Synthetic identity fraud: The risk is very real

Synthetic identity fraud has been on the rise for several years, resulting in billions of dollars in losses and damaging the trust of major organizations. This form of fraud is distinct from traditional identity theft, as it involves creating new identities by combining fabricated details with genuine personal information obtained through data breaches, malware, or social engineering.

Artificial intelligence (AI) has significantly amplified the speed and scale at which criminal syndicates can execute synthetic identity fraud.

AI enables the generation of more authentic-looking documents and deepfake images, making synthetic identities appear more believable. Because this type of fraud is harder to detect than traditional identity theft, it poses a significant and growing risk to financial institutions, retailers, fintech firms, telecommunications, and healthcare organizations, which are often slowed down by corporate compliance, committees, and budget considerations.

According to the Sumsub APAC Fraud in 2026 report, the number of fraud cases where the selfie doesn't match the ID document has surged by 73% year-on-year and now accounts for 35.4% of regional fraud. Synthetic identity fraud in the region has jumped 142% in a single year, with automated attacks increasing by 388% year-over-year.

The report suggests that fraudsters operate like a business process, involving multiple role players, stages, and laundering the proceeds through various channels. A US Federal Reserve report estimates that synthetic identity fraud losses reached $35 billion in 2023, a trend that is likely to continue in other regions, including Africa, where many organizations may already be victims.

To protect businesses against identity fraud and synthetic identity fraud, digital identity solutions are crucial. However, not all identity verification solutions are equal. Companies must utilize trusted, sovereign AI solutions that deliver proven performance in real-world environments. These solutions must be capable of identifying spoofing attempts and verifying identity using facial recognition, age estimation, liveness detection, as well as matching names and identity numbers to trusted national databases.

When investigating the implementation of a digital identity platform, businesses should prioritize the underlying technology, ensuring that it has undergone NIST certifications and the iBeta stamp of approval. iBeta conducts independent third-party biometric presentation attack detection (PAD) testing, which adheres to international standards such as ISO/IEC 30107-3.

These tests involve rigorous scrutiny against various spoofing techniques, including hyper-realistic facial masks and fingerprints, to ensure systems can accurately distinguish real identities from fakes. Only technology that passes such stringent testing can adequately protect against synthetic identity fraud syndicates.