June 14, 2023 – AI usage has taken off in the insurance industry, as compute and data storage resources have gotten cheaper over time. Carriers using AI must adhere to basic principles in the solution architecture to ensure nondiscriminatory and fair outcomes. Moreover, carriers must be able to demonstrate the fairness and transparency of their AI processes to various regulators—a challenge, given that many algorithms are designed to be somewhat opaque.

This report discusses how CIOs and CTOs can ensure that the AI programs they use are explainable and transparent, keeping them in line with regulatory requirements. Aite-Novarica Group reviewed its research, conversations with carriers and vendors, and external articles to develop the checklist for explaining AI and ML algorithms to regulators.
Clients of Aite-Novarica Group’s Life, Annuities, & Benefits or Property & Casualty service can download this report and the corresponding charts.
This report mentions Arize, Cloud Object Storage, Dask, DVC, Grafana, Kubeflow, MLflow, Nvidia, PyTorch, Scale, Snowflake, Spark, Spell, Suberb.ai, Tecton, TensorFlow, and UbiOps.
About the Author
Jack Krantz
Jack Krantz is an Advisor at Datos Insights. His expertise includes applications of numerical modeling, machine learning, and artificial intelligence as well as earth and atmospheric sciences. In his five years with Datos, he has been involved in delivery of numerous consulting projects including vendor selections, IT strategies, data strategies, competitive benchmarking, and project assurance engagements. Jack additionally serves as...