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應用資料採礦技術於信用卡使用行為及市場需求

Applications of Data Mining Techniques to the Behavior of Using Credit Cards and Market Demand

摘要


近隨著金融自由化、國際化的趨勢,加上國民所得提高、電子化的普及,使得信用卡市場蓬勃發展,國內各大銀行紛紛積極投入信用卡發卡行列。台灣的信用卡市場競爭的程度,從各發卡銀行所提供消費者的各項附加服務,如辦卡送禮、持卡免年費、失卡零風險、購物優惠等,幾乎都已是每一張信用卡的基本配備。隨著卡債、卡奴的事件爆發,銀行業者舊有的信用卡行銷策略已經宣告失敗,但信用卡市場背後帶來的經濟效益,仍然是不容忽視,如今,要如何增加信用卡市場的佔有率已不是銀行業者的行銷重點,高佔有率並不一定就能帶來高經濟效益。銀行業者的行銷策略應該是做好信用卡市場區隔,找出不同特性的消費族群,依消費族者選擇信用卡的考量因素擬定行銷策略,進而提升市場競爭地位。本研究選用四種模型建置方式,分別為羅吉斯迴歸、C5.0、CHAID以及類神經網路,經由分類矩陣評估比較四種模型,其中C5.0不論是在整體預測正確率、反查率或準確度,皆是高於其它三個模型,故最後選擇C5.0此一模型。透過C5.0共獲得七項影響「是否有使用信用卡」之相關變數,其中「是否有出國旅行」、「經濟來源是否為自己」、「性別」、「是否畢業後找工作」、「是否有使用網路消費」、「認同環保意識」、「是否有投資或買保險」,此七項變數對使用信用卡消費具較大影響力,最後本研究會針對這些變數再給與發卡銀行建議。

關鍵字

信用卡 資料採礦 C5.0 CHAID 類神經網路

並列摘要


As the trend of financial liberalization and globalization and also the popularization of electronic business and the increase of domestic income, the credit card market has bloomed vigorously then ever, banks are urging on developing credit card markets. All those additional service of every bank could be seen as a clue to know the competitiveness in Taiwan, such as free gift, free annual fee, zero risk of losing cards, shopping discount…etc., and those service almost become a basic equipment of every credit card. With credit debt and credit card slaves increasing, bank's former marketing strategies have failed. The economic benefits of credit card market still are not ignored. Today, how to increase market share of credit card is not the key point of bank’s marketing strategy. There is not necessary that high market share can bring high economic benefits. In order to follow this trend, the study aims to discover the corn factors of possessing credit cards through the application of Clementine 12.0 software. Since Decision Tree-C5.0 is excellent in the forecast accuracy and validity as compared to Logistic Regression, Decision Tree-CHAID and Neural Net were adopted in this research. Through using Decision Tree-C5.0, this study identified seven factors that have greater impact on using credit cards and they are "Whether respondent travel abroad", "Is the source of income making by yourself", "Gender", "Do respondent look for jobs after graduating from school", "Do respondent buy something on the internet", "Approve the environmental awareness". This research will chiefly use these seven factors to provide the marketing portfolio strategy recommendations for banks.

並列關鍵字

Credit Card Data Mining C5.0 CHAID Neural Net

參考文獻


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