Most respondents (75%) believe AI and ML can provide carriers with a competitive advantage.
Adopters say they are facing 4 key challenges around AI and ML… One is financial. The cost of implementation, uncertainty around ROI and competing priorities.
The second challenge: Staffing. The growing challenges of attracting and retaining data scientists when this skill set is in high demand across almost all data-driven industries.
The third challenge is with data. LexisNexis researchers say the challenges with data include the operational complexities of managing data volume, security and quality as carriers shift from single-source solutions to multi-source solutions.
Lastly, compliance challenges will be posed in 2020 in the face of increasing regulatory scrutiny and the challenges of discerning between new, legitimate data sources and sources that are actually proxies for sensitive or prohibited data.
The digital overhaul of the insurance industry that exploded in the last decade will only continue its momentum into 2020 and beyond. As the marketplace continues to become increasingly fast-paced and data-driven, carriers are making more and more investments into capabilities to help them compete, chief among them: artificial intelligence (AI) and machine learning (ML).
A new insurance research report from LexisNexis Risk Solutions sought to analyze the state of AI and ML in the insurance industry in 2020 by identifying carriers’ perceptions and the potential benefits and challenges impacting AI and ML adoption.
To do so, LexisNexis Risk Solutions researchers surveyed more than 300 insurance professionals across the top 100 U.S. carriers within the auto, home, life and commercial markets, working among varying insurance roles.
The slideshow above outlines 6 key findings from The State of Artificial Intelligence and Machine Learning in the Insurance Industry report, which include 4 identified challenges in using and adopting AI and ML.