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保诚 精算师认识一下你的新同事——数据科学家和生成式人工智能.pdf

上传人: a****d 编号:402731 2025-01-10 44页 3.27MB

1、SINGAPORE ACTUARIAL CONFERENCE 202426-29 August 2024Actuaries,meet your new co-workers Data Scientist and Generative AISINGAPORE ACTUARIAL CONFERENCE 202426-29 August 2024Agenda Data Scientists Who are these data scientists?Actuaries vs Data Scientists Learning from each other Generative AI What is

2、Generative AI?Generative AI Does Music,Image,Actuarial Exams,Data Analytics etc.ChallengesSINGAPORE ACTUARIAL CONFERENCE 202426-29 August 2024Data ScientistsAndrew NgSINGAPORE ACTUARIAL CONFERENCE 202426-29 August 2024Who are these Data Scientists?Data Science Interdisciplinary field using statistic

3、s,scientific computing,scientific methods,processes,visualization,algorithms and systems to extract or extrapolate knowledge and insights from data.Data Scientists within insurance,work on several use cases Policy Retention Sales-related:Propensity-to-buy,Next-Best-Offer Claims Analysis:Health-relat

4、ed products Customer Lifetime Value So whats the difference between actuarial vs data science work?SINGAPORE ACTUARIAL CONFERENCE 202426-29 August 2024Actuary vs Data Scientist doing lapse analysisData Science PerspectiveActuarial PerspectiveScoring each customer to see which have a higher chance of

5、 lapsing in the next 6 months and finding ways to retain them.Obtain historical lapse rates for assumption setting(eg.Reserving,Product Pricing)PurposeSINGAPORE ACTUARIAL CONFERENCE 202426-29 August 2024Actuary vs Data Scientist doing lapse analysisData Science PerspectiveActuarial PerspectiveScorin

6、g each customer to see which have a higher chance of lapsing in the next 6 months and finding ways to retain them.Obtain historical lapse rates for assumption setting(eg.Reserving,Product Pricing)PurposeLapse Prediction using Machine Learning TechniquesLapse Experience Study based on ExposureOverall

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本文主要介绍了2024年8月26日至29日在新加坡举行的 actuarial conference 的相关内容。会议探讨了数据科学家和生成式AI在保险行业中的角色和影响,以及它们如何与精算师共同工作。数据科学家使用机器学习技术进行客户流失分析,而精算师则更多地关注于设置假设和产品定价。文章还提到了精算师和数据科学家在客户级别和产品级别上的工作差异。此外,文章还讨论了生成式AI的挑战,包括图像问题、知识截止、模型崩溃、越狱问题等。最后,文章提到了 Goldman Sachs 的一篇关于生成式AI投资的文章,指出生成式AI的炒作与现实之间的差距。
"AI在保险行业的未来角色" "如何利用AI提高精算工作效率" 合作还是竞争?"
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