Pricing and Profitability in Non-Life Insurance

本研究计划的总体目标是发展新的多元统计方法来模拟非寿险数据。保险公司的偿付能力和盈利能力主要依赖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，以估计与保险公司承担的风险相关的成本，以换取向投保人提供的保护。当然，费率制定的做法对保险公司的利润率和整体运营都有重大影响。费率制定涉及对过去索赔的全面评估，这通常是多维的，因为它们反映了保险产品的多风险设计。为了有效地管理和适当地为潜在风险定价，必须在多元尺度上对索赔经验进行分析。在分析索赔时，考虑由两部分组成的方法是有见地的，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。本研究计划的主要目标是开发一个新的两部分建模框架，包括多变量频率和多变量严重性模型。在这些模型中，一个重要的考虑因素是索赔数和索赔金额本身之间的关联。因此，必须将附加的依赖层合并到框架中，以准确地捕获频率-严重性相关性。为了使模型适合于费率制定，协变量效应也必须纳入框架。事实上，保费是作为投保人特征的函数来确定的，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版本。虽然盈利能力与定价直接相关，但客户保留率也起着关键作用。为此，建议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），以最大化盈利能力。通过该研究项目开发的方法将使人们能够更好地了解索赔数据中固有的复杂依赖结构。在费率制定方面，本建议的主要目标是建立反映保险产品多重风险性质的新型定价模型。在提出的框架中，盈利能力不仅将根据定价进行评估，还将通过开发新的个性化保留策略来评估客户保留。该项目开发的整体模型框架将允许对索赔进行更准确和全面的分析，这对于保险业有效的风险管理和战略规划是必不可少的。

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.