Tang Xianxin

(Construction Bank of Hunan branch of Chinese Tieyin branch, Hunan Changsha 410001)

 

This paper analyzesThe problem of credit risk in the development ofIndividual AutomobileCredit in our commercial banking, thenConstructS the quantified management model of the credit risk of individualAutomobileConsumer credit, such as theSelection of parameters,Used standard deviation and VAR to measureThe credit risk of consumer credit, and then make an growth analysis, in order toProvide reference forRisk management ofIndividual ConsumerCredit

Key words: indvidual automobile consumer credit, risk management, quantified management model

CLC number: F830.571 document code: A article number: 1671-8089 (2009) 07-0024-04

One, foreword

Entered in 2009, in order to overcome the weakness of the global economic crisis and the domestic economic downturn, and maintain sustained economic growth, the Chinese government began to promote the automobile consumption as a major economic policy of automobile consumption, but also cannot do without the automobile consumption credit. The financial institutions of the consumer credit business development time is not long, although the service not many varieties, but rapid growth. In the automobile consumption credit as an example, in 2001 the national automobile consumption credit balance of 43600000000 yuan; 2002 automobile consumption credit balance reached 94500000000 yuan, as of 2004 6 at the end of the car consumption loans of financial institutions is 183300000000 yuan, accounting for 10.2 of the total loan balance of financial institutions, to become second only to personal housing mortgage loans to the most important consumer credit varieties. Consider the following reasons, is expected in the future for a long period of time, if the market is to the healthy operation, the automobile consumption credit market China will also continues to accelerate the development of the situation. First, the national income will continue to maintain a rapid growth, car consumption to 10%-25% annual growth rate, 2009 Chinese will become the world's largest automobile consumer countries. Second, China population continues to grow, new consumer groups lack savings strength but there is huge potential demand. Third, at present Chinese car sales, a maximum of only 10% to 15% relates to the automobile credit, while the proportion of the global market for an average of 70%, which American market the highest proportion is 80% to 85%, Germany 70%, India is 60% to 70%.

In the face of such a huge market space, face the reality and the future market demand and the automobile consumption credit development gap, we can not help asking: what hinders the development China automobile consumption credit market risk is risk?! for auto consumption credit market analysis in economics theory, deep study on the cause of the problem, explore solutions, has important theoretical and realistic significance to the development of China's automobile consumption credit market.

The reason for the automobile consumption credit risk produces, different scholars put forward many opinions: Shi Chungui (1997), Zhao Wenyi (2000) analysis of consumer credit risk arising from the debt paying ability, consumer behavior, consumer credit market three kinds of uncertainty theory; Gu Wei (2000), Ren Jinzheng ((2004) from the market perspective that information asymmetry is the source of consumer loan credit risks; Ao Huicheng (2002), Heng Bing (2004) mainly from the perspective of commercial banks, think not mature individual credit environment has become China at present the development of consumer credit system. For auto consumption credit risk solutions, different scholars have put forward the following opinions: Han Xinming (2004 ), Heng Bing (2004) from three aspects to establish credit mechanism, strengthening the construction of commercial operation of the personal credit law and commercial banks to establish an internal bank personal credit system to establish the personal credit system, promote the automobile consumption credit development are discussed; Xu Guang Zhe (2000), Liu Qing (2004), Zhang Mengcheng (2004) proposed that shared risk, car dealers, insurance companies and banks share risk and strengthen the internal management of insurance companies; Liu Yinfeng (2000) to promote the development of [1] automobile consumption credit market our country puts forward perfect personal credit system, perfect the laws and regulations, and other government departments to take corresponding measures etc.. These of the existing research provides the theoretical basis and research methods for the paper, and has the inspiration of research ideas, but still in some aspects of the problem:

1, about the research object of automobile consumption credit market, most of them just focus on the credit side (commercial banks) and the receiver (consumer) relationship problems, while ignoring the and function of insurance companies and car dealers in the market position.

2, the analysis methods are based on logical analysis, but due to the analysis of the market when the market segmentation, the isolation of a part of the market, resulting in analyzing the intrinsic logic is not strong, but most of the focus of the article on the description of the problem or the problem of lack of analytical solution, the important issues.

3, in the solution, most of the problem is China's personal credit system is not perfect, but no other equally important reason? And, to establish a personal credit system is the need of time, but we can wait until after the establishment of a complete personal credit system to develop the consumption credit?

Therefore, this paper tries to make the automobile consumption credit market as a whole to consider, the analysis focus on the problem, efforts to tap the deep-seated reasons behind the phenomenon, the risk as the main line to analyze problems, not only to make the long-term mechanism to solve the problem, but also to explore the feasibility of the present conditions to alleviate the problem the.

Two, the commercial bank credit risk in automobile

Automobile consumption credit risk is refers to the consumer (borrowers) risks are not about to perform according to the automobile consumer credit contract, here "not to perform" is not due for repayment, not including early repayment. This study is the risk of traffic, is also the risk of a automobile consumption credit business, or all risk all business in some period of time. Different aspects of auto consumption credit risk source in internal market, outside the market. The macro economic environment, market structure, market operation mode, the behavior of the market main body and other factors may have a corresponding risk. Specifically, the automobile consumption credit risk include the following aspects:

1, the trustee solvency risk. The trustee solvency risk refers to the trustee in obtaining the automobile consumption credit, due to the change of the trustee's living environment, the reality and the loan application before the expected deviation, which can guarantee lower truthfully performance solvency, which could not repay the loan by loan contract. The trustee solvency risk has the following basic characteristics: first, the trustee in obtaining loans before according to the reasonable expectations is the ability to perform here, eliminate Piandai behavior originally will not have the ability to perform; second, the trustee for breach of contract is already insolvent, excluding the trustee's ability don't go as the situation; third, the trustee to lose this case solvency has in obtaining loans. [2]

The trustee solvency risk is rooted in the external market factors, is a kind of external market risk. At the same time, the trustee solvency risk is the risk management of risk, after signing. As the saying goes "day unexpected situation, people have good and bad fortune". Some common risk trustee of automobile consumption credit market are the following: the trustee's personal safety, or the safety of life; trustee labor ability, namely health issues; employment or possible unemployment risk; commercial failure risk; standard car collision. Therefore suffer losses. When the trustee on the external risk is less than or equal to the trustee self bearing capacity, external risk would not have to credit, commercial banks to overflow, the trustee bear all the risk, the external risk has not formed the market of consumer credit risk; but when a number of external risks more than by the A letter bearing capacity, the excess will spill over to the creditor, the external risk into the market in the consumer credit risk. We can know, the trustee solvency risk is also a kind of uncontrollable risk.

2, the trustee credit risk. By letter of credit risk refers to as the trustee credit is low, resulting in not due or not to fulfill the risk of the loan contract. Considering the trustee different mental attitude, can be divided into the following two situations: first, part of the trustee credit consciousness, not fully consider their own economic strength and the expected debt paying ability in applying for loans before, have a "first loan, to repay. To say" psychology. To apply for bank loans, to the time, do not have the ability to repay the loan, resulting in the credit risk, we can call the negligence of credit risk; second, the trustee in very small amounts in the loan application before the malicious Piandai psychological, when applying for loans without ever wanted to repay the loan, in order to even the use of false personal data to obtain loans to cheat, we can call the fault of credit risk.

Negligence credit risk is different from the trustee solvency risk said in front, the trustee solvency risk in credit management, is a kind of risk, the credit, commercial banks is not controllable risk; but the fault of credit risk in credit granting process, is a kind of ex ante risk, for credit is a credit prior to take some measures to control the risk. At the same time, negligence of credit risk and risk the trustee solvency have in common: two are lack of the ability to repay the debt.

3, the decline in car prices brought about by the auto consumption credit risk. In the car price, although the price Chinese again and again, but the car is far from falling into place, the current domestic car prices are still higher than the international market. According to statistics, the total output of FAW, Dongfeng, SAIC three big automobile group in 2002 1852500, profits of $2330000000; and the General Motors Corporation in 2000 car total output is 8235000, is 3.44 times as big three auto group's total output, but only to achieve the profit of $4452000000, 91% higher than China three car companies, sales profit rate of only 2.4%. If the domestic car prices with the international market prices, then the next time the car market will have a significant price reduction.

From the macro perspective, expand the introduction and improvement of production technology, automobile automobile industry policy changes, the consumer market has brought the rapid growth of China's automobile production, only 1-6 months of 2007 as an example, China's total sales of 2677100 vehicles and 2553600, year-on-year growth of 27.1% and 24.15% respectively. Among them, the car of cumulative sales of 1246100 vehicles and 1132000, year-on-year growth of 36.37% and 31.59% respectively. Output growth with the increase of import policies of automobile is relaxed import vehicle, car prices become an inevitable.

From the micro perspective, some auto makers consider from angle of marketing strategy, in the just introduced a new car, set high prices, to obtain higher bicycle profit, when the test market phase or other competitive models after the listing, immediately greatly reduce the price of the car, to occupy the market. This kind of behavior, from manufacturers perspective is no ground for blame, but brought instability factors of automobile consumption credit market.

The decline in car prices may cause some consumers to pay future loan amount higher than the current price to buy a new car. Such circumstances, consumers will consider whether there is necessary to repay the remaining loan, resulting in the default risk of credit.

4, market interest rates for auto consumption credit risk. Market interest rate as an important automobile consumption credit market exogenous variables, by changing the utility function and the payment function, the letter produces risk, the risk first borne by the trustee, once the amount of risk beyond a certain point, breach of contract has become a rational choice of the trustee, the ultimate expression of auto consumption credit risk. The risk of commercial banks is not controllable risk.

Malicious behavior of 5, car dealers make credit risk increases. The vast majority of automobile dealers in the course of business to focus only on their own sales, seldom consider how to reduce the consumption market risk; minority auto dealers and even with poor credit, does not have the ability to perform in collusion to help people purchase a car, purchase a car for bank loans; a few more car dealers since its establishment with bank fraud purposes, is purely by sell the car for a fraud. As of 2002 November in Shenzhen together using false data for personal automobile consumption loans, involving up to 1100 yuan in economic fraud case is a typical case. The dealer took a few luxury car purchase a car show and some false information to consumers, different bank credit review, very easy to raise a large loan, then left.

The risk for malicious behavior caused by car dealers, banks should strengthen the examination of the qualifications of the seller, for the registered capital less, lack of credit based retailer issued credit more to be extra cautious, prevent illegal vendors to fish in troubled waters. At the same time, in the daily work, the bank can regularly, not on a regular basis has been awarded the credit sellers credit must be evaluated again, strengthen the tracking survey of dealers, the degree of risk, at the same time, the situation changes sellers adjust their credit lines, keep its credit status and enjoy line of credit. [3]

Model three, commercial bank car consumer credit risk management

(a) parameters selection of [4]. This paper is based on a loan contract for example analysis of Credit Metrics J.P. Morgan in the consumer credit risk assessment in. Through the analysis of variable model calculation and model, we hope to dig out the practical value of the method and some simple rules. Because China has not yet established a complete database of credit assets and credit rating system, and the process of marketization of interest rates is also very slow, so it is very difficult in the domestic market to find the corresponding data to calculate. This paper not only analyses, simulations, so as long as we choose to match each other, credit rating and the interest rate and the loan recovery rate data, change trend can reflect the credit risk on it. In this paper, the selected data from the J.P.Morgan "CreditMetricsTM-Technical Document" a book. Whether it is the credit rating, the discount rate, or the loan recovery rate, all is according to the historical data of 1997 years ago American summed up, can be used for a set of parameter data simulation operation.

1, the credit rating transition matrix. The debtor's credit rating may be due to a credit event and metastasis: favorable credit events can make its next issue credit rating rise; on the contrary, adverse credit events will make the next issue of credit rating, a state of the most extreme is the breach of contract. The debtor's credit rating transfer probability can be expressed with the credit rating transition matrix. Matrix is used as the matrix using J.P. Morgan introduced the credit metrics method in (see Table 1).

Table 1: one-year personal credit rating transition matrix

The initial credit rating	At the end of the year the credit rating transition probability (%)
AAA	AA	A	BBB	BB	B	CCC	Default
AAA	90.81	8.33	0.68	0.06	0.12	0	0	0
AA	0.70	90.65	7.79	0.64	0.06	0.14	0.02	0
A	0.09	2.27	91.05	5.52	0.74	0.26	0.01	0.06
BBB	0.02	0.33	5.95	86.93	5.30	1.17	0.12	0.18
BB	0.03	0.14	0.67	7.73	80.53	8.84	1	1.06
B	0	0.11	0.24	0.43	6.48	83.46	4.07	5.20
CCC	0.22	0	0.22	1.30	2.38	11.24	64.86	19.79

The table of the leftmost column is the initial credit rating of the obligor, the right columns is the probability of an a rating in the next years into other rating. For example, the initial AA credit rating for the debtor, in next year's credit rating to the probability of AAA was 0.70%.

2, the contractual cash flows discount rate. Since the discount rate curve of corporate bonds can be used as bond future cash flow rate, then we can combine the credit rating and the personal consumption credit contract bond, and the discount rate data can be obtained in the same year long term credit rating of corporate bond zero coupon rate curve. With the above use of credit rating transition matrix, corporate bonds are a long-term zero coupon yield curve we also use various credit rating by J.P. Morgan in the book of the data (see Table 2).

Table 2: the credit rating of corporate bonds a long-term zero coupon yield curve data (%)

Credit rating	Due within one year	The end of the two years	The end of the three years	The end of the four years
AAA	3.60	4.17	4.73	5.12
AA	3.65	4.22	4.78	5.17
A	3.72	4.32	4.93	5.32
BBB	4.10	4.67	5.25	5.63
BB	5.55	6.02	6.78	7.27
B	6.05	7.02	8.03	8.52
CCC	15.05	15.02	14.03	13.52

3, the loan recovery rate. If the debtor defaults, the loan will not generate commitment owing on the loan cash flow, rate and asset recovery loan value or may recover the value depends on the loan priority class. Different priority classes, loan recovery in the event of default rate is different; the priority level is high, recovery of loans default by loan amount calculation rate is high. The data in table 3.

Table 3: the loan recovery rate (% by value)

Priority level	The mean recovery rate	The recovery rate of standard deviation
Secured priority	53.80	26.86
Unsecured priority	51.13	25.45
Secured subordinated class	38.52	23.81
After the compensation level	32.74	20.18
Junior subordinated class	17.09	10.90

(two) extend the analysis of credit risk measurement. We use a specific car loan contract as an example to analyze the influence in the process of calculation of some parameters on the credit risk evaluation, which affect the final level of risk. This paper only analyze the influence of initial credit ratings and repayment.

1, the influence of initial credit rating of credit risk. The initial credit ratings of different borrowers will directly affect the operation of a year of mean value and variance of loan contract value, which leads to changes in the loan risk. According to the general common sense inference, and credit rating high debtor signed the loan contract risk are generally lower than those with low credit ratings to sign the contract. Here we can be calculated by this conclusion. We assume that the initial credit rating of the debtor is AA, so if we assume that the initial credit ratings for BBB, other conditions remain unchanged, then the calculation of the loan at the end of the year the mean value and the standard value of the data as in table 4:

Table 4: BBB loan contract value of VaR loan to value the required probability and at the end of the year

At the end of a credit rating	Probability (%)	Loan to value at the end of the year (yuan)	At the end of a credit rating	Probability (%)	Loan to value at the end of the year (yuan)
AAA	0.02	54319.62	BB	5.30	52389.54
AA	0.33	54270.34	B	1.17	51399.61
A	5.95	54142.33	CCC	0.12	46312.06
BBB	86.93	53821.56	Default	0.18	25565

In this case the calculated =53678.12, σ =1291.68, then the normal distribution, 5% VaR (expected value) = 2131.27; 1% VaR (expected value) =3009.61. Obviously, with low credit ratings of the debtor to sign the loan contract, risk is relatively high, the high level is acceptable context not bank depends on the bank's own situation. Of course in high risk cases, banks can require the debtor to increase mortgage, risk control and management.

Comparison of 2 different ways of repayment of credit risk, the. The loan contract signed in the bank and the debtor, the debtor may choose different repayment. For example Chinese bank's website lists two repayment methods: matching principal repayment law and matching principal repayment law. Different repayment methods will also be on the loan credit risk -- the relative VaR values -- influence. We next to relative to VaR in the matching principal repayment law of value analysis. [5]

If the debtor or repayment at the end of each year, the repayment but according to matching principal repayment law, all the other assumptions are the same, then the loan contract credit risk will have what kind of change? First we calculate in this condition, calculation formula of average annual amount of A as follows:

We first according to the above formula can be calculated for each year of service payments:

 

 

 

Based on other assumptions and parameters are unchanged, we can use the credit rating transition matrix and the discount rate and the data in table 5 to calculate the matching principal repayment law under the VaR value.

Table 5: AA level and the calculation of the matching principal repayment law under the VaR value data needed

At the end of a credit rating	Probability (%)	Loan to value at the end of the year (yuan)	At the end of a credit rating	Probability (%)	Loan to value at the end of the year (yuan)
AAA	0.70	54274.19	BB	0.06	52450.72
AA	90.65	54227.54	B	0.14	51521.89
A	7.79	54107.7	CCC	0.02	46633.91
BBB	0.64	53802.82	Default	0	25565

On the table can be found at the end of the year the average loan to value: Mu = 54209.44, standard deviation σ = 160.11.

Then in the normal distribution:

 

Through this analysis, we can see that the matching principal repayment methods, banks in the level of confidence level, VaR value is relatively small, relatively smaller potential loss. It can properly relaxed some of the loan contract decision and loan conditions.

Three, the conclusion

The method of comprehensive analysis, Credit Metrics Based on VaR theory as the basis, based on the credit rating; and in all the company of the same level with the same default rate and the actual default rate is equal to the historical average default rate assumption. We use simulation to get a more reasonable result. Therefore, the method is applicable more generally, calculation method is not complicated, with certain maneuverability, is a can be used in bank credit risk control system tool. So as to realize the transformation of a loan from the loan classification rating management to specific accurately measurement of contract risk of loss, provides a new tool and idea for consumer credit risk management of commercial bank. But based on the personal credit loan credit rating, as the index analysis is a large and complex problem, this paper simply presents a general property indexes, this may cause the shadow AID on rating results; this paper gives the individual credit quota to be further tested.

However, from the reality urgency of view, although the traditional credit risk measurement tools and risk management systems are still being most banks to adopt, is the main tool of risk management; but with the development of financial market, commercial banks are facing more and more unexpected risks, credit risk has played a very important role. At the same time, the Commercial Bank of our country is also facing the huge potential credit risks, risk taking ability is not strong, the automobile consumption credit market is in a period of rapid growth. The metric uses the risk quantification techniques to enhance the risk control ability of commercial banks be imperative, but China's current situation, but also improve and strengthen the construction of many aspects of.

Reference.

[1] Wang Limin. Risk analysis and prevention of consumer credit business. Modern finance, 2005; 10:22-23

[2] car Hui. China's auto consumption credit risk management research. Modernization of shopping malls, 2006; 15 : 6-7

[3] Chen Jie. Risk analysis of consumer credit business and strategy. The financial economy, 2006; 08.56-59

[4] J.P. Morgan.Credit Metrics TM-Technical Document.New York, 1997.26- 27

[5] Peng Zuzeng. Fuzzy mathematics and its applications. Wuhan: Wuhan University press, 2002. 143

 

Author introduction: Tang Xianxin (1973 -), male, Han, Hunan Province, Hengyang, economist Chinese Construction Bank Hunan Province, Changsha Iron Silver Branch Department of real estate credit (Personal Loan Center Project Manager), master, research direction for management.