| 摘要: | 消費金融是目前個銀行主要的獲利來源之一，其中現金卡業務更是銀行業個人消費金融部門最重要的收益。該產品同時擁有高利差、高效率、高報酬之優點，且隨著現金卡持有人及使用率之逐年增加，現金卡儼然已成為銀行業重要的獲利商品。 現金卡的特色是手續簡便，核准速度快，因為利率較高，故目標客戶群為對利率敏感度不高的經濟弱勢族群。由於銀行在現金卡市場競爭白熱化，為搶佔市場佔有率衝刺發卡量，而放寛授信標準，簡化作業流程，使發卡量每年以驚人速度成長。但相對的結果也是逾期放款逐年上升，造成銀行的負擔，甚至有銀行宣佈退出現金卡的市場。 本論文主要在探究現金卡發生逾期情形之持卡人特徵，是根據某銀行之內部資料，針對現金卡客戶資料篩選分析，從中歸納出影響客戶信用風險的重要因子，並以其他客戶資料為實證樣本加以驗證；透過Logistic Regression 統計分析，找出影響客戶違約繳款之重要因素，提供銀行經營管理及風險控管之參考，進而強化銀行整體經營績效與競爭優勢。 本實證研究發現發現顯著的變數有七個：最近三個月內查詢次數、教育程度、性別、借款人不動產狀況、工作年資、第一次動用天數以及六個月內總還款金額除以總提款金額的比例。其中第一次動用天數以及六個月內總還款金額除以總提款金額的比例並未在其他文獻中發相關結論，是本研究的重要貢獻。 Consumer banking services form primarily profitable activities in most banks, of which cash card service makes up the largest revenues of personal banking. This financial product has some advantages, including high spreads, high efficiency and high returns. Additionally, with the increasing number of holders and using rates year by year, cash card service becomes the most important product and makes a lot of profits for banks. The characters of cash card service are easy application and fast approval. Because of high interest rate, banks aim at their customers whom are not sensitive to it. Since the competition among banks is violent in today’s world, banks loosen credit requirements and simplify operation processes to broaden market share. However, some banks can not manage credit risk or achieve economic scale, they would perhaps face huge deficit or even withdraw from the market of cash card services. In the present study, we want to find the characteristics of slack card holders. The sample data is taken from internal information of a sample bank. We analyze the consumers who use cash cards and find several factors which affect the credit risk. After the analyzing process, we use Logistic Regression statistic method to find out what important factors could lead to customers’ deferred repayment behaviors. Then we can give some significant implications, such as how to run a bank and how to control risk, to help banks strength their performance and competitive advantage. The results of data analysis show that there are seven significant variables, including frequency of credit inquiry by other bank, education levels, gander, the type of housing, working experiences, the days between issue day and first loan day, and the ratio of total payment in six month to total wiredraw in six month. Furthermore, the effects of two variables, the days between issue day and first loan day, and the ratio of total payment in six month to total wirthdraw in six month, are not found in other studies, so they are very substantial distributions in this study. |
