Synthetic identity fraud, in which fraudsters combine real and fake data to create seemingly legitimate accounts, could be one of the most pervasive and damaging fraud risks facing fintechs, banks, and digital platforms across Africa in 2026.

 
For decades, document forgery was the main type of identity fraud, and enhanced verification tools were built to detect it quickly and stop fraud at onboarding. Over time, however, fraudsters have become more sophisticated, shifting to synthetic identities and AI-assisted techniques that bypass traditional checks. As a result, fraud often goes undetected for longer periods, allowing accounts to build trust before losses surface.

In 2024, fintechs and digital banks across Africa saw a sharp rise in synthetic identity fraud: South Africa reported a 481% increase, while Nigeria recorded a 192% jump. In several markets, synthetic identities now account for over 2% of total verification scam attempts, and the trend continues to accelerate.

For founders, fraud managers, and compliance leads, this shift makes understanding how synthetic identities operate no longer optional but critical to protecting revenue and users. 

This article guides you through synthetic fraud in 2026, practical indicators to spot it early, and strategies to prevent it from affecting your fintech or digital bank.

Why Synthetic Identity Fraud Is Hard to Detect

Synthetic identity fraud usually blends real data with fabricated details to create identities that appear legitimate on the surface. Because parts of the identity are real, accounts often pass initial checks, making the fraud harder to detect.

In many cases, an account clears onboarding because some of the information is valid: a real BVN, a real name, or a real date of birth. The fabricated elements are usually subtle, such as a different phone number, a new email address, or slightly altered personal details. On paper, everything looks consistent enough to pass basic KYC.  In reality, the individual controlling the account is not the true identity holder.

Bolaji Jimoh, Fraud Manager at Dojah, explains that this tactic is increasingly used to carry out Buy Now, Pay Later (BNPL) fraud, particularly among smaller fintechs across Africa. Fraudsters take advantage of lighter credit checks and short repayment windows, knowing losses may not surface immediately. 

To illustrate this, Bolaji shared a real-world example of synthetic identity fraud. In one attempted loan application, his email address was used, paired with a fabricated phone number, and identity details. The application looked legitimate enough to proceed, but if approved, repayment attempts would have gone to someone who never applied for the loan.

Synthetic vs Document Identity Fraud: Key Differences

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Common Red Flags of Synthetic Identity Fraud

Synthetic identity fraud may be hard to detect, but there are early warning signs that can reveal suspicious accounts before they cause significant losses. Four methods to spot synthetic identities on your platform early include:

1. Unusual behavior patterns

Look out for activity that doesn’t match typical user behavior. For example, a newly onboarded account suddenly making multiple high-value transactions in a short period could indicate a synthetic identity. Using behavioral monitoring tools to track login times, transaction frequency, and spending habits can reveal these subtle red flags early.

2. Device and IP inconsistencies

Pay attention to accounts that frequently switch devices or log in from multiple locations. For instance, if a single account accesses your platform from Lagos one hour and Nairobi the next, it might be a fraudster masking their identity. Device fingerprinting and IP monitoring help flag these inconsistencies before they escalate.

3. Cross-database mismatches

Verify your users’ information across multiple trusted sources, not just one. If an account claims a BVN or national ID that appears valid but doesn’t match banking, telecom, or government records, that’s a warning sign. Regular cross-checks catch these discrepancies before they become costly.

4. Account layering and linked contact patterns

Watch for multiple accounts using similar email domains, phone numbers, or other linked details. For example, if you see accounts with emails like olajumoh1@email.com, olajumoh2@email.com, and olajumoh3@email.com, it could indicate coordinated synthetic activity. Mapping these connections helps detect layered accounts early and prevents fraud from spreading across your platform.

Related: Learn more about the emerging fraud trends businesses will face in 2026

Preventing Synthetic Identity Fraud: Practical Measures for Fintechs in Africa

Spotting red flags is important, but prevention before fraudsters exploit your system is even better. For fintechs and banks, stopping synthetic identity fraud before it affects your platform means taking proactive steps that combine transaction monitoring and ongoing risk management. 

Here are five practical ways to do it:

1. Transaction Monitoring

Don’t rely on onboarding checks alone; monitor ongoing transactions continuously. For example, if a newly registered account suddenly makes multiple high-value payments, it should trigger a review. Tools like Dojah’s EasyDetect and Profiled Risk can help you track unusual activity in real time and flag accounts for further verification immediately.

2. Multi-step Verification Beyond Basic KYC

You can also combine identity checks with device and behavioral monitoring. Verify users across multiple signals, such as face match, phone, and email patterns, while tracking their behavior post-onboarding. This layered approach makes it much harder for fraudsters to slip through using partially fake information.

3. Cross-Database and AML Watchlist Checks

Go beyond single-source verification. Regularly cross-check BVNs, national IDs, phone numbers, and other user data against government databases and telecom records. You can also screen individuals against global sanction lists using AML watchlist platforms. This helps catch mismatched or recycled identities that are already high-risk before they can be exploited.

4. Device and Location Analysis

Continuously track user logins across devices and locations. If a single account accesses your platform from two countries within hours or shows inconsistent device usage, it could be an illegitimate attempt. Monitoring device and IP activity allows you to detect suspicious accounts early.

5. Regularly Updated Fraud Rules and Automated Alerts

Fraud patterns evolve fast, so your rules need to keep up. Continuously review risk scoring, update thresholds, and set automated alerts for unusual activity. That way, high-risk accounts are flagged immediately, letting your team intervene before losses occur.

Synthetic Identity Fraud Detection with Dojah

Synthetic identity fraud is no longer an emerging risk. It is an active and growing threat across African fintech ecosystems. As fraudsters blend real and fabricated data to bypass onboarding checks, platforms must adopt lifecycle-based fraud prevention strategies.

Dojah’s anti-fraud solutions help fintechs detect and prevent synthetic identities through multi-step verification, behavioral intelligence, device intelligence, and real-time risk profiling. By connecting these signals across onboarding and post-onboarding activity, your fraud team gains earlier detection and a faster investigation workflow.  

If you want to explore how Dojah can help safeguard your platform against synthetic identity fraud in 2026, speak with our team today.