Fraudsters create scams that deceive individuals into depositing counterfeit checks in their accounts. At the direction of the criminal, financial institution customers who do not realize a deposited check was fraudulent may send funds from a check deposit to someone else, i.e., the fraudster. As a result, customers may become unwitting money mules by helping fraudsters transfer illicit funds.
To help prevent this type of fraud from happening, financial institutions can leverage the ScamClassifier model for check scams (Off-site). The ScamClassifier model divides scams into either a products or services scam or a relationship and trust scam. Relationship and trust scams typically involve a transfer of funds to an imposter pretending to be a trusted or authoritative party, where there is no expectation or promise of merchandise in exchange for the funds.
Explore a check fraud scheme involving an online romance (Off-site), the second in an article series focused on ways to detect check fraud and scams. The article includes an example scenario where an online relationship is cultivated between an unsuspecting victim and a “love interest,” who is really a criminal. Over a long period of time, the “love interest” works to ensure that their victim deeply trusts them. Once they establish that sense of trust, the criminal is able to convince the victim to deposit a fraudulent check and forward the money to them. The victim later realizes the check was fraudulent and discovers the supposed “love interest” was fabricated by a criminal.
Improve Fraud Mitigation and Education
The ScamClassifier model is a tool that provides insight into the types of scams that target individuals, including those related to check fraud and money mule activity. This understanding can be used to increase awareness of scams among financial institution employees and customers. Information on the different types of money mules and the signs associated with money mule activity is available on the FBI website (Off-site).
Note: The ScamClassifier model is not intended to result in mandates or regulations, and does not give any legal status, rights or responsibilities, nor is it intended to define or imply liabilities for loss or create legal definitions, regulatory or reporting requirements. While sharing and use of the ScamClassifier model throughout the industry is encouraged, any adoption of the ScamClassifier model is voluntary at the discretion of each individual entity. Absent written consent, the ScamClassifier model may not be used in a manner that suggests the Federal Reserve endorses a third-party product or service.
