本文選題：生理年齡 + 精算定價　； 參考：《保險研究》2017年02期

【摘要】：互聯(lián)網和大數(shù)據(jù)技術的融合讓個體生理數(shù)據(jù)分析成為可能,并進一步推動個體健康風險量化,本文在此背景下,探討人工智能與保險融合的新路徑,提出了以生理年齡作為個體健康的風險量化指標,進而作為定價基礎的新模式。本研究根據(jù)保險特征,優(yōu)化深度學習技術,通過分析人體老化的生理特征,建立了基于手背紋理照片的生理年齡評價模型,在大量數(shù)據(jù)的支持下,可以獲得穩(wěn)健、精準的生理年齡定量評價結果。本文還討論了以深度學習為代表的人工智能技術與保險融合的模式,提出了可能的結合點以及對應的比較結果。鑒于生理年齡可以更充分反映投保人的"健康風險"信息,論文認為該模式具有很好的應用價值,并通過分析現(xiàn)狀,認為當前是保險公司建立"人工智能大腦"的關鍵時期。
[Abstract]:The combination of Internet and big data technology makes it possible to analyze individual physiological data and further promote the quantification of individual health risk. In this context, this paper discusses a new path of combining artificial intelligence and insurance. A new model based on physiological age is put forward, which can be used as a quantitative index of individual health risk and then as the basis of pricing. According to the characteristics of insurance, optimizing the technology of deep learning and analyzing the physiological characteristics of human aging, a physiological age evaluation model based on texture photographs of the back of the hand is established, which can be robust under the support of a large amount of data. Accurate quantitative evaluation of physiological age. This paper also discusses the model of the integration of artificial intelligence technology and insurance represented by deep learning, and puts forward the possible combination points and the corresponding comparison results. In view of the fact that physiological age can fully reflect the "health risk" information of the insured, the paper thinks that this model has good application value, and by analyzing the present situation, it is considered that the key period for insurance companies to establish "artificial intelligence brain" is at present.
【作者單位】： 中央財經大學中國精算研究院;
【基金】：北京市哲學社會科學基金項目(編號:15JGC153) 教育部人文社科項目(編號:16YJCZH148);教育部人文社會科學重點研究基地重大項目(編號:16JJD790060) 數(shù)據(jù)燈塔(Data Lighthouse)計劃
【分類號】：F842.4

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1 張翠霞;關于職工生理專業(yè)年齡及其結構關系的戰(zhàn)略思考[J];中國保險;1999年05期

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