:::

詳目顯示

回上一頁
題名:先進分類模式於保費數據分析之應用
書刊名:管理資訊計算
作者:程湲晏陳祐祥丁敏慧曹慧華
作者(外文):Cheng, Yuan YanChen, You ShyangTing, Min HuiTsao, Huei Hua
出版日期:2020
卷期:9:特刊2
頁次:頁112-120
主題關鍵詞:續期保費資料探勘保險資料屬性選取Renewal premiumData miningInsurance dataAttribute selection
原始連結:連回原系統網址new window
相關次數:
  • 被引用次數被引用次數:期刊(0) 博士論文(0) 專書(0) 專書論文(0)
  • 排除自我引用排除自我引用:0
  • 共同引用共同引用:13
  • 點閱點閱:8
成熟自由的金融保險市場,琳琅滿目的儲蓄理財工具,「保險」逐漸成為國人解決風險帶走擔憂的重要規劃,始的近年投保率攀升。目前家庭收入爬升緩慢,國人生計憂心,出現了續期保費繳不出的窘境。保險公司重要營運來自於保費收入,客戶保費續繳問題為保險公司與業務員關注議題。本研究經發達的3C系統與電腦科技結合,採用保險業界客戶保險資料,透過資料探勘選出19個條件屬性1個決策屬性。屬性選取技術,運用K鄰近法、規則、貝氏分類與決策樹四種演算法,執行保費續繳問題之預測,並找出:繳費人、薪資結構、購買保單數與有效保單數,為影響續期保費繳納之重要因子。實驗證明屬性選取後準確率高,決策樹J48為較優的演算法,研究結果提供給業界參考,達到公司、客戶與業務員三贏最優局面,為本研究之貢獻。
The mature and free financial and insurance market, as well as a wealth of savings and wealth management tools, "insurance" has gradually become an important plan for Chinese people to solve risks and take away worries. The insurance rate has risen in recent years. At present, the family income has been climbing slowly, and the country is worried about its livelihood. The important operation of insurance companies comes from premium income, and the issue of customer premium renewal is a topic of concern for insurance companies and salesmen. In this study, the developed 3C system is combined with computer technology, using customer insurance data from the insurance industry, and 19 condition attributes and 1 decision attribute are selected through data exploration. Attribute selection technology, using K proximity method, rules, Bayesian classification and decision tree four algorithms to perform the prediction of premium renewal problem, and find out: payer, salary structure, number of purchased policies and effective number of policies, as the impact Important factor for renewal premium payment. Experiments prove that the accuracy of attribute selection is high, and the decision tree J48 is a better algorithm. The research results are provided to the industry for reference, to achieve the best situation of win-win for the company, customers and sales staff, and contribute to this research.
期刊論文
1.李建然、湯麗芬(20190900)。董監事責任保險對企業避稅決策之影響。經濟論文,47(3),485-524。new window  延伸查詢new window
2.Chen, You-shyang、Tsao, Huei-hua、Huang, Cheng-ho(20170900)。Performance Evaluation of Comprehensive Function Classifiers: Taking Growth Rate Data as an Example。Applied Science and Management Research,4(1),61-70。new window  new window
3.Chiang, W. C.、Lin, Y. L.、Yu, L. C.、Chang, Y. H.、Chen, Y. A.、Wang, F. C.、Lin, K. C.(2019)。Application of text mining in the public perception analysis of global budget payment and National Health Insurance systems。Taiwan Gong Gong Wei Sheng Za Zhi,38(2),189-202。  new window
4.Machmudi, M. A.(2017)。Pemanfaatan Teknik Penambangan Data Pada Perguruan Tinggi。Journal Transformasi,13(2),120-127。  new window
5.Shamsuddin, S. N. W.、Mat, N. S. F. N.、Makhtar, M.(2017)。Relevant test set using feature selection algorithm for early detection of dyslexia。Journal of Fundamental and Applied Sciences,9(6S),886-899。  new window
6.Wang, Yichuan、Kung, LeeAnn、Wang, William Yu Chung、Cegielski, Casey G.(2018)。An integrated big data analytics-enabled transformation model: Application to health care。Information & Management,55(1),64-79。  new window
7.Zhang, X.、Hu, D.(2018)。The Behavior Analysis of Stock Analysts Based on K-Prototypes Clustering Algorithm。Journal of Computer Science and Application,8(6),894-901。  new window
8.Handayani, A.、Jamal, A.、Septiandri, A. A.(2017)。Evaluasi Tiga Jenis Algoritme Berbasis Pembelajaran Mesin untuk Klasifikasi Jenis Tumor Payudara。Journal Nasional Teknik Elektro dan Teknologi Informasi,6(4),394-403。  new window
9.李莎莎(2019)。基於數據優化的保險客户承保預測。Statistics and Application,8(5),784-796。  延伸查詢new window
10.李勝會、張子璇、徐貝爾(2019)。大數據背景下基本醫療保險公平性評價--基於 boosting 算法的實證研究。華南理工大學學報(社會科學版),21(2),46-57。  延伸查詢new window
11.邱創鈞、曾柏健、張炳騰(20190100)。應用資料探勘分類法於多屬性ABC存貨分類。創新與經營管理學刊,8(1),46-60。new window  延伸查詢new window
12.彭金隆、魏筱昀、陳彥志(20170500)。壽險公司銀行保險通路策略會不會受到競爭者行為的影響:動態競爭觀點之探討。臺大管理論叢,27(2S),149-176。new window  延伸查詢new window
13.鄭慧、賀婷婷、趙昕(2017)。基於保險賠付模型的財產險業海洋災害償付能力測算。統計與決策,2017(2),148-151。  延伸查詢new window
14.張元鳴(2017)。基於MapReduce的Bagging决策樹優化算法。計算機工程與科學,39(5),841-848。  延伸查詢new window
15.趙健宇、陸正飛(2018)。養老保險缴费比例會影響企業生產效率嗎?。經濟研究,2018(10),97-112。  延伸查詢new window
16.蘇本躍、蔣京、湯慶豐、盛敏(2017)。基於函数型數據分析方法的人體動態行為識别。自動化學報,43(5),866-876。  延伸查詢new window
17.穆懷中、杜芳雨(2018)。技術替代趨勢下基礎養老保險"產出"繳費模式研究。中國人口科學,2018(3)。  延伸查詢new window
18.王海東(2019)。C5.0決策樹與RBF神經網絡模型用於急性缺血性腦卒中出血性轉化的風險預測性能比較。中華疾病控制雜誌,23(2),227-232。  延伸查詢new window
19.同桂杰(2019)。基於貝葉斯決策樹的小麥鎘風險識別規則提取。中國環境科學,39(3),1336-1344。  延伸查詢new window
20.蔡明學、黃建翔(20190600)。應用資料探勘技術探究我國高中生適性學習影響因素。當代教育研究季刊,27(2),39-76。new window  延伸查詢new window
學位論文
1.石鈺齊(2019)。探討癌症病人五年內罹患焦慮症與憂鬱症之預測模式(碩士論文)。高雄醫學大學。  延伸查詢new window
2.吳宛縈(2016)。社會型與商業型長期照顧保險整合之研究(碩士論文)。淡江大學。  延伸查詢new window
3.林智婷(2016)。基於近鄰傳播分群演算法之新型態投資組合風險分散策略(碩士論文)。國立交通大學。  延伸查詢new window
4.邱弘懿(2016)。資料探勘技術應用於不均衡資料預測表現比較--以信用卡違約風險預測為例(碩士論文)。國立交通大學。  延伸查詢new window
5.姚靜姍(2018)。簡易貝氏分類器在不平衡資料集上效能改善之研究(碩士論文)。國立成功大學。  延伸查詢new window
6.段繼明(2018)。長照之保險規劃(碩士論文)。國立臺灣大學。  延伸查詢new window
7.陳佑任(2016)。採用遠距照護之決策樹分類--以臺灣遠距照護系統為例(碩士論文)。國立臺灣大學。  延伸查詢new window
8.陳鈺錡(2018)。特徵選取於資料離散化之影響(碩士論文)。國立中央大學。  延伸查詢new window
9.蔡孟峰(2017)。植基於反向排序K鄰近法和合成少數類樣本的增量技術在資料不平衡之研究與應用(博士論文)。國立中興大學。  延伸查詢new window
10.鍾文豪(2018)。以全民健保資料庫探討高齡人口住院及臨終需求(碩士論文)。國立政治大學。  延伸查詢new window
11.陳則宏(2019)。一個混合分類演算法應用於入侵偵測系統(碩士論文)。國立中興大學。  延伸查詢new window
圖書
1.Braun, Alexander、Schreiber, Florian(2017)。The Current InsurTech Landscape: Business Models and Disruptive Potential。St. Gallen:Institute of Insurance Economics I.VW-HSG, University of St. Gallen。  new window
 
 
 
 
第一頁 上一頁 下一頁 最後一頁 top
:::
無相關博士論文
 
無相關書籍
 
無相關著作
 
QR Code
QRCODE