Synthetic identities remain one of the fastest-growing types of fraud, and their monetary damages are dangerous for business. Synthetic identity fraud occurs where an individual creates new identities by combining real and fake information. The intent is to use this non-existent entity to acquire credit lines and make purchases without repaying what they borrow. However, while synthetic fraud does present a serious issue that businesses can’t ignore, companies should not focus all of their efforts in one place. In a recent webinar, Fraudonomics: Why It Makes Sense to Look Beyond Synthetic Fraud, Datavisor’s Fang Yu discusses the need to take a comprehensive approach to fraud detection and prevention, and why doing so addresses the risks of synthetic fraud and many others. The Implications of Synthetic Fraud for FIs Personal information used to be a commodity of the dark web. But Yu noted that with the rise of social sharing, people are willingly (albeit often unknowingly) sharing details that make it easier and cheaper for fraudsters to create fake identities. This process takes time. Fraudsters initially work toward creating several identities (we’ve seen tens of thousands of synthetic IDs in a batch) and building trust with creditors. Many fraudsters will target low lines of credit or options with minimal credit requirements to build up their history. For the first 1-3 years, there is no damage to FIs. And then suddenly, FIs are blindsided by multiple credit requests and charges in a short timeframe. The more identities a fraudster has used, the greater the losses for the FI. Our research shows the average loss per synthetic identity attack totals $10,000. Multiplied by 500 synthetic identities, FIs are looking at losses in excess of $5M. How to Fight Fraud and Preserve the Customer Experience Financial customers today have high expectations of the companies with which they do business. They want low friction environments without sacrificing privacy or safety. This balance can be hard to achieve because fraud liability increases with low friction and decreases with enhanced security. According to Revolut’s Head of Fraud Mike Valdepenas, it all comes down to the use of models, which are effective and efficient at fraud detection. The benefit to this is that FIs can choose smaller slivers of the population to experience different forms of authentication and ensure they are interacting with legitimate people. “This helps to create less friction because fewer users need to provide additional documentation,” says Valdepenas. “Having an effective and efficient model is critical to being in a place where you can satisfy both high security for the FI and a low friction user experience.” Comprehensive fraud prevention can help FIs avoid falling victim to synthetic identities because they can look at a variety of data points simultaneously. “Confirming things like a person’s name, address, and other key details give FIs a broader and more complete picture of each customer so better decisions can be made.” Watch the webinar Fraudonomics: Why It Makes Sense to Look Beyond Synthetic Fraud for the full story. View posts by tags: Related Content: Quick Takes Infamous Fraud Cases and Their Implications for Modern Fraud Experts Quick Takes What Is Expense Fraud and How Can You Detect It? Quick Takes Does There Have to Be a Tradeoff Between Fraud Prevention and CX? about Parinitha Marnekar about Parinitha Marnekar View posts by tags: Related Content: Quick Takes Infamous Fraud Cases and Their Implications for Modern Fraud Experts Quick Takes What Is Expense Fraud and How Can You Detect It? Quick Takes Does There Have to Be a Tradeoff Between Fraud Prevention and CX?