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"PROPERTY INSURANCE"
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Pair Copula Constructions for Insurance Experience Rating
In nonlife insurance, insurers use experience rating to adjust premiums to reflect policyholders' previous claim experience. Performing prospective experience rating can be challenging when the claim distribution is complex. For instance, insurance claims are semicontinuous in that a fraction of zeros is often associated with an otherwise positive continuous outcome from a right-skewed and long-tailed distribution. Practitioners use credibility premium that is a special form of the shrinkage estimator in the longitudinal data framework. However, the linear predictor is not informative especially when the outcome follows a mixed distribution. In this article, we introduce a mixed vine pair copula construction framework for modeling semicontinuous longitudinal claims. In the proposed framework, a two-component mixture regression is employed to accommodate the zero inflation and thick tails in the claim distribution. The temporal dependence among repeated observations is modeled using a sequence of bivariate conditional copulas based on a mixed D-vine. We emphasize that the resulting predictive distribution allows insurers to incorporate past experience into future premiums in a nonlinear fashion and the classic linear predictor can be viewed as a nested case. In the application, we examine a unique claims dataset of government property insurance from the state of Wisconsin. Due to the discrepancies between the claim and premium distributions, we employ an ordered Lorenz curve to evaluate the predictive performance. We show that the proposed approach offers substantial opportunities for separating risks and identifying profitable business when compared with alternative experience rating methods. Supplementary materials for this article are available online.
Journal Article
Should I Stay or Should I Go? The Impact of Natural Disasters and Regulation on U.S. Property Insurers' Supply Decisions
In this article, we identify the main factors that drive insurers' willingness to offer coverage in catastrophe-prone property insurance lines. We compare insurers' supply decisions in personal and commercial lines, with an emphasis on insurers' responses in the aftermath of natural disasters. Our empirical results suggest important policy implications with regard to improving the availability of insurance against catastrophic threats. Concerning the impact of regulatory constraints, we present empirical evidence that certain regulatory responses may unintentionally impede insurers' willingness to provide coverage against natural disasters.
Journal Article
Nonparametric Estimation of Copula Regression Models With Discrete Outcomes
Multivariate discrete outcomes are common in a wide range of areas including insurance, finance, and biology. When the interplay between outcomes is significant, quantifying dependencies among interrelated variables is of great importance. Due to their ability to accommodate dependence flexibly, copulas are being applied increasingly. Yet, the application of copulas on discrete data is still in its infancy; one of the biggest barriers is the nonuniqueness of copulas, calling into question model interpretations and predictions. In this article, we study copula estimation with discrete outcomes in a regression context. As the marginal distributions vary with covariates, inclusion of continuous regressors expands the region of support for consistent estimation of copulas. Because some properties of continuous outcomes do not carry over to discrete outcomes, specification of a copula model has been a problem. We propose a nonparametric estimator of copulas to identify the \"hidden\" dependence structure for discrete outcomes and develop its asymptotic properties. The proposed nonparametric estimator can also serve as a diagnostic tool for selecting a parametric form for copulas. In the simulation study, we explore the performance of the proposed estimator under different scenarios and provide guidance on when the choice of copulas is important. The performance of the estimator improves as discreteness diminishes. A practical bandwidth selector is also proposed. An empirical analysis examines a dataset from the Local Government Property Insurance Fund (LGPIF) in the state of Wisconsin. We apply the nonparametric estimator to model the dependence among claim frequencies from different types of insurance coverage.
Supplementary materials
for this article are available online.
Journal Article
Deciding Whether to Invest in Mitigation Measures: Evidence From Florida
Prior research provides theoretical insight into factors likely to impact the decision to mitigate such as the degree of risk aversion, the cost of market insurance, and the cost of self-insurance. We provide empirical evidence related to several hypotheses from the self-insurance literature on the decision to mitigate.
Journal Article
Market Discipline in Property/Casualty Insurance: Evidence from Premium Growth Surrounding Changes in Financial Strength Ratings
Analysis of abnormal premium growth surrounding changes in financial strength ratings for a large panel of property/casualty insurers generally indicates significant premium declines in the year of and the year following rating downgrades. Consistent with greater risk sensitivity of demand, premium declines were concentrated among commercial insurance, which has narrower guaranty fund protection than personal insurance. Premium declines were greater for firms with low pre-downgrade ratings, and especially pronounced for firms falling below an Arating. There is no evidence of moral hazard in the form of rapid commercial or personal lines premium growth following downgrades of A-or low-rated insurers.
Journal Article
Learning from natural disasters: Evidence from enterprise property insurance take-up in China
This paper examines the causal impact of natural disasters on property insurance take-up of firms. Using the data of industrial firms in China, we find that a one-standard-deviation increase in typhoon damage leads to a 2.6% increase in the purchase of property insurance the following year. This increase gradually declines and returns to the previous level three years later. Our results demonstrate that this impact is driven not by changes in risk preferences or supply-side variation but by the updated risk beliefs learned from the typhoon experience. Unlike household insurance decisions, the learning effect of firms demonstrates an indirect but positive effect of typhoons on the firm’s insurance decisions from its related firms in the upstream or downstream sectors, but not from competitors.
Journal Article
Expected loss utility for natural hazards and its application in pricing property insurance products
Due to climatic hazards and extreme weather events, the pricing of property insurance products is increasingly attracting the attention of policyholders, insurance companies, and governments. Pricing based on market-oriented methods has to consider the affecting factors from policyholders’ perceived value. Pricing strategy design generates the need for natural hazards risk assessments. A natural hazard risk assessment is closely related to the human factors of a disaster-bearing body. In response to this need, we design an extension of the expected utility that is inconsistent with the additive expected utility, considering the human factors of policyholders, which is referred to as the expected loss utility (ELU). The ELU presents two improvements of the currently used utility. First, subjective probability, which is derived from individual predictions over acts, is applied to the ELU function to overcome the disadvantage that objective probability attaches to uncertainty does not reflect the uncertainty of human factors. Policyholders’ risk attitudes are reflected by the interpretation of interactions among uncertain events. Second, the hesitant fuzzy linguistic preference relation (HFLPR) is employed as the assessment of individual loss evaluation to reflect a policyholder’s hesitation. We apply the techniques of fuzzy linguistic term aggregation and perform a comparison to simplify our loss utility function. A detailed process of expected loss assessment is proposed due to variations in natural environment factors, local social characteristics, and disaster-bearing body factors. An illustrative example is given to perform a comparison with cumulative prospect theory to show the merits of the ELU. This study quantifies policyholder’s cognition of uncertain event and the cognition’s influence on risk assessment which can guide pricing strategy of property insurance products.
Journal Article
The Combined Effect of Enterprise Risk Management and Diversification on Property and Casualty Insurer Performance
In a well-designed enterprise risk management (ERM) program, the firm integrates risk management into the strategic planning process, addressing strategic, financial, operational, and hazard risks under a single overarching process. This is particularly important to large financial firms, such as property and casualty (P&C) insurers, which face a diverse set of risks. Using a sample of P&C insurers with S&P ERM quality ratings from 2006 to 2013, we find that the quality of a firm's ERM is a significant determinant of P&C insurer performance and that, for firms with high-quality ERM programs, product line diversification has a significant positive effect on performance.
Journal Article
The High Price of Prudence--Benchmarking Canada's Property and Casualty Industry
Ineffective government intervention - including state-run insurance providers, high accident benefits, excessively costly tort mechanisms and a failure to crack down on auto theft - are the largest drivers of this variance in automobile insurance. [...]province-by-province comparisons of personal auto insurance show that there are substantial differences among provinces, with four jurisdictions producing higher-than-average results. The two other outliers (Ontario and Alberta) are served by a competitive private sector, but Alberta has chosen until very recently to maintain a costly tort environment and Ontario mandates particularly generous accident benefits and has experienced a plague of auto theft. * In the case of automobile insurance, just a handful of provinces need to think harder about how to improve car insurance premiums. The industry did see significant revenue growth, driven in part by a \"hard\" market for commercial lines (industry slang for a period when rates are rising faster than overall prices in the economy due to availability/capacity restraints).
Journal Article