Face to Face with Fraud
There’s an interesting phenomenon happening every day, on almost every FI website looking to onboard new customers, whether it be a loan or line of credit application or an insurance quote. It’s taking place right in front of us, digitally, often going undetected and costing companies billions of dollars in losses and therefore costing customers billions in increased prices and increased regulation. I’m talking about fraud, but not just criminal fraud or 3rd party fraud, fraud in the sense that actual customers are “padding” their salary or assets in an attempt to reduce their risk profile.
It’s no secret, FIs encounter risk every day, face-to-face, in the form of synthetic identities, stolen financial credentials, bots, and cyber gangs using incredibly sophisticated software, AI and networks designed to get past fraud filters. However, as FIs struggle to stop these fraudsters, this may actually be the easier type of fraud to detect.
1st party fraud, or ‘intent fraud,’ is on the rise. This is when an actual person, no identity or financial information being compromised, attempts to make their credentials appear to be low-risk by misrepresenting their finances in order to pass through underwriting and get a loan.
Covid-19 has been a catalyst in the rise of 1st party fraud. With economies shutting down and credit bureaus lagging, this form of fraud risk is getting more and more difficult to determine. A recent article by Corporate Compliance Insight highlights this:
Dishonest acts by “long-trading” and “good” consumers are possibly being overlooked. Consumers who, through no fault of their own, have found their financial situation greatly impacted in the current climate – furlough schemes, redundancies and the self-employed being impacted by business closures – are placing more consumers in financial difficulty.
Determining the intent of an applicant using today’s technology can prove futile, which leaves FIs to use a tool that has many unintended consequences… friction. But friction is not a solution. It does drive away some fraud but at a huge cost to legitimate prospects abandoning the site in search of a better user experience.
The answer is in your data. The customer data that you use to drive current AI or machine learning risk models, the customer data that is used to retrieve credit bureau information and drive underwriting decisions. The truth is hidden in that data. Human behavior can be translated from that data, opening a new view into the intentions, potential fraud and profile of each customer, minus the friction.
Want to know how to interpret the behavioral analytics that resides inside your customer data and see and combat fraud in real time? Contact me.
