2019 Study Results: How U.S. Insurance Carriers are Using Artificial Intelligence and Machine Learning. As the industry gears up to enter 2020 and the new decade, carriers are investing in the capabilities that will help them thrive in an increasingly fast-paced, data-driven marketplace. Chief among those capabilities? Artificial intelligence (AI) and machine learning (ML).
To better understand insurance carriers’ perceptions and the potential benefits and challenges impacting AI and ML adoption, LexisNexis Risk Solutions surveyed more than 300 insurance professionals across the top 100 U.S. carriers within the auto, home, life and commercial markets. Respondents work in data science, analytic, actuarial, technology, underwriting, product management and claims roles.
Highlights from the insurance research report include:
- The majority of the respondents (62%) work at carriers that are applying, piloting and planning AI and ML projects and are already seeing benefits from their investments.
- Most respondents (75%) believe AI and ML can provide carriers with a competitive advantage.
Adopters are facing four key challenges around AI and ML:
- Financial: the cost of implementation, uncertainty around ROI and competing priorities.
Staffing: the growing challenges of attracting and retaining data scientists when this skill set is in high demand across almost all data-driven industries.
- Data: especially the operational complexities of managing data volume, security and quality as carriers shift from single-source solutions to multi-source solutions.
- Compliance: increasing regulatory scrutiny and the challenges of discerning between new, legitimate data sources and sources that are actually proxies for sensitive or prohibited data.
Today, AI and ML capabilities can provide incremental lift. In the long run, carriers that can successfully operationalize AI and ML will be best positioned to achieve a definitive competitive advantage. The survey results can help carriers mitigate gaps in their capabilities—and shine a light on investments that can advance their AI and ML initiatives.