23 résultats
pour « insurers »
The paper explores the use of machine learning, particularly deep learning techniques, in insurance pricing by modeling claim frequency and severity data. It compares the performance of various models, including generalized linear models and neural networks, on insurance datasets with diverse input features. The authors use autoencoders to process categorical variables and create surrogate models for neural networks to translate insights into practical tariff tables.
"We study a #reinsurer who faces multiple sources of #model #uncertainty. The reinsurer offers contracts to n #insurers whose #claims follow different compound #poisson processes. As the reinsurer is uncertain about the insurers' claim severity distributions and frequencies, they design reinsurance contracts that maximise their expected wealth subject to an #entropy #penalty…."
"This paper examines a #stochastic one-period #insurancemarket with incomplete information. The aggregate amount of #claims follows a compound #poisson distribution. #insurers are assumed to be exponential utility maximizers, with their degree of #riskaversion forming their private information. A premium strategy is defined as a map between risk types and premium rates. The optimal premium strategies are denoted by the pure-strategy #bayesian #nash equilibrium, whose existence and uniqueness are demonstrated under specific conditions for the demand function..."
"There is a well-known conflict of interest between #liabilityinsurance #insurers and policyholders with respect to the decision to settle or litigate a #claim. This short note provides a simple graphical explanation for the problem and grounds it in the way the structure of the parties’ payouts drives their attitudes towards #risk. An optional appendix links the insights to the elementary mechanics of financial options.
Textual and cluster analysis of 10-K documents reveals three #riskculture classes linked to #riskstrategies, decisions, and recruitment. Firms with a strong risk culture show better #financialperformance and more diverse boards. #regulatory #supervision can help #insurers improve #risk behaviors.
#Insurers, #reinsurers and #regulators struggle to #quantify and #manage the #financialimpact of #climatelitigation. This report provides a toolkit to help analyze the #risks, and outlines a simple climate litigation #riskmodel.
#insurers have discretion to determine #solvencyii #capitalrequirements. We find that long-term guarantees measures substantially influence the reported solvency ratios. The measures are chosen particularly by less solvent insurers and firms with high interest rate and credit spread sensitivities. Internal #models are used more frequently by large insurers and especially for #risks for which the firms have already found adequate immunization strategies.
"We analyze #esg scores of worldwide #propertyandcasualtyinsurance during 2012-2022, and show that more sustainable #insurers have high operating leverage, although their combined ratios and z-scores reveal that they are financially stable."
The findings suggest a positive association between #insurers larger exposures to #risk and higher holdings of #brownassets with higher sensitivity to #climatechange and #transition risk.
This paper introduces the application of Deep Reinforcement Learning (#drl) in #alm, addressing limitations of traditional methods reliant on human judgement. The findings highlight the potential of DRL to enhance #riskmanagement outcomes for #insurers, #banks, #pensionfunds, and #assetmanagers, providing improved adaptability to changing market conditions.