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    政大典藏 > College of Commerce > Department of MIS > Theses >  Item 140.119/114284


    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/114284


    Title: 應用倒傳遞類神經網路於P2P借貸投資報酬率預測之研究——以Lending Club為例
    A Study of the Application of Back-Propagation Neural Network to the ROI Forecasting in P2P Lending—A Case of Lending Club
    Authors: 李坤霖
    Contributors: 楊建民
    李坤霖
    Keywords: 金融科技
    個人對個人線上借貸
    類神經網路
    資料探勘
    機器學習
    Fintech
    P2P Lending
    Neural network
    Data mining
    Machine learning
    Date: 2017
    Issue Date: 2017-11-01 14:20:02 (UTC+8)
    Abstract: 金融科技因為能大幅降低金融活動中的交易成本與門檻，同時打破傳統金融交易資訊不及時的情況，因此能創造以往未有的商業價值。其中P2P Lending即透過電子化技術創造交易平台媒合資金提供者與需求者的微型授信服務，因為省去傳統金融機構中介的成本，故能提升供需雙方效益。然而特殊的營運方式使資金提供者須承擔更高風險，實際上P2P Lending亦曾發生重大詐騙與倒帳事件，因此使英美中政府加強監管，相較之下，我國仍維持不納入金融監管原則，因此本研究試圖以Lending Club具有代表性的案例，提供投資者選擇投資標的的建議。
    本研究搜集Lending Club自2007年至2011年42538筆已發行之借貸，在111個變數中使用 Pearson Correlation以及Information gain，並輔以文獻回顧進行變數選擇挑選22個變數。在搭配Dropout技術與透過網格搜索分析最佳化演算法、批次訓練樣本數、訓練次數等參數配置後，本研究訓練得到在測試集準確度達76%的類神經網路模型。經模擬後發現，類神經網路ROI的平均值為9.40，高於對照組7.02，經檢定驗證此差異結果可以採信，因此類神經網路能有效的給予投資人有效的投資建議。
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    3. 陳松興, 江俊豪. （2016）. 中國大陸互聯網金融之網路借貸 （Peer-to-Peer lending） 發展對台灣數位金融之影響研究—以風險監理角度. 兩岸金融季刊, 4（1）, 103-115.
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    Description: 碩士
    國立政治大學
    資訊管理學系
    104356033
    Source URI: http://thesis.lib.nccu.edu.tw/record/#G0104356033
    Data Type: thesis
    Appears in Collections:[Department of MIS] Theses

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