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The report highlights Federated Learning's (FL) benefits in claims loss modeling by enabling collaboration across multiple insurance datasets without data sharing. FL addresses data privacy concerns, rarity of claim events, and lack of informative factors. It enhances forecasting effectiveness while preserving data privacy, applicable beyond insurance to fraud detection and catastrophe modeling, fostering future collaborations.

Monte Carlo studies are conducted to compare the proposed spectral risk measure estimator with the existing parametric and non parametric estimators for left truncated and right censored data. Based on our simulation study we estimate the exponential spectral risk measure for three data sets viz; Norwegian fire claims data set, Spain automobile insurance claims and French marine losses.

Experts agree on the societal benefits of pooling longevity risk through annuities and pensions. While pooling reduces the upfront capital needed for a secure income, challenges arise when participants vary in wealth and health. This paper proposes a model for distributing income in diverse longevity-risk pools, emphasizing the role of social cohesion.

The insurance sector's role in sustainable finance, especially in the green transition, relies on balancing sustainability goals with prudential concerns like risk management under Solvency II. Emphasizing the importance of the Own Risk and Solvency Assessment (ORSA), the sector aims to align investments with policyholder interests while addressing sustainability risks. Efforts continue to integrate sustainability into regulatory frameworks, balancing risk management with support for the sustainability transition.

The study investigates how opting for cyber insurance impacts firms' risk management. It reveals that while cyber insurance often decreases proactive risk prevention (ex-ante moral hazard), it enhances post-breach mitigation efforts, improving outcomes. The key lies in contract design balancing breach coverage and co-insurance rates, emphasizing the need for a robust risk mitigation market in cybersecurity management.

The paper explores convex risk measures with weak optimal transport penalties, demonstrating explicit representations via nonlinear transformations of loss functions. It delves into computational aspects, discussing approximations using neural networks and applies these concepts to diverse examples. Finally, it demonstrates practical applications in insurance and finance for worst-case losses and no-arbitrage pricing beyond quoted maturities.

"An adverse development cover (ADC) is a form of an excess of loss reinsurance contract that provides coverage for future loss payments relating to claims incurred prior to a specified date… A framework for assessing the value of an ADC from the perspective of the ceding insurer is developed. This value assists in making decisions regarding the acquisition of an ADC, comparing available options on offer and accounting for the ADC under the IFRS17 accounting standard."

Information about #fdic #insurance and communication about #bank #stability by the #federalreserve can reassure depositors and mitigate #bankruns, while communication from political leaders only influences their electoral base.

This study examines a #riskaverse #insured who buys deductible #insurance and uses a barrier strategy for reporting #losses. The #insurer has a bonus-malus system with two rate classes; shifting to a costlier class occurs upon loss reporting. The insured's tendency to underreport losses is established under specific conditions, with her strategic reporting threshold derived. Allowing insureds to choose deductibles reveals positive equilibrium values, challenging the assumption of full insurance optimality. This work explains the common underreporting of losses across non-life insurance sectors.

This study addresses #climate-induced decline in #honey production, a significant #risk for #beekeepers. A #parametricinsurance policy is discussed, using #weatherdata to trigger payouts for losses due to adverse conditions. The approach is evaluated using random forests, comparing beekeepers' losses to #insurance benefits under various weather #scenarios, alongside traditional methods. An #italian case example demonstrates pricing for different regions.