In a recent statement made by the White House it was claimed that by 2020 it is highly likely that enhanced AI could replace jobs which command a salary of less than $20 per hour. The rapid evolution of AI over the past 5 years has come about as a general combination of technologies like processing power, data storage and analytics have converged to create the perfect storm of machine learning, cognitive computing and ‘robo-advisory’ neural networks. Already the results are obvious in our daily lives through the use of search engines and contextual prediction, but increasingly more complex use cases have gone mainstream into financial services areas like robo-advisors in the investment world. Unsurprisingly, the insurance industry is fast becoming an area of lucrative opportunity for those firms that are embracing what AI can do for their business.
The era of the robo-life agent has arrived and is now empowering insurance carriers with the ability to source and construct custom and personalized life insurance portfolios, monitor their policies in real-time, and develop pure digital products never conceived before. What is already undeniable is that robo-life agents can provide substantially more efficient and superior solutions to those traditionally done by humans, and are considerably more cost effective. Consequently the vast majority of life insurance agents today will, in time, become a memory of the past. Naturally there will be resistance to such a change, in the same way taxi drivers resist the Uberization model, but as AI competition begins to operate at optimal efficiency levels the advances in cognitive computing will act as a catalyst and make the evolution of the insurance industry a fait accompli.
Amongst the primary impact that AI’s will have on the industry of ‘risk’ will be around the areas of operations improvement and the automating of existing and repetitive front-end interactions, underwriting and claims processing. Common use cases for this will be in client engagement and improved lead conversion ratios, reducing quote-to-bind and FNOL-to-claim resolution times, and accelerating new digital product launches ahead of competitors. Over time however, artificial intelligence will likely have a more profound impact - it will recognize, evaluate, and underwrite incipient risks and detect new revenue streams. By its very nature, AI will rapidly increase in sophistication and will significantly improve cross-sell and up-sell prospects by converting them to customers, hone risk assessment and risk-based pricing, and elevate the service levels around claims adjustment. The unfortunate outcome of this is that many human roles are likely to become redundant over time - advisors, call center agents, claims representatives and underwriters are all at risk.