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 a B2B marketing leader and Head of Marketing at Inscribe, where she leads the company's full marketing function and go-to-market strategy. She oversees brand, product marketing, demand generation, ABM, content, SEO/AEO, events, partnerships, and marketing operations, with responsibility for marketing pipeline and SQO targets. A former journalist and longtime storyteller, Brianna specializes in translating complex AI, fraud, identity, and fintech topics into clear narratives for enterprise audiences. She is the creator and host of Good Question, Inscribe's podcast on AI and fraud risk, and leads Inscribe's annual State of Document Fraud report.

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Synthetic Fraud Detection: An In-Depth Guide

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Brianna Valleskey

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