小微企业信用贷款风险控制问题研究

随着我国社会主义市场经济的发展,小微企业数量不断增加,在促进就业、推动社会进步方面发挥了十分重要的作用。由于小微企业发展规模比较小,流动资金少,为了维持自身正常发展,小微企业需要进行贷款。就目前而言,很多小微企业存在信用贷款风险,严重限制了小微企业的长远发展。因此,本文主要针对小微企业信用贷款风险控制问题展开论述。

对银行小微企业信用贷款风险控制的探讨

小微企业是我国现如今存在的经济主体中规模最小的个体,主要作用为促进国家经济发展质量的提升,且有助于促进科技以及就业创新脚步的加快。其中,相对其他中小企业而言,小微企业存在相对规模较小、经营缺乏稳定性、信用较低等特点,出现信用贷款风险的可能性相对较大,因此,有必要对其进行较为深入的研究,进而探寻出多种有效策略,提升银行小微企业的信用贷款风险控制质量。

国有银行小微企业信用贷款风险管理研究

小微企业因为规模小、稳定性差、生产经营不规范等特点,在开展银行信贷业务时容易引发高风险的问题。因此,国有银行为实现各项业务的良性、稳定的发展,有必加强对小微企业信用贷款风险的管理,只有这样才能降低信用贷款的风险,真正帮助小微企业得到健康、长久地发展。

商业银行信贷风险控制管理研究

研究对商业银行如何提高信用资金的管理能力和加强信用贷款风险的防范措施，为促进商业银行和企业持续、健康、稳定的发展具有重大现实意义。从事前控制、事中控制、事后控制三个角度对商业银行信用贷款风险进行分析和评价，并提出控制贷款风险的有效途径及防范信用贷款风险相应的对策措施。

Credit Risk Transfer and the Performance of Commercial Banks --Based on the Panel Data

Based on the panel data, we analyze the US commercial banks＇ CRT. According to the study, we find that the introduction of CRT will increase the level of banks＇ liquid risk. The performance of bank mainly is that its supervision and review of risk will drop, based on the impact of asymmetric information, commercial Banks transfer the bad loans to investors. Through the analysis we can see that after the transfer of credit risk in commercial bank did not increase income and reduce risk. Because commercial Banks can extend more bad loans to expand its lending scale, and bad loans will increase the bank overall risk.

Credit Risk Transfer in SME Loan Guarantee Networks

Joint loan guarantee contracts and mutual guarantee contracts among SMEs form the basis of SME guarantee networks. The expansion of these networks increases the fragility of a financial system as a result of the regional and industrial risk contagion embedded within them. By providing a theoretical framework of a loan guarantee network, a method is proposed for calculating the amount of risk spillover caused by loan guarantees taking the perspective of the entire network. In addition,the route of risk contagion in guarantee networks is analyzed, revealing that when default risk shocks occur, risk contagion travels along the nodes not once but for several rounds and that the risk control of one firm cannot prevent these systemic risks. Therefore, a risk control scheme is designed based on the location and importance of firms in the network. Using data from a real guarantee network,we demonstrate that identifying the node locations of firms' in the guarantee network(including the coritivity and closeness of the firm) can help in understanding risk contagion mechanisms and preventing systemic credit risk before a crisis occurs.