- Banks need to keep up with fraudsters by adopting technology
- A group of prominent check fraud experts predicts $24 million in fraud damage to banks
- Automated check fraud detection is absolutely crucial
Todd Robertson, senior vice president of business development for ARGO, contributed a post to BAI.org outlining his contention -- with which we tend to agree -- that mere tactical maneuvers are not sufficient to defeat fraud.
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%.
When examining the losses to banks and credit unions, Mr. Robertson brings clarity to the question: How bad is check fraud in terms of damage 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.
Automating Check Fraud Detection
For decades, many financial institution took a "tactical approach" to combat check fraud. However, Mr. Robertson points out three primary technologies that will automate check fraud detection -- significantly lowering the number of checks that need manual review:
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.
As Mr. Robertson concludes:
...It's 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.
This is an approach with which we agree -- however, as fraudsters getting more sophisticated with their tactics, this may not be enough.
Complementing transactional analysis with image forensics AI -- which supercharges the capabilities of check stock validation and signature verification, while increasing detection capabilities with new and innovative analyzers such as Writer Verification -- is the latest approach that has proven most effective against check fraud. By not only analyzing the transaction, but additional fields from the check as well as the writing style, more alterations, counterfeits, and forgeries are able to be detected before the financial institution and their customers experience losses.