Insurance
AI STRATEGY
Insurance
R & D teams use AI to identify patterns in user data , customise pricing models , and understand customer behavior . As BusinessWire reports , satellite and aerial imagery can help analyse property data . An example : Arturo , a company that helps insurance companies with predictive analytics , uses deep learning models to provide unique property data in as little as five seconds . In another use case , NLP analyses financial statements and investor presentations . Both help insurance companies understand what their clients will pay for — and what they ’ ll pay back .
‘ The remaining 20 % is made up of one-off questions that only experienced teams can answer ’. What he ’ s hinting at is an integration of the broad insights offered by AI and the specialised knowledge of R & D experts .
While the benefits of a R & D future built on AI include a faster time to market , more customised components , and optimised labour , there are those who fear its blind spots — bias , overconfidence , occasional error . Indeed , several organisations have turned to regression testing to ensure that AI software is constrained in scope and unable to make decisions on its own . Is this right ? It may provide oversight , but it remains reminiscent of Vonnegut ’ s Harrison Bergeron : handicapped by the government to impede his intellectual capabilities .
Fundamentally , the question is this : AI can do the analytical work of R & D — but who should make the final call ?
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