Why Your IT Rollout Is Failing After Launch, Not Before It
September 22, 2026
In today’s digital-first economy, identity is currency. From opening bank accounts to accessing healthcare systems and enterprise platforms, identity verification sits at the center of trust. But what happens when identities themselves are fabricated?
Enter synthetic identities – a rapidly growing threat that blends real and fake information to create entirely new, fraudulent personas. This, paired with the rise of synthetic data and AI-driven automation, means that cybercriminals are scaling identity fraud in ways that are harder to detect, harder to trace, and more costly than ever before.
In this blog we will dive into how synthetic accounts are created, why they’re so effective, and what organizations can do to defend against this evolving threat.
Unlike traditional identity theft, where a criminal steals a real person’s information, synthetic identity fraud involves creating a brand-new identity using a mix of legitimate and fabricated data.
A synthetic identity might include:
These elements are combined to create a “person” who doesn’t actually exist—but appears legitimate enough to pass basic verification checks.
Once a synthetic identity is created, cybercriminals use it to open accounts across financial institutions, e-commerce platforms, SaaS applications, and even healthcare systems.
These synthetic accounts are often nurtured over time to build creditworthiness and transaction histories. The cybercriminals then use leverage them to bypass fraud detection systems over time.
Eventually, attackers “bust out”—maxing out credit lines or executing large fraudulent transactions before disappearing. This long-game approach makes synthetic fraud particularly damaging. Losses aren’t immediate—they accumulate over months or even years before detection.
The rise of artificial intelligence has dramatically lowered the barrier to entry for cybercriminals.
Firstly, AI models can generate everything a cybercriminal needs in order to create a realistic fake identity. This can be anything from realistic names and addresses to valid-looking ID numbers or even entire virtual profiles at scale.
Learn more about the dangers of AI in our blog: How AI Cybercrime is Entering a Dangerous New Era.
Additionally, fraudsters can now create realistic-looking profile photos, fake IDs and supporting documents and even deepfake videos to help them pass identity verification checks. The use of AI makes creating a fake persona much easier than it was 5-10 years ago.
Another tactic cybercriminals are using to create synthetic identities is taking leaked data from data breaches. Massive data breaches provide a treasure trove of real data that can be stitched into synthetic identities. Even partial data (like SSNs or email addresses) increases credibility.
Ironically, the same synthetic data that is used legitimately by organizations for testing and AI training, can also be exploited to simulate fraud scenarios and refine attack strategies. Hackers will test drive their synthetic identities at scale before unleashing them into the virtual world.
Traditional fraud detection systems are designed to flag anomalies tied to real individuals. Synthetic identities, however, don’t map cleanly to a single victim. Some of the key challenges include:
1. No Direct Victim: There’s often no individual reporting fraud, which delays detection.
2. Blended Data Signals: Because synthetic identities use real data fragments, they can pass credit checks, ID verification processes, and basic controls.
3. Behavioral Normalcy: Attackers carefully build account history over time, making activity appear legitimate.
4. Siloed Systems: Organizations often lack cross-platform visibility, making it difficult to detect patterns across accounts or institutions.
While financial services are the primary target, synthetic identity fraud is expanding rapidly across a number of sectors including financial services, healthcare, e-commerce and retail, and SaaS and technology providers.
Banks currently face the highest losses due to credit-based fraud and “bust-out” schemes. In healthcare, fraudulent identities can be used to access medical services, submit false insurance claims or obtain prescription drugs.
Similarly, in retail, SaaS, technology and e-commerce, synthetic accounts enable fraudulent account creation, purchases or chargebacks. These synthetic accounts can also abuse free trials, platform resources and act as footholds for larger scale attacks.
The financial and operational consequences of synthetic identity fraud are significant:
According to industry estimates, synthetic identity fraud is one of the fastest-growing types of financial crime, costing billions annually.
Combating synthetic identities requires a layered, intelligence-driven approach.
First, businesses need to move beyond static data checks. Things like biometric authentication, validating identities against trusted data sources and implementing document verification technologies can help strengthen your organization’s identity verification. This is the first step in preventing synthetic identity fraud.
Next, monitor how users interact with systems. If there is something suspicious about the typing patterns, login behaviour, or transaction habits, these could reveal a synthetic account. Behavioural anomalies are one of the ways to detect synthetic accounts, even when static data appears valid.
Similarly, organizations can use machine learning models trained to detect identity inconsistencies, unusual account linkages, and other patterns that are indicative of synthetic identity creation.
Another way to defend against synthetic identity fraud is to break down internal silos by integrating fraud detection across:
All organizations should be implementing continuous monitoring of their IT environments. Fraud doesn’t stop after onboarding. Continuously assess accounts throughout the customer lifecycle to identify suspicious activity.
Lastly, partner with a security provider. Solutions from vendors specializing in identity verification, fraud prevention, and threat intelligence can significantly enhance detection capabilities.
Synthetic accounts represent a fundamental shift in cybercrime: cybercriminals have gone from stealing identities to manufacturing them. As attackers become more sophisticated, organizations must rethink how they establish and maintain trust in digital environments.
The fight against synthetic identity fraud isn’t just about better tools—it’s about better strategies, deeper visibility, and a proactive approach to identity security.
