Federal Reserve’s FraudClassifier model helps classify fraud involving payments

The Federal Reserve published the FraudClassifier model – a set of tools and materials to help provide a consistent way to classify and better understand the magnitude of fraudulent activity and how it occurs across the payments industry.

The model was developed by the Fraud Definitions Work Group, which was comprised of Federal Reserve and payments industry fraud experts.

“The FraudClassifier model can help address the industrywide challenge of inconsistent classifications for fraud involving ACH, wire, or check payments,” said Jim Cunha, secure payments strategy leader and senior vice president at the Federal Reserve Bank of Boston.

“The FraudClassifier model enables payments stakeholders to classify fraud in a simple and similar manner. It can be applied across an organization to help ensure greater internal consistency in fraud classification, more robust information and better fraud tracking.”

The key advantage of the FraudClassifier model is the ability for organizations to use it to classify fraud independently of payment type, payment channel or other payment characteristics.

The model presents a series of questions, beginning with who initiated the payment to differentiate payments initiated by authorized or unauthorized parties. Each of the classifications is supported by definitions that allow for consistent application of the FraudClassifier model across the industry.

The Fraud Definitions Work Group also developed and recommended an industry adoption roadmap, which outlines a strategy and potential steps to encourage voluntary industrywide use of the FraudClassifier model.