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How does synthetic identity fraud impact U.S. lenders according to the chapter?

Synthetic identity fraud significantly impacts U.S. lenders by costing them over $6 billion annually. This type of fraud involves creating fake identities using a mix of real and fabricated data, which makes detection very challenging and undermines traditional credit scoring models.

Synthetic identity fraud is a major challenge for U.S. lenders, resulting in losses exceeding $6 billion each year. This fraud involves the creation of fake identities by combining real and fabricated information, which makes it difficult for detection systems to identify. These synthetic identities can distort risk models by appearing as creditworthy borrowers before defaulting. This not only leads to direct financial losses but also undermines the reliability of traditional credit scoring models, forcing lenders to develop new verification methods to combat this sophisticated form of fraud.

Key points

  • Synthetic identity fraud costs U.S. lenders over $6 billion annually.
  • Fraud involves creating fake identities with real and fabricated data.
  • Detection is challenging, affecting credit market stability.
  • Synthetic identities appear creditworthy before defaulting, distorting risk models.
  • Traditional credit scoring models are undermined, requiring new verification approaches.
Source:AI and ML Governance in Financial Services· AI-Enabled Threat Actors and Systemic Risk· p. 60–67

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Cover of AI and ML Governance in Financial Services

AI and ML Governance in Financial Services

Richard Gwashy Young

Routledge, Taylor & Francis Group

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