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FRISS

Key facts

Cohort: Cohort 8, 2022 

Focus in insurance value chain/workflow: Point of underwriting I Claims 

Specific lines of business supported: Personal I Corporate I SME I Speciality 

Founded: 2006 

Status: Operating, still in insurance 

Company type: Data transformation, Data consolidator 

Head office: The Netherlands 

Main global offices: The Netherlands, USA, Germany, Australia 

Locations served: Europe, United Kingdom, USA, South America, Asia 

Employee count: 201-500 

Overview

FRISS focuses on providing “trust automation” solutions for property and casualty insurers. FRISS’s Trust Automation Platform combines text mining, machine learning, anomaly detection, predictive models, and network analysis to indicate fraud risks for policies or claims. This allows insurers to manage trust throughout the insurance value chain, from the first quote all the way to claims and investigations when needed. FRISS Underwriting Insights aggregates third-party data sources to provide underwriters with more information about businesses seeking quotes. 

Lab activity

Primary way aimed to improve insurance processes and tools whilst in the Accelerator: New sources of risk insight - data or models I Data, product & service consolidator I Enhancing back-end data efficiencies  

In the Accelerator, FRISS proved that it could classify US businesses using accurate and objective NAICS codes and provide deeper insight into complex risks for the Lloyd’s market. 

FRISS also developed a deeper understanding of what is required for a broader expansion outside the US, before deploying this after leaving the Lab and expanding its NAICS classification capability beyond the US. Within the Lab, FRISS also developed a new capability to profile insurers’ portfolios in context, helping them develop a growth strategy.  

"You never know the opportunities you might come across whilst working with your mentors."
Martyn Griffiths, Sales Manager UK

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Learn about all our alumni who have take part in the Lloyd’s Lab Accelerator programme.