<?xml version="1.0" encoding="UTF-8"?><ns2:project xmlns:ns1="http://gtr.rcuk.ac.uk/gtr/api" xmlns:ns2="http://gtr.rcuk.ac.uk/gtr/api/project" xmlns:ns3="http://gtr.rcuk.ac.uk/gtr/api/fund" xmlns:ns4="http://gtr.rcuk.ac.uk/gtr/api/person" xmlns:ns5="http://gtr.rcuk.ac.uk/gtr/api/project/outcome" xmlns:ns6="http://gtr.rcuk.ac.uk/gtr/api/organisation" ns1:created="2026-06-03T15:52:43Z" ns1:href="http://gtr.ukri.org/gtr/api/projects/58845278-D395-4199-AE31-EC97EE222D2F" ns1:id="58845278-D395-4199-AE31-EC97EE222D2F"><ns1:links><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/persons/185D6E81-6274-49F7-A32E-CBFBD16B6DAA" ns1:rel="PM_PER"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/546C23B1-4831-4658-94E5-05683CCAD78F" ns1:rel="LEAD_ORG"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/546C23B1-4831-4658-94E5-05683CCAD78F" ns1:rel="PARTICIPANT_ORG"/><ns1:link ns1:end="2023-07-30T23:00:00Z" ns1:href="http://gtr.ukri.org/gtr/api/funds/6A561C09-96D0-4135-B81E-AA69997EEB65" ns1:rel="FUND" ns1:start="2023-04-30T23:00:00Z"/></ns1:links><ns2:identifiers><ns2:identifier ns2:type="RCUK">10067619</ns2:identifier></ns2:identifiers><ns2:title>AI Risk Management Platform for Insurance Industry</ns2:title><ns2:status>Closed</ns2:status><ns2:grantCategory>Collaborative R&amp;D</ns2:grantCategory><ns2:leadFunder>Innovate UK</ns2:leadFunder><ns2:abstractText>Holistic AI (HAI) will lead a consortium in the development of the first-to-market AI Risk Management Platform for insurance. The Platform has been co-conceived with our insurer and AI technology partners to enable insurers to evaluate AI risk and to price insurance; and to allow AI companies to manage and mitigate AI development and deployment risks via risk management tools and by accessing effective insurance. The consortium will help shape the rapidly emerging policy and regulatory landscape for trusted and responsible AI/ML.

The consortium brings together HAI's deep expertise in AI, data and software development and risk assurance knowhow; academic and policy expertise at UCL; and end user stakeholders including insurance providers.

The need for the HAI platform is driven by the rapid adoption of AI and ML across society. It is already widely used in sectors spanning finance and banking, automotive (autonomous vehicles), medicine and healthcare (robotic surgery, clinical trials, automated image diagnosis, etc.), and is increasingly being used in HR and legal decisions. With this growth and with increasingly complex use cases, there is increasing concern about the risks associated with AI, with legislation and regulations emerging rapidly across the globe, which are dramatically changing the landscape, and reflect (and place) risks upon companies utilising AI which they must protect against.

HAI will lead a consortium to meet global needs of insuring against AI, ML and algorithmic issues. These can be catastrophic - evidenced by KnIght Capital's $450m bankruptcy due to algorithmic trading system issues. Key challenges for the consortium are to define which risks should be prioritised and measured, and to create the tools to enable this.

HAI already provides a sophisticated suite of systems for AI audit and assurance, which break down algorithmic processes across multiple verticals, while considering use cases and user/operator risk and oversight. HAI currently works with enterprise companies like Unilever, evaluating their multiple AI projects for bias and failure, ready for multinational application in the emerging regulatory landscape.

The new Risk Management Platform will focus on specific insurance Industry requirements, evaluating and quantifying potential risk within/from AI, ML and algorithmic applications. Leveraging our existing assessment capabilities with wider requirements it creates a pricing and assessment structure enabling the insurance of algorithms.

This creates a distinct offering providing the first tools suitable for Insurer AI assessment, positioning the UK at the centre of a multi-billion dollar market</ns2:abstractText></ns2:project>