Payments Security

FraudClassifier Model: Helping a Corporate Credit Union Classify Fraud

Released in June 2020, the FraudClassifierSM model provides an intuitive fraud classification approach to help organizations speak the same language and obtain a holistic picture of fraud involving payments. Fast forward to the present, where Neil Kumar, vice president of compliance at Alloya Corporate Federal Credit Union (Off-site), explains how this organization has incorporated the model into its existing processes.

Kumar did not need to be convinced to adopt the FraudClassifier model – even though Alloya already had a robust system to track both suspected and confirmed fraud. Alloya is a not-for-profit, wholesale financial institution offering a variety of payment solutions, including ACH processing, funds transfers and check processing, among other financial products and services, to its 1,400 credit union member-owners across the United States. The company was founded in 2011 and is based in Naperville, Ill.

Neil Kumar“When I heard about how the FraudClassifier model offers a standard way to classify fraud, it just seemed so logical,” said Kumar. “There are lots of different ways to track fraud, but until the model was released, there wasn’t a common fraud terminology across the industry that would enable us to speak the same language about fraud. At Alloya, we also like that the model can be used to classify fraud involving any type of payment, although our company currently applies it only to outgoing wire transfers. With payments accelerating in speed, I think it’s more important than ever for our industry to consistently classify fraud.”

Adopting the Model

Kumar says it has been easy to map the FraudClassifier model to Alloya’s existing fraud tracking approach, which takes the model one step further by including an additional level of detail. For example, the model provides two classification options when an authorized party is manipulated to initiate a payment: products and services fraud, or relationship and trust fraud. Alloya classifies events one level deeper, indicating the type of scam or scheme used (e.g., romance, investments, impostor or prepayments fraud, such as timeshare scams). This helps Alloya staff understand how the fraud was conducted and identify trends. In turn, this information can be used to educate Alloya’s credit union members – and ultimately, end consumers – on how to avoid popular scams.

“If we want to have a larger, industrywide impact on combatting fraud, I recommend leveraging the FraudClassifier model to facilitate the process of getting everyone on the same page.”

As Kumar reflects on the industrywide potential offered by the FraudClassifier model, he says increased fraud information-sharing among stakeholders using the model can facilitate trend analysis across the industry, significantly improve fraud management and deter fraud. He emphasizes the model’s primary benefit is that it provides a common way for the industry to talk about fraud. “The FraudClassifier model is a great place to start for organizations that don’t yet have a fraud classification approach,” Kumar said.

Who Uses the FraudClassifier Model?

The FraudClassifier model is gaining traction in the industry as stakeholders increasingly become aware of it and begin to use it within their organizations. LexisNexis® Risk Solutions recently conducted a study (Off-site) of 500+ risk and fraud executives working for financial services and lending companies in the U.S. and Canada. A total of 46% of survey respondents from U.S. retail and commercial financial institutions indicated they are [familiar with and] using the model to classify fraud related to payments. For respondents who were aware of the model but not currently using it, 75% indicated their organization plans to use the model in the near future.

To learn more about the industry’s awareness, use and intended use of the model – as well as overall recent fraud trends and effective fraud management practices – check out the 2021 LexisNexis® True Cost of FraudTM Study (Off-site).

The 2021 LexisNexis® True Cost of FraudTM Study provides a holistic snapshot of current fraud trends in the U.S. and Canadian financial services and lending markets. As implied by the name of the study, the analysis looks beyond the dollar value of a fraudulent transaction and considers related costs, such as investigative, processing and legal fees and recovery expenses. The survey also discusses how the COVID-19 pandemic has impacted fraud costs and targeted channels. Note: LexisNexis requests contact information before site visitors can download the report.

Register to access educational resources and support tools for the FraudClassifier model, such as a downloadable version of the model and supporting definitions, as well as a spreadsheet-based fraud classification tool.

Sharing and use of the FraudClassifier model throughout the industry is encouraged; any adoption of the FraudClassifier model is voluntary at the discretion of each individual entity. The FraudClassifier model is not intended to result in mandates or regulations, and does not give any legal status, rights or responsibilities, nor is the FraudClassifier model intended to define or imply liabilities for fraud loss or create legal definitions, regulatory or reporting requirements. Absent written consent, the FraudClassifier model may not be used in a manner that suggests the Federal Reserve endorses a third-party product or service.

“FraudClassifier” is a service mark of the Federal Reserve Banks. A list of marks related to financial services products that are offered to financial institutions by the Federal Reserve Banks is available at