS and cochair of ACIP, said “MAS strongly encourages the use of data analytics in AML/CFT, which has the potential for bringing about transformative change in our approach to combating financial crime. The strong showing by analytics solutions providers during the recent Singapore Fintech Festival shows the growing opportunities to adopt such techniques. We are heartened that the ACIP banks are willing to share their experiences with other financial institutions looking to embark on such projects. MAS also looks forward to working with the industry on areas of collaboration in AML/CFT analytics.”

The full paper can be read here.