Check fraud continues to challenge financial institutions across the United States. Nasdaq found that in 2023, check fraud losses totaled $21 billion in the Americas, representing nearly 80% of total global check fraud losses. In response to rising concerns around check fraud, FinCEN has released a new Financial Trend Analysis (FTA), Mail Theft-Related Check Fraud: Threat Pattern & Trend Information, February to August 2023.
FinCEN’s FTA examines trends identified in Bank Secrecy Act (BSA) data linked to mail theft-related check fraud from the review period of February 27 and August 31, 2023. This blog explores three key insights from the FTA and how your institution can prevent stolen check fraud.
1. Criminals are Cashing in on Check Fraud
Check fraud scams prove to be very lucrative for criminals. According to the FTA, more than $688 million was associated with mail theft-related check fraud losses during the review period. The FTA also found that the average activity amount per BSA report for mail theft-related check fraud was $44,774, while the median amount was $14,215.
2. Technology is Abused to Avoid Human Contact
FinCEN’s FTA found that criminals prefer to deposit checks via ATM or remote deposit capture, or open accounts online using fraudulent information or a money mule in cases of new account fraud. These methods allow fraudsters to avoid in-person contact with depository institution personnel, eliminating an interaction that could lead to unwanted suspicion or detection of the fraud. Remote deposit capture has the added benefit that the physical check is not physically handled by financial institution employees — advantageous for scammers using poorly made counterfeits.
3. Checks are Most Often Stolen & Altered
In response to efforts from financial institutions to combat more traditional check fraud typologies, criminals have shifted to stealing checks from the mail and exploiting them for their own gain. The United States Postal Service (USPS) reported 38,500 high-volume mail theft incidents from October 2021 to October 2022 and over 25,000 incidents in the first half of 2023. According to the FTA, criminals most often altered and then negotiated these stolen checks, accounting for 44% of BSA reports. Second most often, stolen checks were used as a template to create counterfeits — reflected in 26% of BSA reports. In 20% of BSA reports, criminals fraudulently signed and deposited the checks.
4. Check Fraud Scams Range in Sophistication
Importantly, FinCEN’s FTA provided an overview of stolen check fraud methodologies, and ranked them in terms of sophistication. Methods where the check was not washed, including fraudulently endorsing a check, altering the payee or dollar amount, and third-party payments, were considered less sophisticated and easier for financial institutions to identify.
Moderately sophisticated schemes include check washing, selling stolen check information online, using compromised check information to create counterfeit checks, and stealing newly ordered checks from the mail. These forms require more complex identification methods for financial institutions to prevent.
The most sophisticated methods for mail theft-related check fraud included new account fraud, where criminals open new accounts to negotiate checks, check fraud as part of romance or employment scams, and insider involvement, where an employee at a financial institution or USPS aids a criminal. These methods are the most complex for financial institutions to solve and require innovative solutions to combat effectively.
Solving Complex Check Fraud with Consortium Analytics & Machine Learning
Criminals prefer stolen checks due to the ability to evade conventional detection approaches such as Magnetic Ink Character Recognition (MICR), image analysis and positive pay. A consortium approach complimented by machine learning analytics is the key to helping institutions stay ahead and detect this more sophisticated check fraud typology.
Unique in the industry, Nasdaq Verafin’s check fraud solution combines consortium insight into deposit-side risk with precision machine learning analytics for in-clearing check fraud. These machine learning analytics are trained on data from thousands of customers, 575 million profiled counterparties, and billions of check image examples with many confirmed as true fraud. The result is a complete solution to the industry’s pervasive check fraud challenge, offering superior fraud detection with fewer false positives – even for the most challenging typologies.
As criminals continue to gravitate toward sophisticated check scams such as mail theft-related check fraud, it is more important than ever that financial institutions embrace collaborative and innovative means of detection.
