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This study addresses a novel risk-sharing problem where an agent maximizes expected wealth under ambiguity, penalized by a chi-squared model ambiguity. The framework generalizes monotone mean-variance preferences and accommodates multiple reference models for applications like climate risk. Explicit solutions are derived for the insurer’s optimal risk-sharing strategy, decision measure, and wealth process, which depends linearly on auxiliary processes linked to Radon-Nikodym derivatives. The model penalization parameter affects wealth variance, and the optimal strategy considers the counterparty’s model and premium. Future work could explore Lévy-Itô processes, alternative divergences, or a Stackelberg game framework.

EIOPA's April 2025 Insurance Risk Dashboard indicates stable, medium-level risks in the European insurance sector, though pockets of vulnerability exist due to geopolitical uncertainty and market volatility. Macroeconomic risks are stable but with concerning GDP growth and inflation forecasts. Credit risks remained stable until early April, when spreads widened slightly. Market risks are elevated due to bond and equity volatility. Liquidity, solvency, profitability, financial interlinkages, and insurance risks are stable. Market sentiment is medium risk, and ESG risks are steady but with an intensifying outlook due to shifting environmental agreements.

This paper extends prior work to model an insurance company facing a future "tipping point" where catastrophe risks increase. Using viscosity solutions of a Hamilton-Jacobi-Bellman equation, the authors solve an optimal control problem to find the best dividend strategy. They show that, under fair premium adjustments and full observability, increased catastrophe risk may benefit shareholders. Numerical examples support these findings, and future research may explore relaxing model assumptions.

An agent with multiple loss models optimizes risk sharing with a counterparty using a mean-variance criterion adapted for ambiguity. Under a Cramér-Lundberg loss model, the optimal risk sharing contract and wealth process are characterized. The strategy is proven admissible, and the value function verified. The optimal strategy is applied to Spanish auto insurance data with differing models from cross-validation for numerical illustrations.

Insurance Europe supports simplifying the EU’s Taxonomy Regulation, advocating for reduced reporting burdens. It calls for suspending the insurance underwriting KPI, introducing a 10% materiality filter for the investment KPI, and simplifying reporting templates. The industry backs EU efforts to enhance sustainability while ensuring practical and effective regulatory measures.

EIOPA highlights the lack of consistent regulatory treatment for crypto assets in the (re)insurance sector, raising concerns about risk sensitivity. Current capital weight options may underestimate crypto risks. To ensure prudence, EIOPA proposes a uniform 100% capital requirement for all crypto holdings. This approach balances risk management with simplicity while acknowledging that future market growth may require revisions. A review of crypto treatment under Solvency II is recommended as the sector evolves.

The study examines Pareto optimal risk sharing in insurance with consumption substitution and saving in a two-period model. It confirms the robustness of classical risk-sharing results, even with recursive utility, and explores the link between consumption elasticity and saving. Precautionary savings and partial separation of risk aversion are demonstrated.

Insurance decisions range from trivial to significant, accumulating impact over time. Intuition can mislead, especially when premiums rise due to risk. Key factors include hazard size, wealth, risk aversion, and insurer margins. Greater transparency in insurance margins can help families make informed choices, improving financial well-being and societal welfare.

This article also has links to a calculator and spreadsheet which apply the framework described herein.

This study examines climate change's impact on water-related home insurance claims in Norway using a unique dataset. It develops a statistical model to address claim data challenges, reveals geographical and seasonal risk patterns, and evaluates pricing strategies. The findings provide insights for insurers to adapt to evolving climate risks.

“In this report we look at the steps taken by banks and insurers since 2021 to respond to the impacts of climate change, and we set out how our regulatory work has evolved in that period. We also look ahead to the planned release, later in 2025, of a consultation paper seeking views on an update to our supervisory statement (SS) 3/19.”