Modeling

Triple-I Blog | California Finalizes Updated Modeling Rules, Clarifies Applicability Beyond Wildfire – Go Health Pro

by
Triple-I Blog | California Finalizes Updated Modeling Rules, Clarifies Applicability Beyond Wildfire – Go Health Pro

California’s Department of Insurance last week posted long-awaited rules that remove obstacles to profitably underwriting coverage in the wildfire-prone state. Among other things, the new rules eliminate outdated restrictions on use of catastrophe models in setting premium rates. The measure also extends language related to catastrophe modeling to “nature-based flood risk reduction.” In the original … Read more

California Commissioner Announces Regulation to Enable the Use of Modeling in Rates – Go Health Pro

by
California Commissioner Announces Regulation to Enable the Use of Modeling in Rates – Go Health Pro

California Insurance Commissioner Ricardo Lara on Friday announced what he’s calling “first of its kind” catastrophe modeling and ratemaking regulation that will allow carriers to use the models as a factor in setting and getting rates. The regulation is a part of his so-called Sustainable Insurance Strategy to increase coverage in wildfire-distressed areas of the … Read more

Triple-I Blog | Actuarial Studies Advance Discussionon Bias, Modeling, and A.I. – Go Health Pro

by
Triple-I Blog | Actuarial Studies Advance Discussionon Bias, Modeling, and A.I. – Go Health Pro

The Casualty Actuarial Society (CAS) has added to its growing body of research to help actuaries detect and address potential bias in property/casualty insurance pricing with four new reports. The latest reports explore different aspects of unintentional bias and offer forward-looking solutions. The first  – “A Practical Guide to Navigating Fairness in Insurance Pricing” – … Read more

Evaluating the Effectiveness of Reward Modeling of Generative AI Programs – Go Well being Professional

by

Evaluating the Effectiveness of Reward Modeling of Generative AI Programs New analysis evaluating the effectiveness of reward modeling throughout Reinforcement Studying from Human Suggestions (RLHF): “SEAL: Systematic Error Evaluation for Worth ALignment.” The paper introduces quantitative metrics for evaluating the effectiveness of modeling and aligning human values: Summary: Reinforcement Studying from Human Suggestions (RLHF) goals … Read more

x