四川灾后农房重建贷款信用风险评价与管理研究
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摘要
“5.12”汶川大地震可谓新中国成立以来破坏性最强、波及范围最广、救灾难度最大的一次地震,造成了大量农房的倒塌、基础设施的破坏。农民的生产生活受到了极大影响,农民赖以生存的生产资源被破坏,借以居住的房屋被毁灭,特别是在基础设施落后的贫困山区,而收入的限制更严重制约着灾后恢复性重建。在灾后重建的“万米长跑”中,农房重建已被纳入民生的首要环节。为积极支持灾后农房重建工作,金融机构,尤其是作为农村金融主体的农村信用社,挑起了灾后农房重建的支撑大梁,抗震救灾专项贷款的开展极大地促进了农房重建工作。但由于抗震救灾专项信贷具有较强的准财政性质,对于本身历史包袱就较为沉重的农村信用社来讲无疑不利于其可持续发展经营。为此,科学划分受贷农户信用信息,衡量农房重建贷款风险,对金融机构专项贷款风险管理具有积极的指导意义。
本文在综合国内外农户信用风险评价与风险管理理论的基础上,通过对四川省5个重灾区县384户受贷农户、10个金融机构的调查数据,采用模糊聚类分析对各区县农户进行了信用信息分类研究；同时对贷款本身的操作风险和担保风险进行了识别；紧接着在信用分类的基础上,对农房重建贷款风险管理进行了研究并提出了相关的管理建议。本文通过这几部分的研究得出了以下几个结论：
(1)农房重建贷款补充了巨灾金融理论。农房重建贷款是地震灾后为支持灾区农户生活生产设施重建所创新的专项信贷产品,从产品形式创新、外部供给机制探索、风险管理方面丰富了金融服务体系的内涵,补充了巨灾金融理论。
(2)农户信用风险较低。地震灾区农户由于所处经济环境、自身创收能力等不同,金融机构面临的信用风险大小也不同。但归因于对口援建导致的用信环境改善、产业发展导致收入增加以及灾区感恩之心的良性引导,地震灾区农房重建贷款农户信用风险较低。
(3)操作风险和担保风险诱发农户信用风险的可能性较高。从实际研究结果来看,金融机构在特种贷款上因操作混乱造成的经营风险高于农户信用损失风险；同时,从政府担保资金的运作来看,担保资金不足造成的风险敞口也较信用风险大。
(4)不健全的制度成信用风险主因。灾后农房重建贷款风险产生主因归结于金融机构内部管理制度的不健全,内部缺乏对信贷人员不按章操作的处罚管理制度,导致贷款道德风险发生机率的增大；政府担保资金使用制度的滞后更加剧了到期坏账造成的损失风险。
在以上研究结论的基础上,本研究认为农房重建贷款信用风险管理要做好以下几个方面的工作：(1)创新农房重建贷款信用风险管理模式；(2)规范农房重建贷款操作流程；(3)创建农户信用信息动态监测机制；(4)健全金融机构内控机制；(5)健全贷款信用风险补偿机制；(6)改善信用贷款发放环境。
"5.12"Wenchuan earthquake could be described as the most devastating disaste since the founding of new China, causing the collapse of a large number of rural housing, production and living of farmers had been greatly Impact. The productive resources and houses were destroyed, especially in the poor mountainous areas, income limits restricting the recovery of reconstruction. In the post-disaster reconstruction "meters long-distance running", the rural housing reconstruction had been incorporated into the most important part of people's livelihood. Catastrophe a test of people's will and strength, but also a test of the financial system to cope. To actively support the post-disaster reconstruction of rural housing, financial institutions, especially as the subject of rural credit cooperatives, played an key role in the rural housing reconstruction after the disaster, special loans to carry out had greatly promoted the rural housing reconstruction. However, due to the special relief of credit with a strong quasi-fiscal nature, and for its heavy historical burden, the loans were undoubtedly bad for sustainable development of Rural Credit Cooperatives. Then, the scientific division of credit information by credit farmers, measuring the risk of rural housing reconstructio loans, had a positive significance to financial institutions risk management.
Based on the theory of credit risk assessment and risk management, through the survey data in 5 cunties of Sichuan Province,384 farmers, and 10 financial institutions, the paper attempted to use the method of Fuzzy Matrix analysis for each county farmers to classify credit information; the same time, tried to identify the management risk and security risk of itself; followed in the classification, the paper had studied the risk management of loans for rural housing reconstruction and put forward some related management proposals. Through these parts, the study reached the following conclusions:
(a) The rural housing reconstruction loan Complemented the financial catastrophe theory. Rural housing reconstruction loan was a special innovative credit product which aims to support reconstruction after the earthquake disaster. The product enriched the connotation of the financial service system to supplement the financial catastrophe theory from product form of innovation, exploring the external supply mechanism, risk management.
(b) Household credit risk was low. Due to the different economic environment, and their income-generating ability, financial institutions face different risk. Because of angelica aided by their counterparts resulting in better credit environment, industrial development has led to increased revenue and positive gratitude disaster guide, rural housing reconstruction loans have lower credit risk.
(c) The risk ranged from management and was higher than credit risk. Basing on the survey, the financial institutions confusion operating in special loans may cause the higher loss of business risk than credit risk households; the same time, from the operation of government guarantee funds, the lack of guarantee funds had more exposure than credit risks.
(d) The main reason for credit risk was the lag of management system. Risk of post-disaster reconstruction loans generated was due to the internal management system of financial institutions was not perfect. Internal lack of credit officers were not punished by chapter operations management system, resulting in a loan increases the probability of moral hazard; government guarantee behind the use of funds was exacerbated by the system due risk of bad debt losses.
Based on the conclusions of the study, this study suggested that to management of the credit risk, the financial institutions must do the following several aspects:a) Innovation the credit risk management mode of rural housing reconstruction loans; b) specification the operation process of rural housing reconstruction loans; c) created Dynamic monitoring mechanism for farmers credit information; d) sound financial institutions, internal control mechanisms; e) sound loan credit risk compensation mechanism; f) improve the credit loan environment.
本文在综合国内外农户信用风险评价与风险管理理论的基础上,通过对四川省5个重灾区县384户受贷农户、10个金融机构的调查数据,采用模糊聚类分析对各区县农户进行了信用信息分类研究；同时对贷款本身的操作风险和担保风险进行了识别；紧接着在信用分类的基础上,对农房重建贷款风险管理进行了研究并提出了相关的管理建议。本文通过这几部分的研究得出了以下几个结论：
(1)农房重建贷款补充了巨灾金融理论。农房重建贷款是地震灾后为支持灾区农户生活生产设施重建所创新的专项信贷产品,从产品形式创新、外部供给机制探索、风险管理方面丰富了金融服务体系的内涵,补充了巨灾金融理论。
(2)农户信用风险较低。地震灾区农户由于所处经济环境、自身创收能力等不同,金融机构面临的信用风险大小也不同。但归因于对口援建导致的用信环境改善、产业发展导致收入增加以及灾区感恩之心的良性引导,地震灾区农房重建贷款农户信用风险较低。
(3)操作风险和担保风险诱发农户信用风险的可能性较高。从实际研究结果来看,金融机构在特种贷款上因操作混乱造成的经营风险高于农户信用损失风险；同时,从政府担保资金的运作来看,担保资金不足造成的风险敞口也较信用风险大。
(4)不健全的制度成信用风险主因。灾后农房重建贷款风险产生主因归结于金融机构内部管理制度的不健全,内部缺乏对信贷人员不按章操作的处罚管理制度,导致贷款道德风险发生机率的增大；政府担保资金使用制度的滞后更加剧了到期坏账造成的损失风险。
在以上研究结论的基础上,本研究认为农房重建贷款信用风险管理要做好以下几个方面的工作：(1)创新农房重建贷款信用风险管理模式；(2)规范农房重建贷款操作流程；(3)创建农户信用信息动态监测机制；(4)健全金融机构内控机制；(5)健全贷款信用风险补偿机制；(6)改善信用贷款发放环境。
"5.12"Wenchuan earthquake could be described as the most devastating disaste since the founding of new China, causing the collapse of a large number of rural housing, production and living of farmers had been greatly Impact. The productive resources and houses were destroyed, especially in the poor mountainous areas, income limits restricting the recovery of reconstruction. In the post-disaster reconstruction "meters long-distance running", the rural housing reconstruction had been incorporated into the most important part of people's livelihood. Catastrophe a test of people's will and strength, but also a test of the financial system to cope. To actively support the post-disaster reconstruction of rural housing, financial institutions, especially as the subject of rural credit cooperatives, played an key role in the rural housing reconstruction after the disaster, special loans to carry out had greatly promoted the rural housing reconstruction. However, due to the special relief of credit with a strong quasi-fiscal nature, and for its heavy historical burden, the loans were undoubtedly bad for sustainable development of Rural Credit Cooperatives. Then, the scientific division of credit information by credit farmers, measuring the risk of rural housing reconstructio loans, had a positive significance to financial institutions risk management.
Based on the theory of credit risk assessment and risk management, through the survey data in 5 cunties of Sichuan Province,384 farmers, and 10 financial institutions, the paper attempted to use the method of Fuzzy Matrix analysis for each county farmers to classify credit information; the same time, tried to identify the management risk and security risk of itself; followed in the classification, the paper had studied the risk management of loans for rural housing reconstruction and put forward some related management proposals. Through these parts, the study reached the following conclusions:
(a) The rural housing reconstruction loan Complemented the financial catastrophe theory. Rural housing reconstruction loan was a special innovative credit product which aims to support reconstruction after the earthquake disaster. The product enriched the connotation of the financial service system to supplement the financial catastrophe theory from product form of innovation, exploring the external supply mechanism, risk management.
(b) Household credit risk was low. Due to the different economic environment, and their income-generating ability, financial institutions face different risk. Because of angelica aided by their counterparts resulting in better credit environment, industrial development has led to increased revenue and positive gratitude disaster guide, rural housing reconstruction loans have lower credit risk.
(c) The risk ranged from management and was higher than credit risk. Basing on the survey, the financial institutions confusion operating in special loans may cause the higher loss of business risk than credit risk households; the same time, from the operation of government guarantee funds, the lack of guarantee funds had more exposure than credit risks.
(d) The main reason for credit risk was the lag of management system. Risk of post-disaster reconstruction loans generated was due to the internal management system of financial institutions was not perfect. Internal lack of credit officers were not punished by chapter operations management system, resulting in a loan increases the probability of moral hazard; government guarantee behind the use of funds was exacerbated by the system due risk of bad debt losses.
Based on the conclusions of the study, this study suggested that to management of the credit risk, the financial institutions must do the following several aspects:a) Innovation the credit risk management mode of rural housing reconstruction loans; b) specification the operation process of rural housing reconstruction loans; c) created Dynamic monitoring mechanism for farmers credit information; d) sound financial institutions, internal control mechanisms; e) sound loan credit risk compensation mechanism; f) improve the credit loan environment.
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