Eitx
EITX is a UK-based insurtech firm specializing in machine learning models for insurance fraud detection, founded to address gaps in traditional fraud detection systems.
Profile
Builds custom machine-learning models to detect insurance fraud by mapping connections between policies, people, and incidents.
EITX is a UK-based insurtech firm specializing in machine learning models for insurance fraud detection, founded to address gaps in traditional fraud detection systems. The company builds bespoke probabilistic graph networks that connect entities like cars, policies, and individuals, weighting links by fraud probability. Unlike off-the-shelf SaaS solutions, EITX customizes models for each insurer's specific fraud patterns, focusing on motor incidents, bodily injury, and health/medical claims.
Their approach claims a 0% precision rate on flagged fraud rings and a median detection time of 11 days, recovering £147 million for clients between 2022 and 2025. The company operates with SOC 2 Type II compliance and supports UK, EU, and US data residency. EITX's recent model update (v4.2.1 as of May 2026) reflects ongoing tuning to emerging fraud tactics.
The firm distinguishes itself by offering explainable traces for every flagged ring, contrasting with opaque 'risk score' systems from incumbents. Their six-week deployment cycle includes quarterly re-tuning, a selling point against competitors' annual update cycles.
Who buys this
- Motor insurance providers combating staged collisions
- Health insurers targeting provider over-billing schemes
- Property insurers detecting liability fraud rings
- Special Investigation Units (SIUs) at large carriers
- Reinsurers analyzing cross-book fraud patterns
Strengths and what to watch
Strengths
- Custom models trained on client-specific fraud rings rather than generic datasets
- Probabilistic graph networks reveal non-obvious connections missed by rule-based systems
- Quarterly model re-tuning included at no additional cost, unlike competitors' fee-based updates
Watch for
- Dependence on client data exports for model accuracy may limit scalability
- No disclosed funding rounds or revenue figures despite claimed £147M client recoveries
- Potential regulatory scrutiny as explainable AI requirements tighten in EU/UK insurance markets
Key Information
- Founded
- 1974
- Headquarters
- London, Greater London. Read
Frequently Asked Questions
What is EITX and what do they do?
EITX is a UK insurtech firm building custom machine learning models to detect insurance fraud. Their systems map connections between policies, people, and incidents using probabilistic graph networks, focusing on motor, injury, and health claims with 0% false positives on flagged fraud rings.
How does EITX's fraud detection technology work?
EITX creates bespoke probabilistic graphs weighting links between entities like policies and claimants by fraud probability. Unlike rule-based systems, these models reveal non-obvious connections, updated quarterly to adapt to new fraud patterns while providing explainable traces for each detection.
What types of insurance fraud does EITX detect best?
Their models specialize in motor claim fraud (staged collisions), bodily injury schemes, and healthcare provider overbilling. The system identifies complex fraud rings by analyzing connections across policies, with reported £147M in client recoveries from 2022-2025.
How accurate is EITX's fraud detection system?
EITX claims 0% false positives on flagged fraud rings with median 11-day detection times. Models are retuned quarterly using client-specific data rather than generic datasets, contrasting with annual update cycles common among competitors.
Is EITX compliant with insurance industry regulations?
The company operates with SOC 2 Type II compliance and supports UK/EU/US data residency requirements. Their explainable AI approach aligns with tightening regulatory demands for transparency in fraud detection systems across insurance markets.
Who uses EITX's fraud detection solutions?
Primary clients include motor insurers, health providers, property carriers, and reinsurers. Special Investigation Units (SIUs) leverage their models to detect cross-policy fraud patterns, with customization for each insurer's specific fraud risks and claim types.
Sources
- www.eitx.co.uk — Core product details, client metrics, and operational approach
- www.linkedin.com — Indirect confirmation of B2B focus through employee background
- www.linkedin.com — Technical team expertise in data applications
- www.reuters.com — Context on UAE telecom market where parent company operates