Advancements in artificial intelligence, machine learning and advanced analytics, combined with exponentially increasing data sets, provide life and health insurers with transformative opportunities. If they leverage new data and technologies effectively, they can dramatically improve the value they deliver to shareholders and policyholders, as well as position themselves to gain competitive advantage in the future. 

Successful life and health insurers of the future will bridge the gap between data and the people that make decisions. AI-driven decision-making is fundamental to this. It enables predictive, fast and granular insights into policyholder behavior and portfolio value. Successful life and health insurers will operationalize AI-driven decision making, ensuring key decisions are always supported by data and evidence. Decision Science technology and skills will be at the forefront of this evolution. 

Adoption of AI-enabled decision making allows life and health insurers to increase value in three significant ways;

Improved customer lifetime value

Insurers can use AI to process large, complex and disparate data sets, pulling granular insights to better understand and serve policyholders. Product features and pricing can be targeted at the cohort or individual policyholder level. Furthermore, a better, predictive understanding of policyholder behavior can improve engagement and satisfaction.

Improved portfolio value

Insurers can leverage the wealth of internal and external data available to optimize financial value, particularly in the management of large in-force portfolios. AI techniques can deliver greater granularity and accuracy in claim assumption-setting and substantially reduce insurers’ capital reserve requirements. Using AI to inform decision making in domains like Distribution and Retention also enables insurers to optimize where and how limited investment is allocated. 

Lower operating costs

Life and health insurers are understandably cautious of the use of “black-box” AI. However, much of the short-term value the industry can derive from AI and ML techniques comes from efficiency. Using transparent AI to automate problem-solving and to complement day-to-day actuarial work is low-hanging fruit for executives under pressure to lower operating costs and boost efficiency.

Today, leading life and health insurers around the world are reviewing and reshaping their organizations to build successful, scalable, and sustainable operating models for the future. The industry faces a tipping point; forward looking insurers will implement AI-enabled decision making across their business operations, and will ultimately better serve their shareholders and policyholders. Insurers failing to capitalize on this opportunity will see the strength of their products relative to the market, as well as customer engagement and satisfaction levels, wane over time.