Abstract
According to the latest statistical data from Ministry of Finance, it is found that domestic consuming loan is growing up continuously these years. Up to the end of September in 2000 the sum of this business is 3984.9 billion. It is equal to 34.1% among loan of native banks. Personal small-scale consumer credit is increasing at 18% rate per year from 148.6 billion in 1994 to 365.1 billion in the end of September in 2000. It is developed vigorously, and even to be the main profit for banks. This is because consumers have slowly changed their concepts about how to use their money. Another reason is that the banks are actively to provide small-scale consumer credit with easy formality. But its potential risk is becoming higher since depression in economy and unemployment are getting higher. ¡§How to do the credit estimation for your consumers; how to make the lost of breaking an appointment lower¡¨ is the most urgent for the banks who would like to have good performance in the field of consuming finance.
This research takes 1764 consumers who have small-scale consumer credit from a specific bank as samples for analysis. We found 29 elements that will affect the payment from literature and credit estimation from other branches. After concluding 6 types of credit risk, 25 influent elements offered by sample bank are listed for the purpose of analysis. ¡§K-W independent check¡¨ and ¡§Spearman¡¦s rho related analysis¡¨ are used to gain 17 variables. They are interactive and remarkable for credit. The summarized introduction of this research is as follows.
1. Age is notable for payment. The risk between ages of 41 ~45 is higher than the average. Seniority around 7 ~10 years is also dangerous. The above appearance is figured out to be concerned about transition of economical environment such as depression in economy and unemployment. The thought ¡§ higher ages or seniority means lower risk¡¨ should be done some amendment.
2. Actual net income should be considered while estimating the credit. Higher income is not necessarily equal to lower risk. People with high income were easily to obtain more loans since they would have better payment capacity. It is observed from credit estimation of each bank. In fact income is unable to reflect payment capacity. Debt will be important reason to influence payment capacity.
3. Having real property doesn¡¦t mean having no risk. We could find that consumer¡¦s property usually took large percentage in credit estimation. Sometimes consumers would become dangerous since they had debt for real property. The banks had better to correct their illusion ¡¨land is wealth¡¨ as soon as possible.
4. More or less guarantees are not essential for credit risk. Simple and fast formality appeals to the popular while the banks are promoting small-scale consumer credit. In the past the banks believed that more guarantees could lower the risk. It is wrong and will be the block in developing business. The banks should focus on payment capacity as main accordance for credit estimation.
Key words: Consumers loan; Credit risk management, Credit scoring system.
| Identifer | oai:union.ndltd.org:NSYSU/oai:NSYSU:etd-0731102-201404 |
| Date | 31 July 2002 |
| Creators | Ho, Kuei-Ching |
| Contributors | Alpha Lowe, I-Hchen Chen, Chin-Kaug Jen, Yuan-Shuh Lii |
| Publisher | NSYSU |
| Source Sets | NSYSU Electronic Thesis and Dissertation Archive |
| Language | Cholon |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0731102-201404 |
| Rights | unrestricted, Copyright information available at source archive |
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