Pricing and Profitability in Non-Life Insurance

本研究项目的总体目标是开发新的多元统计方法，用于非寿险数据建模。保险公司的偿付能力和盈利能力关键取决于他们准确评估与所有业务线相关的财务风险的能力。虽然有几种做法可以确保保险公司的正常运作，但费率制定是一个至关重要的组成部分。从根本上说，费率制定包括开发定价模型，以估计与保险公司为换取向投保人提供的保护而承担的风险相关的成本。当然，费率制定做法对保险公司的利润率和整体经营都有重大影响。费率制定涉及对过去索赔的全面评估，这些索赔通常是多维的，因为它们反映了保险产品的多风险设计。为了有效地管理和充分定价的基本风险，这是必要的，索赔经验的分析进行了多变量规模。在分析索赔时，考虑两部分的方法是有见地的，其中为索赔频率（索赔数量）和严重性（每项索赔的损失金额）定义了一个模型。这项研究计划的主要目标是开发一种新的两部分建模框架，涉及多变量频率和多变量严重程度模型。这些模型中的一个重要考虑因素是索赔数量与金额本身之间的关联。因此，必须将额外的依赖层并入框架中以准确地捕获频率-严重性相关性。为了使模型适用于利率制定，协变量效应也必须纳入框架。事实上，保费是根据投保人的特征确定的，这些特征可以预测他们的风险。因此，将开发基于回归的多变量模型。虽然盈利能力与定价直接相关，但客户保留也起着关键作用。为此，该提案的另一个方面是探索使用个性化策略来建立最佳的客户保留行动（如折扣），以最大限度地提高盈利能力。 通过这项研究计划开发的方法将允许更好地了解索赔数据中固有的复杂依赖结构。本建议的一个主要目标是围绕费率制定，开发新的定价模型，反映保险产品的多风险性质。在拟议的框架中，盈利能力将评估不仅在定价方面，而且在客户保留方面，通过开发新的个性化保留策略。该计划中开发的整体建模框架将允许对索赔进行更准确和全面的分析，这对于保险业的有效风险管理和战略规划至关重要。

The overall goal of this research program is to develop novel multivariate statistical methods for modelling non-life insurance data. An insurer's solvency and profitability rely critically on their ability to accurately assess the financial risk associated with all lines of business. While there are several practices that ensure the proper functioning of an insurance company, ratemaking is a vital component. Fundamentally, ratemaking consists of developing pricing models to estimate the costs associated with the risk assumed by the insurer in exchange for the protection provided to the policyholder. Certainly, ratemaking practices have significant impacts on both profit margins and the overall operations of an insurer. Ratemaking involves a comprehensive evaluation of past claims, which are typically multidimensional as they reflect the multi-peril design of insurance products. In order to effectively manage and adequately price the underlying risk, it is imperative that the analysis of claims experience be carried out on a multivariate scale. In analyzing claims, it is insightful to consider a two-part approach wherein a model is defined for both the claim frequency (number of claims) and severity (loss amount per claim). A main goal of this research program is to develop a novel two-part modelling framework involving both a multivariate frequency and multivariate severity model. An important consideration in these models is the association between the claim counts and amounts themselves. Accordingly, an additional layer of dependence must be incorporated into framework to accurately capture the frequency-severity correlation. In order for the models to be appropriate for ratemaking, covariate effects must also be incorporated into the framework. Indeed, premiums are determined as a function of policy-holder characteristics which are predictive of their risk. As such, regression-based versions of the multivariate models will be developed. While profitability is directly related to pricing, customer retention also plays a key role. To this end, an additional facet of the proposal is to explore the use of personalized strategies for establishing optimal customer retention actions (such as a discount) to maximize profitability. The methodology developed through this research program will allow to gain better insights into the complex dependence structures inherent in claims data. Focusing on ratemaking, a main goal of this proposal it to develop novel pricing models which reflect the multi-peril nature of insurance products. In the proposed framework, profitability will be assessed not only in terms of pricing, but also in terms of customer retention through the development of novel personalized retention strategies. The overall modelling framework developed in this program will allow for a more accurate and comprehensive analysis of claims, which is imperative for effective risk management and strategic planning in the insurance industry.