Fraud and Financial Crime Convergence: It’s Really Here!

Four key challenges are driving financial institutions to bring fraud and financial crime management together

It feels like we have been discussing the convergence of fraud and financial crime for at least a decade. I’ve certainly shared my views and predictions, including one of my recent blog posts Fraud and Financial Crime Product Strategy: C is for Convergence, but just in time for summer, the strategy is finally making a splash. As my colleague Sarah Rutherford shared in her post, Fraud and Financial Crime Management Are Converging – But How Fast?, over 50% of financial institutions around the world are aiming to achieve convergence in less than three years.

Further supporting that view is Daniel Mayo, Chief Analyst of Financial Service Technology at Ovum. In this short video, Daniel recently shared that “most institutions do actually have ambitions to either integrate or collaborate between the AML and financial fraud functions.” He also shared his view on the increasing use of AI across fraud and AML. Check out the video below to learn more.

Convergence Drivers

After all this time, what is driving this significant shift to unite fraud and financial crime management?

Four key challenges are shared across the two functions:

  1. Isolated data – Machine learning is only as good as the data that your systems ingest. Today, the two fraud and financial crime teams typically work separately towards having the right data at the right time. Shared data and efforts could benefit both sides of the organization leading to increased efficiency and more robust data.
     
  2. Mule activity – Money mules, people whose accounts are used by criminals for money laundering — at times unknowingly — have become a key enabler of both fraud and money laundering. This has grown considerably with the introduction of real-time payments, which not only enable customers to move money quickly but also fraudsters. Since these payment transactions are irrevocable, it leaves little room for banks to recover those funds, leading to greater investment in stopping mule activity. 
     
  3. Operating expenses – Financial institutions are trying to compress operating costs amid mounting expenses. Since there is an estimated 80% overlap in software functionality between legacy fraud and anti-money laundering systems, institutions are now aiming to take advantage of significant cost savings.
     
  4. Faster payments – This bears repeating. While customers are enjoying the ability to move money faster, so are fraudsters, making it nearly impossible to get fraudulent funds back. However, if fraud and AML teams work closely together using a centralized solution, they can get a much clearer view of the crime rings to better combat fraud and financial crime.

I know it can all seem overwhelming and unclear on where to get started, but in my next post, I’ll provide some easy, practical tips to get started. If you can’t wait for that, don’t hesitate to check out my recent webinar, Fraud & Financial Crime Convergence: Demanding Smarter Decisions, which is available on-demand. Follow me on Twitter @FraudBird.

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