A joint model of cost and churn for the insurance industry
针对保险市场索赔成本高变异性与客户流失影响盈利的问题，提出用多元Tweedie回归与共享随机效应联合建模索赔成本与流失行为，帮助保险公司更准预测成本、分类客户盈利性并设计留存或定价策略。
Abstract In insurance markets, claim costs are highly variable, heavy‐tailed, and difficult to predict. At the same time, policyholder retention and lapse behavior (customer churn) are critical determinants of long‐term profitability and solvency. Most existing models in the literature treat claim costs and lapses as independent, overlooking potential latent associations that arise from adverse selection and unobserved heterogeneity. In this article, we introduce a joint modeling framework that simultaneously captures individual‐level claim costs and churn behavior, using multivariate Tweedie regression with shared random effects. This framework integrates claim cost dynamics with lapse risk, allowing insurers to more accurately predict costs, classify policyholder profitability, and design retention or pricing strategies. Applying our approach to data from the Wisconsin Local Government Property Insurance Fund, we demonstrate that accounting for dependence between claim risk and lapse risk improves out‐of‐sample prediction and yields actionable insights for customer valuation and management.