Solving Synthetics: Holistically Attacking a Diverse Threat
Synthetic identities are the fastest-growing and hardest-to-detect type of financial crime in the United States.
The known disparities in synthetic fraud behavior and lack of a universal tagging system for synthetic identities were key drivers for this final installment of ID:A Lab’s three-part research series on synthetic identities. In this study we compared the performance of a holistic synthetic solution, to traditional fraud and credit defenses and a symptom-focused synthetic solution at a leading U.S. card issuer. The results show capture rates per solution and the estimated savings of implementing a more comprehensive approach.
The research underscores the benefits of solutions designed to address a range of synthetic types and help enterprises tackle the issue based on how they experience it – as a fraud problem, a credit problem, or both. Download to learn more.