Synthetic Identity Fraud: How to Detect It Before It Does Damage

Synthetic identity fraud is one of the fastest-growing financial crimes across Europe. Unlike traditional fraud, it uses a blend of real and fake information to create new, believable identities. These identities can pass through onboarding checks undetected, often for months or even years. 

Zoot helps banks, lenders, and financial institutions across Europe detect and stop synthetic fraud early using advanced fraud detection and prevention tools that are fast, configurable, and compliant.

Synthetic identity fraud occurs when fraudsters create new identities using a mix of valid and false information. For example, they might combine a real national ID number with a fabricated name, address, and date of birth. These identities are then used to: 

• Apply for credit 

• Open accounts 

• Build up a positive transaction history  

• Commit fraud when credit limits increase or trust is established  

These cases are hard to spot because the identities often appear legitimate in isolation. Traditional tools can miss them entirely unless your systems are designed to detect subtle inconsistencies and behavioural red flags. 

Synthetic identities are designed to blend in. They don’t trigger obvious red flags like stolen credentials or mismatched KYC data. Instead, they exploit gaps in:

Onboarding processes that rely on static checks  

• Credit systems that validate based on limited inputs 

• Fraud systems without adaptive risk scoring or behavioural monitoring 

Without the right fraud detection software, many of these identities pass through screening unnoticed. 

For European banks and lenders, synthetic identity fraud isn’t just a financial risk. It’s a strategic vulnerability. The impact includes: 

• Charge-offs and write-downs once the fraud is executed 

• Increased compliance risk under GDPR and KYC/AML regulations 

• Operational strain on fraud teams chasing hard-to-prove cases 

• Lost customer trust if synthetic fraud compromises your systems 

The longer synthetic identities go undetected, the greater the financial and reputational cost. 

Early detection is critical. A strong fraud strategy includes multiple layers of defence. Here’s what matters most: 

Use a Fraud Rules Engine That Sees Beyond the Basics 

Zoot’s configurable fraud rules engine helps identify unusual patterns, suspicious linkages, and application anomalies. 

Automate Decisioning With Real-Time Data 

Apply consistent checks at speed using fraud prevention software that evaluates identity data, credit risk and behavioural factors together. 

Integrate Multiple Data Sources 

Cross-reference credit bureaus, identity databases, device fingerprints and behavioural biometrics to flag inconsistencies. 

Monitor Post-Onboarding Behaviour 

Synthetic fraud often builds credibility before striking. Ongoing behavioural monitoring helps detect when usage patterns shift. 

Here’s what you gain: 

• Faster identity checks using real-time data sources 

• Customisable fraud prevention workflows tailored to your business logic 

• No-code configuration to adapt quickly to new fraud tactics 

• Seamless integration with third-party identity and credit data providers 

• Full support for application fraud and credit fraud prevention 

With Zoot’s fraud detection software, you get the speed and control needed to act confidently and stay ahead of evolving threats. 

Synthetic identity fraud is hard to see but easy to stop with the right technology in place. Zoot helps you catch it early with intelligent, automated systems built for speed and scale. Get ahead with smarter fraud detection and prevention.