报告人：Zhuo Jin金卓（澳大利亚麦考瑞大学）

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

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 seconds, 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.

报告时间：2025年4月8日（星期二）10:00-12:00

报告地点：科技楼南楼711室

邀请人：吴付科

报告人简介：金卓教授，澳大利亚麦考瑞大学精算中心教授，2005年和2007毕业于申博sunbet官网数学系应用数学专业，分别获理学学士和硕士学位，2011年毕业于美国韦恩州立大学数学系数学专业，获哲学博士学位。2011年至2022年在澳大利亚墨尔本大学经济系精算中心工作，2022年至今当前在澳大利亚麦考瑞大学精算中心工作。研究方向为随机最优控制，随机系统的数值方法，精算学，数理金融。在国际期刊发表70余篇论文，期刊包括Insurance Mathematics and Economics, European Journal of Operational Research, SIAM Journal on Control and Optimization, Automatica, ASTIN: Bulletin, Scandinavian Actuarial Journal.