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内生免赔额保险合同定价的Copula面板数据模型AI 解读

Summary Insurers adjust premiums for renewing policyholders based on past claims, a practice known as experience rating. This paper examines experience rating in insurance contracts with deductibles, a key instrument for mitigating inefficiencies arising from information asymmetry between policyholders and insurers. We propose a copula-based panel data model that accounts for the endogeneity of deductible choice, particularly when the assumption of contemporaneous exogeneity…

利用深度学习将天气动态纳入保险理赔分流AI 解读

In property insurance claims triage, insurers often use static information to assess the severity of a claim and to identify the subsequent actions. We hypothesize that the pattern of weather conditions throughout the course of a loss event is predictive of the insured losses, and hence appropriate use of weather dynamics improves the operation of insurers’ claim management. To test this hypothesis, we propose a deep learning method to incorporate dynamic weather information…

利用成对 Copula 构造对捆绑保险风险进行依赖建模、定价与管理AI 解读

We propose a dependence-aware predictive modeling framework for multivariate risks stemmed from an insurance contract with bundling features — an important type of policy increasingly offered by major insurance companies. The bundling feature naturally leads to longitudinal measurements of multiple insurance risks, and correct pricing and management of such risks is of fundamental interest to financial stability of the macroeconomy. We build a novel predictive model that…

含内生协变量的复合分布 Copula 回归及保险免赔额定价应用AI 解读

This article concerns deductible pricing in nonlife insurance contracts. The primary interest of insurers is the effect of the contract deductible on a policyholder’s aggregate loss that is determined by a compound distribution where the sum of individual claim amount is stopped by the number of claims. Policyholders choose the deductible level based on their hidden risks, which makes deductible endogenous in the regressions for both claim frequency and claim severity. To…

以 copula 连接单变量 D-vine 的多元时间序列建模AI 解读

This article proposes a novel multivariate time series model named copula-linked univariate D-vines (CuDvine), which enables the simultaneous copula-based modeling of both temporal and cross-sectional dependence for multivariate time series. To construct CuDvine, we first build a semiparametric univariate D-vine time series model (uDvine) based on a D-vine. The uDvine generalizes the existing first-order copula-based Markov chain models to Markov chains of an…

保险经验费率厘定中的成对 Copula 构造AI 解读

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…