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Fraud

Synthetic Identity

A synthetic identity is a fictitious identity created by combining real personal information (often stolen) with fabricated data. Unlike traditional identity theft, it does not correspond to any real person, making it particularly difficult to detect.

Synthetic identity fraud is considered the fastest-growing form of financial fraud. The fraudster creates an identity by assembling disparate elements: a real national insurance number (often belonging to a child, deceased person, or recent immigrant), combined with a fictitious name, date of birth, and address. This hybrid identity is then used to build a legitimate credit history before committing massive fraud.

The typical process spans several months or even years. The fraudster begins with modest credit applications that are declined but create a file with credit bureaux. They then obtain small credit lines that they repay punctually to build a good score. When the profile is sufficiently established, they maximise all credit lines and disappear (the 'bust-out' technique).

Detecting synthetic identities requires advanced approaches: consistency analysis between different identity attributes, cross-referencing with official databases, detection of suspicious behavioural patterns, and analysis of the relationship graph between identities. Artificial intelligence and machine learning are essential for identifying the subtle anomalies that characterise these fabricated identities.

Regulations

AMLD6GDPR

Real-world examples

  • 1.A fraudster uses a minor child's national insurance number combined with a fictitious name and address to create a credit profile. After two years of exemplary behaviour, they take out 50,000 in loans they will never repay.
  • 2.A criminal network creates dozens of synthetic identities using national insurance numbers of recently deceased persons, opening bank accounts and taking out insurance policies on a large scale.
  • 3.A finance company detects a synthetic identity during a car leasing application through cross-analysis: the declared address has no energy consumption history, and the national insurance number is associated with an inconsistent date of birth.

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