Say Hello to Big Data - and Goodbye to Bank Deposit Fraud

Blog Article
Say Hello to Big Data - and Goodbye to Bank Deposit Fraud

Bank deposit fraud is hitting financial institutions (FIs) on all fronts these days. While old-school, low-tech deposit fraud at the teller window hasn't disappeared, fraudsters have evolved. Now, they’re incorporating new schemes and tactics to exploit deposit channels that don’t require face-to-face human interactions—like ATMs and remote deposit capture (RDC) technologies.

Let’s explore why bank deposit fraud is such a prevalent and persistent problem for banks and credit unions. More importantly, we'll explain how FIs can fight back using a powerful one-two punch of big data and predictive analytics.

Deposit fraud and check fraud go hand-in-hand.

Bank deposit fraud is inextricably connected to check fraud. So, with people using fewer checks these days in favor of digital payment options, you’d think check fraud would be on the decline. No such luck!

Check fraud is surging as criminals have become increasingly prolific and relentless in their efforts to make money off checks—and that includes devising new deposit fraud tactics. A 2022 Aite-Novarica report found first-party check fraud and deposit fraud are on the rise—with 38 percent of FIs reporting a more than 20 percent increase compared to the previous year1.

Common deposit fraud schemes and scams include:

  • Depositing a fake, forged or altered check—either remotely or in-person—then immediately withdrawing whatever portion of the funds is immediately available.
  • Remotely depositing the same check multiple times—using the mobile apps for accounts they hold at various banks and credit unions. They may even make a final, physical duplicate deposit at an ATM or with a teller. With this scheme, fraudsters can literally “cash in” on the funds from a single check multiple times.
  • Purposely overpaying an individual or business for goods or services with a bad check—then asking the victim to refund the “excess” amount they paid. Once the scammer receives the refund, they quickly deposit the payment and cash out the funds.

In each of these deposit fraud scenarios, the speed of theft is a key factor in the fraudster’s success.

Faster banking opens the door to faster fraud.

FIs face two key challenges in the fight against deposit fraud. The first, is that to meet customer expectations for swift and seamless banking transactions, FIs must make at least a portion of the deposited funds immediately available. But in so doing, they provide a window of opportunity for criminals. That’s where the second challenge comes in.

There’s a lack of real-time communication between receiving and issuing FIs—and fraudsters exploit this gap. By the time the deposited check is processed and the fraud is detected, the criminal is long gone—along with the stolen funds.

To effectively combat deposit fraud without compromising the customer experience, banks and credit unions need to be able to make informed, real-time decisions about whether to accept a deposit—and how much of the funds to make immediately available.

Big data and predictive analytics make a powerful combo.

Big data and predictive analytics are proving effective in the fight against bank deposit fraud. By sharing data across institutions and processing that data with real-time analytics—backed by machine learning models—FIs can see across an individual’s current and past account behavior to accurately predict risk and detect potentially fraudulent transactions. Four key insights FIs can use to detect deposit fraud include:

  1. Determining if the person is authorized to transact on the account
  2. Confirming the payer’s account exists and is in good standing
  3. Flagging potential duplicate items in real-time
  4. Predicting the likelihood that a check will be returned

By using real-time data intelligence, FIs can protect against deposit fraud losses—while continuing to deliver fast and easy banking experiences across channels. Deposit Chek® from Early Warning, for example, draws on data contributed by thousands of banks and credit unions—and analyzes millions of daily transactions—to alert FIs to possible counterfeit and duplicate items. And its real-time deposit screening capability lets FIs avoid unnecessary holds on deposited funds. In 2022, Early Warning alerted FIs to $10.2 billion in high-risk checks.

Financial institutions of all sizes—from local credit unions to national banks—can capture the benefits of big data and predictive intelligence to reduce fraud losses. To explore tangible strategies you can use at your institution, read our white paper, Fraudsters love your omni-channel approach: 3 ways banks can stop deposit fraud with predictive intelligence.

Sources

  1. Aite-Novarica Report, What’s Top of Mind for Fraud Executives TRENDS, SCAMS, AND TALENT, August 2022