AI-driven digital identity verification and fraud prevention platform Socure has developed an innovative risk score to detect when users manipulate their identities and help address a $100 billion fraud problem.
Socure has introduced the Identity Manipulation Risk Score — the first predictive tool designed to stop repeat first-party fraudsters from taking advantage of the digital economy.
First-party fraud occurs when an individual intentionally misrepresents their identity or financial situation to gain financial benefits, such as loans, credit, or services, without intending to repay or fulfill obligations. Unlike third-party fraud, where someone else’s identity is stolen, first-party fraud is committed by the actual account holder and is often harder to detect. This type of fraud is costing businesses over $100 billion each year.
The tech company’s new tool is part of Sigma First-Party Fraud, Socure’s advanced fraud detection system. It analyzes dispute histories, payment denials, and account closures in real time using data from a vast network of industries, including banks, fintech companies, payment platforms, online merchants, and sports betting firms.
By tapping into this broad fraud intelligence network, Sigma First-Party Fraud helps businesses detect high-risk users at the time of account creation and continuously monitor them throughout their customer journey. This allows companies to identify and block fraudulent activity before it causes financial damage.
With the addition of a new functionality, this tool helps organizations measure the risk of identity manipulation at key moments, like account signups, high-risk transactions, and dispute resolutions. Fraudsters often use small changes — like different emails or phone numbers — to trick businesses while still using their real identity.
A recent survey by Socure found that nearly half (49%) of people who committed first-party fraud in 2024 did so because they got away with it in 2023. This shows that repeat fraud is a growing issue without a strong deterrent. At the same time, it means that the impact of the new prevention technique may be even stronger as blocking first-party fraudulent activity in the first place will very likely stop the repeat fraud instances as well.
With real-time data from over 210 million identities, 325 million accounts, and 20 billion transactions, Sigma First-Party Fraud gives fraud teams the ability to spot early warning signs, predict risky behavior, and stop repeat fraud before it grows. Since the tool uses AI and shared data from multiple industries, it offers a much more powerful way to predict and prevent fraud than traditional fraud detection methods. The ability to track fraudulent users across different companies is a major step toward protecting the financial system at a large scale. Besides, the service’s adaptive machine learning models continuously refine available fraud detection mechanisms, leveraging insights from billions of transactions to enhance accuracy and reduce false positives.
