Fraud is on the rise in our increasingly complex financial system. When bad actors are able to steal from banks and lenders, everyone loses: from the banks themselves to lawful consumers who pay more for financial services as a result.
Using the latest advances in data, AI and machine learning, a number of tools have emerged in recent years to verify identity online and prevent stolen identity—or “third party”—fraud. These tools help financial institutions confirm that a user or applicant is who they say they are, and catch bad actors trying to impersonate legitimate customers.
But another type of fraud—one that’s significantly harder to detect—continues to bedevil the financial services industry. First-party fraud refers to instances where an individual applies for a loan in their own name, but never actually intends to pay it back. Sometimes consumers engage in first-party fraud as a “hack” to save money—a worrisome trend that’s grown with the rise of Buy Now, Pay Later (BNPL) loans. (In one recent study, 52% of Gen Z respondents admitted to committing that type of first-party fraud.) Other times, organized crime rings perpetrate first-party fraud by tricking or coercing legitimate consumers into using their own information to further criminal schemes.
Institutions differ in treating this type of risk as fraud versus credit. But however it’s categorized, it hits the bottom line: first-party fraud costs U.S. financial institutions and merchants more than $100 billion per year, according to research released last fall. Studies by FICO have found that first-party fraud can occur at three times the rate of identity theft, with 10 times greater losses.
Because first-party fraud involves a legitimate consumer that is not lying about their identity, it can be far harder to detect. Typical processes like verifying a consumer's address, phone number, and Social Security number are not effective in catching first-party fraudsters. By the time many lenders identify first-party fraud, it's already too late—the loan is out the door and the damage has been done. Banks and other lenders need new, innovative approaches to keep up with this insidious and increasingly prevalent form of fraud.
That’s why our team at Prism Data is excited to announce a first-of-its-kind tool to help financial providers identify and stop first-party fraud. We call it CashScore® FirstDetect™.
FirstDetect is a groundbreaking first-party fraud risk score, powered by open banking data, that predicts the likelihood that a consumer will default on a loan right away. The use of open banking is novel and key to the solution; this exciting new source of information includes thousands of data points missing from traditional credit files. This includes up-to-date financial details, like a consumer’s current income and assets, as well as nuanced patterns and trends that illustrate their earning, spending, and saving behavior over time.
Fraudsters don’t act like ordinary consumers. In analyzing millions of consumer deposit account records, and many instances of first-party fraud, we’ve learned to discern subtle patterns indicative of this unique risk. Our platform identifies sudden changes in income and expenses, predicts balance activity and future availability of funds, tracks BNPL usage (and abuse) that is not reported to the credit bureaus, and much more. We apply these learnings to make highly accurate predictions about how likely a loan applicant is to perpetrate first-party fraud.
FirstDetect enables lenders to significantly reduce risk and losses for products like credit cards and short-term personal loans, and is particularly useful for one-time transactions like BNPL loans. This new score is available to all Prism Data clients, adding to our market-leading suite of cash flow underwriting products. It can be used as a standalone score, in tandem with Prism’s flagship CashScore, or as a complement to existing first-party fraud defenses.
With FirstDetect, lenders can sidestep first-party fraud before it happens. It’s a powerful new tool for reducing risk, arriving at a time when Fed data shows delinquencies are rising across virtually every form of consumer debt, and when the rapid accumulation of BNPL “phantom debt” has resulted in warnings from regulators and banks about significant risks for retail lenders and to the larger U.S. financial system. New regulatory requirements on the horizon in states like New York may even require BNPL lenders to conduct further analysis into their borrowers’ ability-to-repay.
At Prism Data, we’ve pioneered the use of open banking data for automated cash flow underwriting. As the CFPB moves closer to finalizing its proposed rules on open banking announced last fall, this data will be more readily available than ever. FirstDetect represents yet another innovative use-case for open banking that’s a win-win for consumers and for financial providers.
Prism Data is the modern cash flow underwriting engine, providing the infrastructure and analytical tools necessary to utilize open banking data to its fullest potential—expanding access to credit, reducing credit and fraud risk, improving decision-making, and powering whole new product opportunities. With nearly a decade of experience and having powered billions of dollars in real-world originations, the Prism platform provides maturity, reliability, compliance, and predictive-power unrivaled in the market today. If you’re interested in learning more, we’d be excited to hear from you.
