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This research examines how ESG performance impacts default probability (PD) in life and non-life insurance firms. Findings show that improved ESG practices reduce both short-term and long-term PD, benefiting credit ratings and financial stability. Policymakers and managers can use this to enhance risk management and sustainable finance strategies.
This study assesses flood-related financial stability risks in the Netherlands through diverse scenarios for bank stress tests. Results show varying impacts on bank capital, amplified by climate change. Stronger defenses can mitigate some effects, and there's a non-linear relationship between flood damages and capital depletion, emphasizing extreme scenario consideration.
This research uses Monte Carlo simulations to examine managing basis risk in parametric insurance through diversification. Findings show that increasing contracts reduces risk and volatility, spatial relationships significantly affect risk levels, and disaster severity has little impact, suggesting severe events shouldn't limit parametric insurance development.
This paper addresses actuarial challenges in insurance by developing a user-friendly algorithm for optimal reinsurance decisions, balancing capital efficiency and asset/liability management. It combines expert judgment with quantitative methods, overcoming computational barriers for non-specialists. The techniques can be applied to broader risk management problems in insurance.
The study explores an insurance company managing financial risk through reinsurance, aiming to optimize terminal wealth and minimize ruin probability. Using neural networks, it finds the optimal reinsurance strategy based on expected utility and a modified Gerber-Shiu function, illustrated by a numerical example involving a Cramér-Lundberg surplus model.
This study analyzes insurance claim processing delays due to limited capacity and backlogs. It proposes optimal capacity selection to minimize costs by accounting for delay-adjusted and fixed settlement costs, supported by theoretical insights and a large-scale numerical study to demonstrate practical application.
The lack of risk transfer stems from structural forces that deter innovation in insurance policies, leading to inefficient risk management and hindering market development. Policy responses can help address these issues.
This study explores large-scale, technology-driven consumer fraud over the next decade, offering four forward-looking scenarios. Using trends, scenarios, and narratives, feedback was gathered to identify strategies for tackling fraud. A systems approach modeled criminal and anti-fraud systems, leading to key "challenge" themes to guide future anti-fraud efforts.
Climate change poses financial risks to institutions. Quantifying these risks is difficult, limiting mitigation efforts. Scenario analysis helps assess risks by extending macro-climate scenarios to asset-level analysis. Despite advancements, limitations remain in applying this approach to financial modeling.
This study develops a new method to estimate U.S. homeowners insurance coverage and premiums, revealing significant under-insurance, especially among vulnerable borrowers in high-risk areas. It highlights the role of rising premiums and behavioral inertia in under-insurance, with potential impacts on mortgage and real estate markets.