Friendly fraud or first-party fraud? Authorized push payment fraud, real-time payment or authorized Fraud? Across the world, the terms and definitions we're using to describe fraud differs significantly. And, while the differences might seem to be insignificant and carry minimal consequences, the reality is that the industry is plagued with inconsistent fraud classifications – and the ramifications can be anything but insignificant.
If we're wanting consumers to be more savvy and aware, having numerous definitions and terms for the same fraud MOs leads to complexity and increased risk of pushing consumers away, rather than educating them.
To discuss the challenges around fraud language, we sat down with Andres Rapela, AVP, Secure Payments and Payments Improvement at the Federal Reserve. We wanted to learn more about their Fraud Classifier Model which they created to help address the industry-wide challenge of inconsistent classification for fraud involving ACH, wire or check payments.
The lack of a common language limits our ability to fully understand and fight fraud. Inconsistent language can cause strategy and important conversations about fraud to become convoluted or deviate from the original purpose. Most importantly, inconsistent classification creates inconsistent data – which can lead to inaccurate analysis and assessments of the extent of fraud within organizations.
In our conversation with Andres, we cover:
1. Get the full run through – What is Fraud Classifier model? And how did it come about?
2. Discuss why proper fraud classification matters
3. Examine the impact of inconsistent fraud classification
4. Look at where organizations can start their journey to standardization.
