# LexisNexis AI tool slashes fraud false positives by 80% - FinTech Global

*Источник: FinTech Global*
*Дата: 2026-09-28*
*Язык: en*

**Кратко:** LexisNexis Risk Solutions, the risk intelligence provider behind the Emailage brand, has introduced Emailage Adaptive, an AI-driven risk scoring tool that recalibrates itself automatically. The company says it detects more genuine fraud while sharply cutting the number of legitimate, low-risk transactions wrongly flagged as suspicious.

LexisNexis Risk Solutions, the risk intelligence provider behind the Emailage brand, has introduced Emailage Adaptive, an AI-driven risk scoring tool that recalibrates itself automatically.
The company says it detects more genuine fraud while sharply cutting the number of legitimate, low-risk transactions wrongly flagged as suspicious.
The system runs entirely on AI models and draws on signals including email, IP address, phone number and physical address. During testing, it identified roughly 90% of fraud cases within the riskiest band of transactions and lowered false positives by more than 80%.
It learns continuously from the transaction records, fraud trends and sector context specific to each client. Using that input, it builds successive fraud prevention models tailored to the organisation, which update without human involvement to produce sharper risk scores and stronger predictive performance. The tool is intended for use across multiple industries and high-exposure activities, including opening new accounts, managing existing ones and processing payments.
Email data sits at the centre of the approach. Consumers hold 7.9bn email accounts worldwide, and a third of people retain the same address for over a decade. The company argues that examining the history and usage patterns of these accounts can yield distinctive insight when combined with wider risk intelligence.
Dell Technologies offers an early proof point. Since adopting Emailage Adaptive to inform its risk decisions, the technology group has doubled its capture rate for high-risk fraud and reduced manual checks on low-risk transactions by 83%.
The product arrives as fraud losses climb. Research from the LexisNexis Risk Solutions Cybercrime Report 2026 found that one in every 11 attempts to create a new account worldwide is fraudulent.
LexisNexis Risk Solutions says explainability underpins the platform’s design. Its models depend on a steady supply of client transaction data, sector trends and newly identified fraud behaviour to power an ongoing cycle of improvement. This input lets the models sharpen over time and produce risk scores that come with clear reason codes.
Those codes show whether each individual factor pushed a score up or down. The tailored models combine global transaction data with verified customer feedback and adjust once new patterns are confirmed. The company also states that its responsible AI approach supports transparency, helps reduce bias and helps safeguard data privacy by relying on trustworthy data sources.
Dell Technologies director of business operations Jeremy Cole said, “The self-calibrating AI model has helped us modernise fraud prevention by minimising reliance on static rules and manual policy adjustments. Our fraud team can now calibrate less, act faster and approve more legitimate transactions with confidence.”
LexisNexis Risk Solutions global head of fraud and identity Kimberly Sutherland said, “As generative AI scales, fraud attacks are now happening at a faster rate than most manual prevention strategies can keep pace with, overwhelming systems and exposing businesses to ever greater risk.
“By continuously learning from fraud outcomes, backed by cross industry risk intelligence, a self-calibrating fraud model can adjust instantly to subtle changes in fraud patterns, removing the lag between when patterns emerge and when defences calibrate. This allows fraud teams to continually enhance predictive accuracy while reducing manual workload.
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