臺灣博碩士論文加值系統

由近年來連續不斷發生的人身保險詐欺案顯示，詐領保險金的金額逐年增加，保險詐欺不但使得保險人財務深受其害，整個社會也遭到嚴重的創傷與損失，付出許多社會成本。基此，本研究採用Logistic Regression Model為理賠評等模式，探討台北市人壽保險商業同業公會所擬定「人身保險業通報制度」之揭露事項，並從中找出影響保險詐欺之顯著變數，建立一套正確且實用的理賠評等模式以及相對因應策略，為保險人爭取理賠時效、減少審核時間，客觀科學化的方法更能使調查資料得到迅速的整理與分析，旨在使保險詐欺難以從事，且容易被偵察及制阻，減少保險詐欺頻率。

Life insurance fraud cases have kept happening continuously in recent years, which reveal that the amount of insurance fraud is keeping increasing. Insurance fraud not only affected the finance of insurers very much, but the whole society also encountered lots of damage and loss, and caused much social cost. Therefore, this study took Logistic Regression Model for compensation criterion mode to probe into the exposed items and other related variables of「Life Insurance Notification System」set by Taipei Life Insurance Commercial Association. It also deeply probed and found the variables of insurance fraud for setting up the most accurate and practical compensation criterion mode. It is set to strive for insurers compensatory time, reduce the time of verification, its objective and scientific methods offer the investigated information fast consolidation and analysis. The purpose of this mode is to stop the insurance fraud and make it easy to be predicted and prevented, and reduce the frequency of insurance fraud.

目錄
壹、緒論1
一、研究動機與目的1
二、研究範圍2
三、研究架構3
貳、保險詐欺因素分析與文獻回顧5
一、研究背景5
二、人身保險詐欺之分析11
三、人身保險詐欺之防阻對策17
四、文獻回顧20
參、流程分析與模型設計25
一、研究流程25
二、LR模式之建立26
三、LR模式估計與檢定29
四、MNR模式之建立33
肆、實證分析36
一、資料來源及內容38
二、資料分析38
三、樣本常態性與差異性檢定46
四、LR模式50
五、最適LR模式52
六、其他相關實證結果58
伍、結論63
一、結論63
二、後續研究建議64

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