AI
AI continues to dominate the C-suite agenda , and the insurtech sector remains a prime candidate leading this transformation . This technology is reshaping critical aspects of insurance operations , especially in claims management and customer experience .
According to the Goldman Sachs Asset Management Global Insurance Survey 2024 , 73 % of insurers are using or exploring AI to reduce operational costs . Further , 39 % of insurers are using or considering AI for underwriting , with 20 % leveraging AI for investment evaluation . Recent data from McKinsey suggests that AI could potentially deliver up to US $ 1.1tn in additional value to the insurance sector annually by 2030 , while a PwC survey found that 68 % of insurance companies use or plan to implement AI in their operations .
Alan O ’ Loughlin , AVP Data Science , International , LexisNexis Risk Solutions , says : “ AI and machine learning ( ML )
“ AI and machine learning technologies empower rapid , data-driven decision-making ”
ALAN O ’ LOUGHLIN AVP DATA SCIENCE , LEXISNEXIS RISK SOLUTIONS technologies empower rapid , datadriven decision-making that means customers should enjoy faster , fairer and more accurate quotes and a more personalised service at insurance claim .”
He continues : “ Data normalisation through AI and ML techniques is creating standardisation and consistency for usage-based insurance based on this data .”
Insurers are now able to harness vast amounts of structured and unstructured data from various sources , including telematics devices , wearables and social media platforms . This wealth of information allows for more accurate risk assessment and pricing models .
The transformation is by no means cosmetic ; it ’ s changing how insurers interact with policyholders . At the heart of this change lies the exponential growth in data availability and processing capabilities .
Daniel Cole , Senior Managing Director , Financial Services & Insurance Practice at Publicis Sapient adds : “ AI revolutionises risk assessment and underwriting in insurance by analysing vast data sets from diverse sources like social media and financial records . It improves accuracy through machine learning algorithms , automates routine tasks and enables personalised underwriting models .”
He continues : “ Real-time decisionmaking and continuous learning further enhance efficiency and customer satisfaction . Additionally , AI strengthens fraud detection , ensuring integrity across insurance portfolios .”
86 November 2024