Full metadata record
DC Field | Value | Language |
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dc.contributor.author | 鄭欽文 | en_US |
dc.contributor.author | Chin-Wen Cheng | en_US |
dc.contributor.author | 許和鈞 | en_US |
dc.contributor.author | Her-Jiun Sheu | en_US |
dc.date.accessioned | 2014-12-12T02:59:06Z | - |
dc.date.available | 2014-12-12T02:59:06Z | - |
dc.date.issued | 2005 | en_US |
dc.identifier.uri | http://140.113.39.130/cdrfb3/record/nctu/#GT009337527 | en_US |
dc.identifier.uri | http://hdl.handle.net/11536/79657 | - |
dc.description.abstract | 由於國內現金卡使用日漸普及,而發卡銀行為提高現金卡市場佔有率,通常採取較寬鬆的審核方式與簡化核發現金卡的流程,來衝刺發卡量以達預定業績目標。此舉已嚴重影響發卡銀行的授信品質,導致催收款增加,呆帳損失風險因而逐年提高。因此,如何在衝刺發卡量的前提,同時做好預先防範呆帳損失風險發生,仍是發卡銀行極待克服的課題,而現金卡信用風險審核標準與風險評估模型的建立,將有助於發卡銀行解決相關問題。 今年爆發雙卡風暴以來,現金卡一下子從銀行爭相發行的金雞母變成人人喊打的過街老鼠。如何配合現金卡原有之授信風險分散效果,同時建立一套健全的現金卡授信評估模式,以最小的營業成本、最便捷的核卡速度,又能在降低呆帳損失的先決條件下,達到增加經營利潤的結果,是本研究的最終目標。 綜觀國內以往授信評估相關研究,大多著重於迴歸分析法、區別分析法、Probit 迴歸模式…等統計方法,主要是利用過去企業金融相關的財務變數來建構授信評估模型,而這些模型所建構出來的企業信用評等表,並無法滿足銀行從事現金卡放款的實際需求。本研究以銀行第一線授信人員的立場,透過銀行實務界的看法,並藉由層級分析法(簡稱AHP)來分析銀行從事現金卡授信決策時所考量之因素,以建立授信決策之評估準則,以期能更符合銀行在從事現金卡授信決策的實際需求。 本文之研究,在資料收集方面係以萬泰銀行的12家分行為對象,針對該行內現金卡之授信人員進行問卷調查。經與該發卡銀行授信、放款部門之授信人員深入訪談後,發現信用卡繳款紀錄是最被重視的審核要素,顯示辦卡人的過去繳款習慣仍是現金卡授信人員審核的重點考量項目,而高居第二重要的審核要素則是申辦者的教育程度,這應該是現金卡在沒有徵提擔保品的情況下,台灣的學歷高低仍然是考量還款能力與授信展望的重要依據。而過去許多論文研究結果顯示出不同年齡層的辦卡人,對呆帳率的高低具有高度影響,在本論文經由AHP分析之後卻反而成為最不被授信人員重視的審核要素。 | zh_TW |
dc.description.abstract | In light of increasin ge prospect customers g popularity of cash cards adoption, banks are seen issuing cash cards and encoura to hold multiple cards through relaxed approval and credit reference procedures, simply to attain market shares and making the goal on new issues. However, the above behavior has significantly undermined the creditworthiness of issuing banks, leading to increased outstanding debts, and thus higher risk of bad debts each year. Therefore, how to concurrently manage risk exposure to outstanding bad debts while augmenting new card issues remains a missing piece from the puzzle for banks. An audit system and risk evaluation model, therefore, may simply help the banks to solve this puzzle . Ever since the outburst of the twin cards tornado, cash cards is transforming from cash cow to a trouble maker..The purpose of this study is to provide a whole completed set of lending valuation model in which the main features of cash cards are incorporated and lending risks are diversified. Among the main features are: providing the smallest operation cost and the fastest approving speed, reducing the loss of slack cards and increasing operating profits. We have seen that most of the domestic research on credit endorsement are focusing on Logistic Regression、Regression. Analysis、Discriminate Analysis、Probit Regression model , etc . on the early stage. For Logistic Regression、Regression. Analysis、Discriminate Analysis、Probit Regression model , and so on . Statistics methods are targeting on assessing corporate credit built by financial variables, this can only provide a credit endorser an unilateral evaluation. Nonetheless, it could not provide a bank a precise reference for decision making during credit endorsement. This research reports the results of business loan process by the bank where the Factor Analysis Method , Analytic Hierarchy Process (AHP) technique were employed to evaluate the business loan . This research is based on 12 credit cards issuing banks. Target surveys have also been conducted among the cash cards endorser in these 12 banks. Credit card payment is the most concerned factor after the aforementioned surveys. The second most influential factor in credit cards endorsement is the applicant’s educational background. Prior to the imposition of applicant’s collateral, educational background was still one of the most concerned factors in assessing one’s payment ability in Taiwan. Many researches in the past have shown that applicants’ age may impact the level of bad debt significantly. However, credit endorser concerns less about the applicant’s age in this research . | en_US |
dc.language.iso | zh_TW | en_US |
dc.subject | 迴歸分析法 | zh_TW |
dc.subject | 區別分析法 | zh_TW |
dc.subject | Probit 迴歸模型 | zh_TW |
dc.subject | 因素分析法 | zh_TW |
dc.subject | 層級分析法 | zh_TW |
dc.subject | Regression Analysis | en_US |
dc.subject | Discriminate Analysis | en_US |
dc.subject | Probit Regression | en_US |
dc.subject | Factor Analysis Method | en_US |
dc.subject | Analytic Hierarchy Process | en_US |
dc.title | 現金卡風險要素評估─以萬泰銀行為例 | zh_TW |
dc.title | A factor evaluation model of risk exposure to the issue of cash cards - an example of Cosmos Bank | en_US |
dc.type | Thesis | en_US |
dc.contributor.department | 經營管理研究所 | zh_TW |
Appears in Collections: | Thesis |