汽車貸款呆帳之授信評估與實際影響因素缺口之內容析 -以最終消費者汽車融資為例

The Analysis of Deficiencies between Credit Appraisal on Car Loan Bad Debt and Factors Affecting Underwriting Policy by Content Analysis Illustration of Car Loan End Consumers

謝 志 行(Chih-Hsing Hsieh)

指導教授 ： 廖淑伶

元智大學/管理學院/管理研究所/碩士(2006年)

摘要

本論文研究之目的為：參考國內外的文獻及其相關資料，加上實務經驗中，認為會是影響汽車貸款授信風險的因素。深入研究目前汽車融資公司所使用的信用評等表，進行內容分析，以汽車融資公司經營汽車貸款業務的特性，依據實際發生呆帳的原因，找出授信原則和信用風險模式未顧及的部份，此一部份為影響放款授信成敗的顯著因素。衡量影響汽車貸款的顯著變數，為汽車融資公司建立專屬的信用風險評估模式，掌控風險，爭取授信審核的時效，提高融資公司的授信品質，兼顧汽車融資公司的服務效率。
本研究係以國內某主要汽車貸款融資公司之北區分公司(北區分的業務區域為新竹以北和宜蘭、花蓮地區)，自民國94年7月1 日到民國94年12月31日為止，共提列433件呆帳案件(提列呆帳金額為$89,775,934)至該汽車融資公司之台灣總公司的帳務回收部門，選取北區分公司在授信時為A Rating (即信用評分為98.0 –100)及B Rating (即信用評分為 91.0 – 97.9)，並且到95年8月31日為止，仍未清償的103件呆帳案件為研究對象。
本研究是藉由內容分析法，以汽車融資公司之呆帳案件為分析標的，針對授信及內容分析法之相關文獻進行探討。由原始申請資料、混合評等與評分表、及法務催收的過程，以內容分析類目來進行編碼，及操作變項定義，本研究變數的選取，分為表內變數及表外變數二部份，表內變數包括：車主填寫的貸款申請書、車主和保證人所提供的財力證明、在職證明、不動產資料，表外變數，則是汽車融資公司內部所訂定的一套審核資料，總計表內變數及表外變數，共選出28個變數。再以SPSS套裝軟體輔助下，進行敘述性統計分析及線性迴歸分析。
本研究結果發現：
一、貸款金額對呆帳金額有顯著差異：
貸款金額越高，則借款戶因為無力付款而違約的機率就越高，發生呆帳的機率也越高，所以貸款金額越高對呆帳金額有顯著差異。
二、是否取回車輛對呆帳金額有顯著差異：
呆帳客戶的車輛若是取回，依照法律程序進行法拍，可清償客戶部份的債務，若呆帳客戶的車輛無法取回，合約的餘額及法律費用均要提列為呆帳，呆帳金額隨之增高，所以是否取回車輛對呆帳金額有顯著差異。

關鍵字

汽車融資公司 ； 汽車貸款 ； 授信原則 ； 信用風險模式 ； 內容分析法

並列摘要

The purpose of this paper is to determine the car loan factors that affect underwriting policy, appraisal practice in the financial services industry based on domestic and international Bibliometrics and other references. Upon the credit evaluation score and the characteristics of motor mortgage business, this paper is to establish the appropriate underwriting policy and risk management model by content analysis for the financing of vehicles. Each parameter that affects the process of credit analysis is to develop professional risk management in order to increase the efficiency of appraisal practice, contract quality as well as the service effectiveness.
The research is based on 433 write-off cases valued NT$89,775,934 outstanding balance at a loss recovery department of the finance house in the Taipei district including Taipei, HsinChu, Hwalien and Ilan from 1st July 2005 to 31st December 2005. From the write-off cases, 103A& B rating cases rated from 91.0 to 100 points are selected as a comparative target of this paper and they have been still outstanding amounts until 31st August 2006.
Write-off cases are the targets of this paper to study and examine the parameters of credit analysis and related articles by content analysis. Original application information, mixed evaluation standard and rating form, the process of delinquent collection are categorized by items of the content analysis as well the definition of operation variables. The 28 variables are divided into inside column variables and outside variables based on an applicant's creditworthiness and capacity, as well as the value of any collateral that are offered to secure the credit. Inside column variables include application forms, financial certificates from owner and guarantors, employment, value of any collateral. Outside column variables are composed of the underwriting policy in a certain finance house. This information is used in descriptive statistic analysis and linear regression analysis.
The results are as bellowed:
1.A clear positive correlation between finance amount and write-off amount. The higher financed amount is the higher write-off amount because of the greater possibility for delinquency.
2.A clear negative correlation between repossession vehicles and write-off amount. A repossessed vehicle is eligible to attend an official auction for loss recovery to decrease the write-off amount. Thus, it is has a great influence on write-off amount if a certain vehicle is unable to turn-in or repossess.

並列關鍵字

Finance House ； Car Loan ； Underwriting Policy ； Risk Model for Credit Management ； Content Analysis

參考文獻

6. 江惠櫻（2001），「商業銀行對企業授信決策考量因素與授信品

25. 黃小玉（1987），「銀行放款信用評估模式之研究－最佳模式

34. 楊孝榮 (1985)，「內容分析 ，社會及行為科學研究法」，第

3. 台北市銀行公會（1995）。台北市銀行公會徵信與授信業務聯繫

融聯合徵信中心編輯委員會。