Synthetic identity fraud, in which criminals build fake identities using a mix of real and fabricated data, is emerging as a major driver of financial crime as generative artificial intelligence accelerates its scale and sophistication, according to a new report from Mitek and Datos Insights.
U.S. unsecured credit losses tied to synthetic identity fraud are projected to exceed $3.1 billion in 2026, up from $1.8 billion in 2020, according to the research, which describes the trend as a "defining strategic threat for financial institutions." The losses are largely driven by application fraud, in which synthetic identities are used to open credit cards, personal loans and other lending products not backed by collateral.
"AI-enabled tactics, organized criminal operations and scalable identity manipulation are changing the economics of fraud," Garrett Gafke, chief operating officer at fraud prevention firm Mitek, said in a Wednesday press release.
Synthetic identity fraud is growing at an annual rate of about 16%, driven by low-cost access to personal data and the industrialization of fraud operations, according to the study. It notes that application fraud is the primary channel through which synthetic identities generate losses, as they are used to gain entry into the financial system via credit cards, personal loans and deposit accounts.
More than 80% of financial sector fraud-prevention leaders surveyed in the study identified synthetic identity fraud as a high or moderate risk to application processes.
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