“Organizations have the best chance of identifying synthetics if they use a layered fraud mitigation approach that incorporates both manual and technological data analysis,” said Jim Cunha, secure payments strategy leader and senior vice president at the Federal Reserve Bank of Boston. “In addition, sharing information both internally and with others across the payments industry helps organizations learn about shifting fraud tactics.”

A synthetic identity is created by using a combination of real information (such as a legitimate Social Security number) and fictitious information (which can include a false name, address or date of birth). Synthetic identities can be used to establish accounts that behave like legitimate accounts and may not be flagged as suspicious using conventional fraud detection models. This affords perpetrators the time to cultivate these identities, build positive credit histories, and increase their borrowing or spending power before “busting out” - the process of maxing out a line of credit with no intention to repay.

The white paper examines factors that influence synthetic identity fraud mitigation, including:
• Technological advancements, such as artificial intelligence and machine learning
• Regulatory and environmental influences
• Information sharing and data integrity