Issue #58 | 26 July 2024
Stay in the know on the stories shaping the future of insurance, with the weekly lowdown brought to you by Genasys.
This week in The Lowdown: how the metaverse could transform the insurance industry; maximising UBI programs for faster car crash responses; and balancing innovation and risk in AI for insurance leaders.
How the metaverse could transform the insurance industry
The metaverse, an immersive and experimental virtual evolution of the internet, holds the potential to revolutionise the insurance industry, Milliman reports.
Insurers could provide personalised user experiences, advanced risk assessments, and immersive training, while also offering coverage for virtual assets and continuity products for businesses relying on the metaverse. Key processes like underwriting and claims management could be streamlined, and digital twins could enhance risk simulations and fraud detection.
Maximsing UBI programs for faster car crash reports
Usage-based insurance (UBI) programs, which have surged in popularity, offer a significant advantage for insurers: the ability to detect accidents instantly and dispatch emergency assistance, Insurance Thought Leadership reports.
Despite the projected growth of the UBI market from $30.6 billion in 2023 to $80.7 billion by 2028, many insurance carriers have yet to fully leverage this technology. By utilising real-time data on driving habits, insurers can implement crash response systems that expedite emergency support, reduce claims costs, and enhance customer satisfaction.
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Balancing innovation and risk in AI for insurance leaders
AI promises to transform the insurance industry, presenting both remarkable opportunities and significant risks, Insurance Edge reports.
As AI adoption grows, so do the associated challenges, making effective governance crucial. To harness the benefits of AI while mitigating its risks, insurers need to focus on several key areas. Addressing issues such as data availability, model maintenance, and AI bias is essential to avoid operational inefficiencies and legal complications. A transparent AI framework, clear accountability, and rigorous performance metrics are vital for managing these challenges.
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