Earlier this month, InsureTech Connect- "the largest annual insurtech event in the world" - was held at the MGM Grand in Las Vegas. This year the event attracted over 6,000 registrants and over 250 speakers; attendees represent all facets of the insurance industry, ranging from budding tech startups to large brokerage firms. The theme of the conference was the "transition from legacy technology" with the implementation of innovation in the insurance industry.
Dan Rice, Chief Technology Office and Co-Founder of Sagewise, offers his view on the conference in an op-ed:
Two technologies filled the cutting edge discussion: AI (artificial intelligence) and blockchain, but both were met with a level of caution and skepticism.
Speakers at the event agreed the future of AI has numerous benefits with potential for creating new and substantial efficiencies in the industry, but the looming regulatory barriers are foreseeable when using AI for insurance. CEO of the National Association of Insurance Commissioners (NAIC) presented one such issue:
"Big Data usage should not be a black box. Companies must be able to explain and have mastery of the models they want to use."
This requirement from regulators reveals a particular problem for the use of AI: "since neural nets, once trained, are generally not human readable or well understood." The General Data Protection Regulation (GDPR) from the European Union (EU) has created a "hamstring to the development of insurance AI" in limiting data sharing between enterprises so that innovation is constrained, causing the EU to lag behind other countries with less restrictive laws.
Rice found that the sessions on blockchain were as "tempered" as the AI with less maturity in the level of discussion:
"It could have easily been a blockchain 101 session. Examples shown were still in proof-of-concept prototype phase ... Absent from the conversation were metrics like how much efficiency an enterprise can hope to gain through implementation of the blockchain technology in their business, or any guidance on how heavily companies should be investing in it."
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