What’s the role of predictive analytics in fraud and AML prevention?
Clinton Mills, Managing Director for GBG DecTech recently contributed an article to the Journal of Financial Compliance exploring the role of predictive analytics in fraud and AML management.
In his piece, Clinton explains predictive analytics, how losses to financial crime can be reduced, and how to find the right balance between investment in technology and human resources.
The common problem we are all facing in fraud, risk and compliance these days is how we address the challenge of false positive rates. We want to avoid an overwhelming number of alerts without compromising our effectiveness in fraud prevention, anti-money laundering (AML) and counter-terrorism financing (CTF). The goal is to optimise processes to allow legitimate customers through quickly while ensuring any suspicious activity is blocked or reviewed.
In the article, Clinton goes into more detail about:
- The scope of the problem – the total cost of fraud, money laundering, terrorism financing attempts and the set of risks which face financial institutions
- How institutions need to have a firmer grasp of detecting financial crime – for example, application and transaction fraud
- The importance of tackling these problems, in particular, terrorism financing
- The way organisations can manage and handle resource challenges
- Challenges in fraud prevention and money laundering detection – what are the five main difficulties associated with fraud prevention?
- Predictive analytics – what is it and where can it be used?
- Building effective fraud models and data used for these models
- The range of monetary channels which organisations must consider to remain compliant
If you’d like to find out more, you can read the full article here.
GBG can help businesses manage fraud prevention, and address AML and CTF requirements, from the moment a customer applies for an account through to each and every individual transaction that customer makes. Our end-to-end decision support technologies can identify the level of risk associated with a customer or a transaction. Suspicious or high risk activity is flagged for review or automatically blocked. Legitimate activity is processed instantly, creating an excellent customer experience and allowing fraud teams to focus on the high risk and suspicious activity.