关于贷款五级分类管理工作的调查与思考

自1998年推行贷款五级分类工作以来,国有商业银行对实施贷款质量五级分类管理制度的认识逐渐提高,防范信贷风险的意识逐渐增强,开展了大量的基础性工作,进行了有益的尝试;但是,银行内部和外部仍然存在诸多制约因素,严重阻碍了五级分类管理工作的顺利推进,不利于客观真实地揭示银行的信贷资产质量.     

浅谈如何推行贷款质量五级分类管理

一、贷款质量五级分类的定义五级分类法是以风险为基础,其任务首先是暴露风险、量化风险,揭示贷款的真实价值。人民银行规定:根据贷款及时、足额回收的可能性,贷款划分为正常、关注、次级、可疑、损失五个不同类别,即"五级分类"。前两类为优良贷款,后三类称为不良贷款。二、目前贷款质量五级分类管理存在的问题从1998年试点到现在全面推行五级分类管理,存在许多问题,主要包括商业银行信贷工作基础管理比较薄弱,贷款的档案资料不全甚至遗失,给分类工作带来了困难。五级分类建立在大量的历史资料和数据分析基础上,对客户信息量的要求不仅是丰富、完善、翔实,而且要求要活、要新,更要动态监测、分析由表及里,由往而今、去伪存真。如果做不到这些,即使信贷员素质再高也不能准确判断五级分类的结果。五级分类由     

对实行贷款质量五级分类管理的思考

贷款五级分类制度是根据内在风险程度将贷款划分为正常、关注、次级、可疑、损失五类，其中后三类合称为不良贷款。这种分类方法主要依据借款人的还款可能性，即最终偿还贷款本金和利息的可能性，确定贷款遭受损失的风险程度，以此来揭示贷款真实价值的过程和结果。     

对做好贷款五级分类管理工作的思考

全面推行贷款五级分类管理办法，是农业银行为进一步提高信贷资产管理水平，适应现代企业管理制度改革的需要，与国际信贷资产管理惯例接轨，向现代商业银行迈进的重要步骤。在具体工作中，如何做好贷款五级分类管理工作呢？我认为应做好以下八个“相结合”：     

贷款五级分类工作的对策

我国各国有商业银行对贷款逐步实行了以风险为基础的五级分类管理.据调查,分类过程中潜伏着风险隐患,制约和影响了贷款分类管理水平,为此建议:     

信息不对称对农村信用社贷款的影响

信息不对称的现象普遍存在于金融市场中,由于对企业信息掌握的不对称给银行发放贷款带来重大的风险隐患,农村信用社的脆弱风险防范体系更加要着重提防信息不对称对信贷发放的负面影响,将由此而带来的信贷风险将至最低成为了农村信用社的迫切需要。     

实施贷款五级分类管理对农信社改革经营的影响

贷款五级分类制度是根据内在风险程度将商业贷款划分为正常、关注、次级、可疑、损失五类。这种分类方法是银行主要依据借款人的还款能力,即最终偿还贷款本金和利息的实际能力,确定贷款遭受损失的风险程度,其中后三类称为不良贷款。此前的贷款四级分类制度是将贷款划分为正常、逾期、呆滞、呆账四类。     

Bank credit risk and structural credit models: Agency and information asymmetry perspectives

This work investigates the effects of agency and information asymmetry issues embedded in structural form credit models on bank credit risk evaluation, using American bank data from 2001 to 2005. Findings show that both the agency problem and information asymmetry significantly cause deviations in the credit risk evaluation of structural form models from agency ratings. Five independent factors explain a deviation of 42.6–78.3% and should be incorporated into future credit risk modeling. Additionally, both the effects of information asymmetry and debt-equity agency positively relate to the deviation while that of management-equity agency relates to it negatively.     

Institutional ownership and credit spreads: An information asymmetry perspective

Recent literature has documented a link between institutional equity ownership (IO) and cost of debt capital, and interpreted it as a corporate governance effect. However, institutional equity investors may also affect cost of debt through their influence on information asymmetry condition of firms. To distinguish between the two effects, we break down institutional investors into different groups: transient institutional investors (TRA who are sensitive to information asymmetry but unlikely to participate in corporate governance, and the dedicated ones (DED) who act oppositely. Based on a most up-to-date and comprehensive bond data spanning the past 20 years, we find that credit spreads narrow (widen) with an increase in equity ownership by TRA (DED). The effects are most prominent among short-term bonds, bonds with lower ratings, higher leverage and higher volatilities. The results persist after controlling for potential endogeneity and other information asymmetry measures, and are unlikely due to an asset substitution effect. Overall, our findings provide strong support for the effect of information asymmetry on credit spread, and highlight the importance of distinguishing various types of institutional investors.     

征信体系建设与商业银行信用风险管理

征信体系是社会信用体系的核心,也是现代金融体系运行和稳定的基石,征信体系健全与否将直接影响金融机构的风险控制水平。商业银行作为经营货币和风险的特殊企业,在目前我国征信体系尚不完善的情况下,承担了大部分的信用缺失成本,对建立完善的社会征信体系的需求更为迫切。     

基层人行计算机信息安全管理的短板剖析与矫正

自2005年开始，人民银行信息化建设全面提速，项目建设力度加大，数据集中快速推进，客观上需要高度重视和深入研究计算机信息安全问题。作为市县两级人民银行，既是人民银行组织体系中最基层的分支机构，也是新形势下维护和确保计算机信息安全的前沿阵地和薄弱环节。因此，如何加强和保障计算机信息安全，对基层人行来说比以往任何时候更显得重要和突出。     

维护征信信息准确性防范征信信息失真

市场经济在某种意义上是契约经济,诚信是契约的灵魂,是市场经济的基石.随着我国市场经济的进一步发展,诚信对人们的生活,特别是商事活动的影响随处存在,个人信息作为诚信的载体也日益受到人们的重视.     

非银行信用信息采集中的问题及其建议

非银行信用信息采集是信用管理和信用服务的重要内容,是发展市场经济的重要手段。目前,非银行信用信息采集还存在一些不尽如人意的地方。因此,学习和借鉴西方发达国家个人和企业信用信息采集机制、深刻剖析我国非银行信用信息运行状况,成为新形势下开展金融信用制度创新,使其更好服务于金融业发展的重要课题。     

The effect of earnings surprises on information asymmetry

We examine the effect of earnings surprises on changes in information asymmetry. We hypothesize and find that asymmetry is lower (higher) in the quarter following positive (negative) earnings surprises compared to firms that meet the consensus analyst earnings forecast. The relations between earnings surprises and information asymmetry are stronger when the surprises are more likely to capture investors’ attention. Examining the source of these changes, we show that decreased information search activities is the most important factor for asymmetry declining after positive surprises; for negative surprises, decreased uninformed trading plays a dominant role increasing asymmetry.     

The incidence of earnings management on information asymmetry in an uncertain environment: Some Canadian evidence

In this study, we investigate the association between earnings management and information asymmetry considering environmental uncertainty. Results show that a complex and dynamic environment weakens the relationship between discretionary accruals and information asymmetry measured as share price volatility and bid-ask spread. More specifically, the positive relationship between earnings management and information asymmetry is weakened for diversified firms, those intensively investing in R&D, and those facing high sales volatility. This highlights the difficulty for investors to assess earnings management in an uncertain environment. Finally, in such a context, discretionary accruals are more likely to be detected by investors for firms cross-listed on a U.S. stock exchange, a more liquid and transparent stock market compared with the Canadian stock market.     

The information content of trade credit

During 1992–2007, suppliers financed almost 10% of the total assets of US listed firms. This intensive usage of trade credit is puzzling in the light of its high (implicit) costs. By arguing that trade credit use provides valuable information to outside investors, we first derive a theoretical model that predicts a positive correlation between trade credit use and the quality of the firm’s investments. Then, using several proxies for firm’s investment quality (Z-score, return on assets, and long-run abnormal returns), we show that this prediction receives strong support from a large sample of US firms.