As the insurance industry continues to embrace insurtech, use of artificial intelligence will no longer be a novelty, but the norm. Insurers will have higher expectations for customized experiences and a higher degree of personalization.
Looking toward the next decade, insurers and brokers will have to consider how to use blockchain and artificial intelligence as a tool to transform the most important piece of all—user experience. They can do that in several ways:
Moving toward personalized insurance. Artificial intelligence makes it feasible for insurers to personalize coverages and rates. To do this they need AI and access to trustworthy, accurate data sources. Those sources, including sales databases, data from wearables and user preference data, offer companies much deeper insight and allow them to contextualize behaviors to make more rational decisions.
Studies show that nearly 80% of customers are happy to provide their insurers with additional data if it means they could benefit from a lower premium. Trials are being done on wearables data to help insurers accurately price individual travel, life and health insurance.
Enhancing customer experiences. The sheer volume of calls and transactions that insurers process daily is sparking movement toward AI. Chatbots and other AI-based insurtech applications are fielding more of these calls and communications. The industry is quickly moving toward customers self-managing claims. AI is providing more guidance to customers, and it has become increasingly difficult for them to differentiate between machine and human interaction.
As the industry evolves, big data and AI are combining to create new efficiencies that are transforming the customer experience. For insurance industry executives, a passing knowledge of AI isn’t enough.
It needs to be viewed as a cornerstone of company culture.
Investments to take insurers’ insurtech strategies to the next level are needed as part of their ongoing business strategy, or they’ll run the risk of lagging behind their more progressive competitors.
Data scrubbing and personalized sales. Insurers can’t serve customers well without correct individual information. It’s labor-intensive for humans to find and correct errors. With group plans, for instance, census data obtained during quoting is often incomplete. AI can analyze a census to make smart decisions regarding each insured’s missing and incorrect data. It also can boost sales by analyzing group attributes and providing customized options to maximize the attractiveness of the offer.
But AI can do more than just correct and input census data. A group insurance carrier may receive requests for proposals in many different formats, such as email text, Microsoft Word documents, and PDFs with text or embedded images. Recent advances in data extraction from unstructured digital sources include novel techniques, such as “deep biaffine attention for neural dependency parsing.” Dependency parsing is a technique for annotating sentences to make it easy for both humans and computers to understand, frequently used in algorithms for image captioning and language translation. Biaffine attention increases performance, resulting in a more reliable method for extracting quoting information from a PDF or an email. This new method improves straight-through processing and personalization in group and individual insurance. With the help of AI, the industry is finally moving from one-size-fits-all to a more personalized approach.
Check out the full article in AM Best’s Monthly Insurance Magazine.