报告题目：Large Language Models for Textual Analysis of Insurance Claims

报 告 人：钱林义（华东师范大学教授）

报告时间：2025年11月11日（星期二下午）15：30-17：00

报告地点： 腾讯会议： 374-912-223 （15：30开始）

报告摘要：This study proposes a comprehensive and general framework for examining discrepancies in textual content using large language models (LLMs), broadening application scenarios in the insurtech and risk management fields, and conducting empirical research based on actual needs and real‐world data. Our framework integrates OpenAI's interface to embed texts and project them into external categories while utilizing distance metrics to evaluate discrepancies. To identify significant disparities, we design prompts to analyze three types of relationships: identical information, logical relationships and potential relationships. Our empirical analysis shows that 22.1% of samples exhibit substantial semantic discrepancies, and 38.1% of the samples with significant differences contain at least one of the identified relationships. The average processing time for each sample does not exceed 4 s, and all processes can be adjusted based on actual needs. Backtesting results and comparisons with traditional NLP methods further demonstrate that our proposed method is both effective and robust.

报告人简介：钱林义，教授，博士生导师，华东师范大学统计学院院长助理、保险与精算系主任，中国普惠养老金融研究中心副主任，上海市曙光学者，中国准精算师，《应用概率统计》杂志责任编辑，中国工业与应用数学学会金融数学与工程和精算保险专委会委员，中国现场统计研究会风险管理与精算分会副理事长，中国保险学会教育专委会副主任委员，中国现场统计研究会统计历史与文化分会常务理事，中国优选法统筹法与经济数学研究会量化金融与保险分会理事，中国社会保障学会商业保险分会理事，中国保险学会理事，上海市保险学会理事。研究方向为概率统计，保险精算。在Journal of Econometrics、Bernoulli、Journal of Risk and Insurance、Insurance: Mathematics and Economics、Astin Bulletin、Scandinavian Actuarial Journal、North American Actuarial Journal等杂志上发表论文60余篇，专著1本，主持国家课题4项，省部级课题6项；作为子课题负责人参与一项国家社科重大项目和一项国家自科重点项目。曾获上海瑞士再保险精算科学奖三等奖、第十一届全国统计科研优秀成果奖二等奖、上海市优秀博士论文奖、上海市自然科学奖三等奖等奖项；撰写的多篇专报获得国家和省部级领导人批示。