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Synthetic Fraud Detection: An In-Depth Guide

Synthetic fraud detection is a method used by financial institutions to prevent fraudulent activities involving fictitious identities. It employs advanced algorithms and data analysis to identify anomalies in data and flag potential synthetic identities, helping to proactively prevent financial losses.

March 3, 2022

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Brianna Valleskey

Head of Marketing

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Synthetic identity fraud is a type of identity theft in which a criminal combines both real and fake personal information to create a new, fictitious identity that can then be used for various identity-related schemes, such as credit card fraud, bank fraud, and more. While the fraudster may use an individual's SSN, they add fake personal details, such as a fictitious name and address. This combination of identifying information often fails to show up on credit reports or other traditional detection tools used by consumers.

About the author

Brianna Valleskey is the Head of Marketing at Inscribe AI. A former journalist and longtime B2B marketing leader, Brianna is the creator and host of Good Question, where she brings together experts at the intersection of fraud, fintech, and AI. She’s passionate about making technical topics accessible and inspiring the next generation of risk leaders, and was named 2022 Experimental Marketer of the Year and one of the 2023 Top 50 Woman in Content. Prior to Inscribe, she served in marketing and leadership roles at Sendoso, Benzinga, and LevelEleven.