FRISS is 100% focused on automated fraud and risk detection for P&C insurance companies worldwide. Their AI-powered detection solutions for underwriting, claims and SIU help 175+ insurers grow their business.

FRISS detects fraud, mitigates risks and supports digital transformation. Insurers go live within 4 months, realize up to 10 times ROI and 80% increase in straight through processing of policy application and claims. FRISS solutions help lower loss ratios, enable profitable portfolio growth, and improve the customer experience.

  • Prevent criminal and fraudulent customers from entering your client base.
  • Detect insurance fraud before claims are paid out.
  • Payout genuine claims three times faster and onboard new customers in a split second to improve the customer experience.

175

implementations worldwide

130

million screenings per year

1

billion $ fraud savings per year

8

customer satisfaction rating

FRISS & Web-IQ partnership

Compliance screening / risk assessment

Receive relevant and actionable customer risk information within minutes into your system from sources such as darkweb, social media, news/media articles and millions of online pages.

  • On average 80% reduction of processing time to identify online risks
  • Improved onboarding screening prevented fraudulent/criminal customers from entering the customers database within the first month of implementation
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About FRISS

FRISS is an international and fast-growing group of talented people driven by passion, focus and dedication to fight insurance fraud. At FRISS, they feel comfortable being themselves and we have full confidence in their knowledge & expertise.

They don’t want people to pay higher premiums because others commit fraud. With AI technology and data, FRISS detects and prevents fraud. For FRISS, that is honest insurance. Demand for anti-fraud solutions has grown since FRISS was founded in 2006, and they now have over 175 implementations across 40+ countries, with offices in Chicago, Santiago, Paris, Cologne and Utrecht.

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