10 résultats
pour « losses »
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.
"… we find that the #uncertainty premium is negatively correlated with #riskaversion at all sizes and #probabilities of #risks. This leads to a selection effect: individuals who purchase #insurance are not necessarily the most risk averse. We show that the resulting #misallocation of insurance leads to large #welfare#losses."
"We show that past operational losses are informative of future losses, even after controlling for a wide range of financial characteristics. We propose that the information provided by past losses results from them capturing hard to quantify factors such as the quality of operational risk controls, the risk culture, and the risk appetite of the bank."
"... the information provided by past losses results from them capturing hard to quantify factors such as the quality of operational risk controls, the risk culture, and the risk appetite of the bank."
"... at least in financial terms, the associated losses can be covered by insurance contracts. The role of actuaries is to develop adequate contract structures, calculate correct premiums, and implement quantitative risk management in insurance firms."
"Our findings offer new evidence on how economic shocks transmit to banking industry losses with implications for risk management and supervision."
"... different loss reserving models specialise in capturing different aspects of loss data. This is recognised in practice in the sense that results from different models are often considered, and sometimes combined. For instance, actuaries may take a weighted average of the prediction outcomes from various loss reserving models, often based on subjective assessments."
"We ... estimate the quarterly evolution of expected losses (Capital at Risk) for the UK banking sector, and via Monte Carlo simulations the stochastic distribution of UK banks’ losses to study the severity and likelihood of tail-events (Conditional Capital at Risk). In the end, we provide insights on the impact of the Covid-19 pandemic on UK banking system’s loss distribution by decomposing the sources of average and tail risks."
" We show that the U.S. insurance industry’s capacity to pay catastrophe losses is higher in 2020 than it was in 1997. Insurers could pay 98% of a $200 billion loss in 2020 in comparison to 81% in 1997."
"Current reporting standards for insurers require a decomposition of observed profits and losses in such a way that changes in the insurer's balance sheet can be attributed to specified risk factors. Generating such a decomposition is a nontrivial task because balance sheets generally depend on the risk factors in a non-linear way. This paper starts from an axiomatic perspective on profit and loss decompositions and finds that the axioms necessarily lead to infinitesimal sequential updating (ISU) decompositions, provided that the latter exist and are stable, whereas the current practice is rather to use sequential updating (SU) decompositions. The generality of the axiomatic approach makes the results useful also beyond insurance applications wherever profits and losses shall be additively decomposed in a risk-oriented manner."