Even in today’s digital environment, check fraud continues to thrive. Check fraud and money laundering continue to be the most reoccurring forms of financial crimes that are committed, with most financial institutions seeing millions of attempted attacks a year. Many institutions have seen check fraud losses double in the past 24 months.
With check fraud growing, we can no longer just tactically combat its effects. Fraudsters are continuing to cultivate new and ever more outlandish scams to swindle Americans out of their earnings. Check fraud still appears in traditional forms, including basic counterfeit checks, forging checks, paperhanging (writing a check from a closed account) and check kiting. Some of the more innovative check fraud schemes include check mail fraud, check washing, use of the Dark Web and identity check theft. However, the most traditional, low-tech method – over-the-counter fraud – continues to be the channel with the greatest loss, at 49 percent. According to fraud experts, attempted check fraud is up more than 100% compared to 2021, even though check volume is only up 8%.
One question worth asking at this point is “How monetarily detrimental is check fraud to financial institutions?” Even with the recent digital transformation, a group of prominent check fraud experts predicts that in 2023 check fraud will result in $24 billion in damages at banks. This is based on a 50% increase over the American Bankers Association’s last estimate published in 2020. In 2022, ABA established a new check fraud committee to understand current trends and better position the industry to respond to the heightened activity.
Fraudsters are working day in and day out to develop new techniques that will put financial institutions at risk. Curbing check fraud is a high priority right now, and that includes improving the systems used to detect it in order to mitigate it. In order to prevent losses and customer impact, successful banks have strategically automated three key functional areas:
Transaction analysis: Transaction analysis enables banks and credit unions to process debits and credits contained in deposits and withdrawals, and identify suspicious items like out-of- range check numbers and check amounts and duplicate check numbers. With this capability, tests at the account and entity level can be made, measuring such things as account velocity, account volume, and deposits or withdrawals of unusual amounts. This data helps determine items to flag as suspicious.
Check stock validation: Analyzing presented check images against historical, referenced check images validates the consistency and accuracy of check stock. With this capability in place, financial institutions can identify counterfeit in-clearing and over-the-counter checks faster and with increased accuracy and reliability than visual inspections.
Signature verification: Using machine learning algorithms and sophisticated decision trees to provide a detailed analysis of check signatures results in efficient evaluation of suspect in-clearing and over-the-counter checks, and thus increased confidence levels for acceptance and return decisions. In addition, comparing digitized signatures to referenced images, managing multiple signatories on the same account, and monitoring items requiring dual signatures to validate check signatures on personal and business accounts helps reduce risk for banks.
With sophisticated fraudsters conducting repetitive, small-deposit account transaction fraud attempts, it is increasingly difficult for financial institutions to detect and prevent fraudulent activity. To successfully fend off these attempts, it is important to bolster security with an automated check fraud detection solution that combines transaction analysis, check stock validation and signature verification. Equipping banks with automated solutions can help institutions collectively save billions each year by deterring fraudulent attacks.
Todd Robertson is senior vice president of business development for ARGO
