农户小额信贷信用风险评估模型构建

本文利用陕西省杨凌区三家农村信用社提供的数据资料,对农户小额信贷信用风险进行实证研究,建立Logit信用风险评估模型。研究结果表明:模型的识别能力较好,对违约农户的识别正确率达85.9%,农村信用社可借助Logit模型评估农户信用风险,提高贷款质量;农户的农业收入、非农收入、房屋价值、贷款用途、贷款数额与农户信用风险有显著相关关系,而农户的年龄、耕地面积、年总支出对农户的信用风险影响不大。     

浅析小额农贷的风险防范与化解

经过不断的完善和探索,小额农贷这项金融产品以其额度小、灵活多变、手续简便等特点,有效地解决了长期困扰农民的贷款难问题,对服务“三农”和促进农村经济发展做出重要贡献。然而随着小额农贷规模的不断扩张,其存在的风险也同步显现出来,     

数据挖掘在信用风险管理中的应用

本文详细分析了在现代信用风险管理中不同方法对数据质量的要求,并在此基础上提出采用数据挖掘方法改进数据质量、提高计算精度的建议,供我国金融机构信用风险管理之借鉴.     

数据挖掘在信用风险管理中的应用

本文详细分析了在现代信用风险管理中不同方法对数据质量的要求,并在此基础上提出采用数据挖掘方法改进数据质量、提高计算精度的建议,供我国金融机构信用风险管理之借鉴。     

数据挖掘在我国商业银行信用风险度量模型中的应用

基于数据挖掘的银行客户管理信息系统就是银行利用数据挖掘技术，通过有效充分的数据挖掘，将银行客户资料作不同角度的分析，从中对客户进行定位分类，明确客户的消费倾向与消费模式，预测客户的风险性，从而实现与银行信用风险度量系统的结合。     

农户小额信贷信用风险评估机制研究

本文基于近几年农户对小额信贷需求的增加与经济下行带来的放贷压力增大的矛盾日益突出,农村金融风险监管成为农村金融工作重心的现状,以四川荣县信用联社为研究对象,通过层次分析法构建农户小额信贷信用风险评估体系,利用模糊综合评价法对信用风险进行量化评估,得到信用风险综合评价结果,进而为完善农户小额信贷风险管理提供有效资料.     

KMV模型在农业上市公司信用风险度量中的应用

我国商业银行面临的主要风险是信用风险,信用风险管理成为银行关注的重中之重。本文以农业类上市公司为样本,运用Matlab技术,通过实证来检验模型识别上市公司信用风险的能力,研究表明现阶段基于期权定价理论的KMV模型能很好地度量我国农业类上市公司的信用风险。     

CreditRisk+模型在不良资产证券化信用风险测算中的应用研究

CreditRisk 模型是由CSFP(Credit Suisse Financial Products)1997年推出的信用风险评价模型。CreditRisk 模型的最大优点是相对于其他模型,需输入的数据少,可以较为容易地计算单笔不良资产的边际风险贡献,因而可以更加直接地识别高风险资产,有助于资产池的优化以及风险管理。     

农村小额信贷信用风险分析——基于成本收益的博弈模型

信用风险是制约农村小额信贷可持续发展的主要风险。加强农村小额信贷信用风险的管理,不仅有助于小额信贷机构自身的可持续发展,也有助于农村金融的发展和社会经济的安全。立足博弈论视角,通过构建农村小额信贷机构和借款农户的成本收益博弈模型,来探求农村小额信贷信用风险的主要影响因素,并提出一些风险管理措施。     

信用风险模型回收率的实证分析

信用风险近年来越来越受到国人的关注。随着中国经济的发展和产业不断升级，经济个体的金融联系越来越密切且复杂，而信用风险也成为主要的金融风险之一。为了管理信用风险，国外经济发达国家或地区的著名金融机构纷纷开发自己的信用风险内部模型。例如Credit Metrics、KMV、Credit Rish＋、Credit Porfolio View。违约回收率对于计算信用风险是非常重要的。文章基于广东地区某商业银行抵押贷款处置资料对我国违约回收率数据进行考察，以揭示我国信用风险状况。     

Implementing natural capital credit risk assessment in agricultural lending

Agriculture has critical impacts and dependencies on natural capital, and agricultural lenders are therefore exposed to natural capital credit risk through their loans to farmers. Currently, however, lenders lack any detailed guidance for assessing natural capital credit risk in agriculture and are challenged by the fact that the relevant material risks vary considerably by agricultural sector and geography. This paper develops a natural capital credit risk assessment framework based on a bottom‐up review of the material risks associated with natural capital impacts and dependencies for Australian beef production. It demonstrates that implementing natural capital credit risk assessment is feasible in agricultural lending, using a combination of quantitative and qualitative inputs. Implementation challenges include the complexity and interconnectedness of natural capital processes, data availability and cost, spatial data analytical capacity, and the need for transformational change, both within lending organisations and across the banking sector.     

Cluster Analysis for mixed data: An application to credit risk evaluation

Credit risk is one of the main risks faced by a bank to provide financial products and services to clients. To evaluate the financial performance of clients, several scoring methodologies have been proposed, which are based mostly on quantitative indicators. This paper highlights the relevance of both quantitative and qualitative features of applicants and proposes a new methodology based on mixed data clustering techniques. Indeed, cluster analysis may prove particularly useful in the estimation of credit risk. Traditionally, clustering concentrates only on quantitative or qualitative data at a time; however, since credit applicants are characterized by mixed personal features, a cluster analysis specific for mixed data can lead to discover particularly informative patterns, estimating the risk associated with credit granting.     

Incorporating sustainability criteria into credit risk management

Does a commercial debtor's economic, environmental and social performance in terms of sustainability affect its credit risk rating? Does adding criteria aimed at assessing a lender's environmental, social or sustainability practices provide added value to traditional financial rating criteria? Many analyses have reported that a correlation exists between companies' environmental and their financial performance. We checked out the assertion that it ‘pays to be sustainable’ by analyzing the role that criteria pertaining to sustainability and environmental orientation play in the commercial credit risk management process. Our results show that sustainability criteria can be used to predict the financial performance of a debtor and improve the predictive validity of the credit rating process. We conclude that the sustainability a firm demonstrates influences its creditworthiness as part of its financial performance. Copyright © 2008 John Wiley & Sons, Ltd and ERP Environment.     

民营企业融资的信用障碍之探讨

信用缺失是民营企业融资的直接障碍,应通过完善私有产权的法律保护、依法规范政府行为、培育信用中介机构、加强信用文化建设等措施,构建有利于民营企业树立信誉的外部环境。     

通道货运分担率预测的LOGIT模型特性变量选取

文章基于效用函数理论和Logit模型,结合影响通道内各种运输方式选择的影响因素分析,以及各种运输方式的特性,认为通道内影响货运分担率预测的特型变量选取了安全性、快速性、用户成本、方便性、准时性以及货物价值6个特型变量,并分析了各个特性变量的的取值标定方法。     

Empirical analysis of the integration of environmental risks into the credit risk management process of European banks

About 15 years ago, banks started to integrate environmental risks into their credit risk management procedures. In this article, a survey of the European banking sector focusing on the analysis of the integration of environmental risks into all phases of the credit risk management, rating, costing, pricing, monitoring and work‐out, is presented. The integration of environmental risks into the whole credit risk management process is important because only then is an adequate risk management guaranteed. The results show that banks integrate environmental risks especially into the rating phase, but not in all phases of the credit management process, though this is recommendable because these risks influence all phases of the credit management process. Furthermore, significant differences in integrating environmental risks between banks that are signatories of the UNEP statement by banks on the environment and sustainable development and banks that had not signed this agreement so far could be found. Copyright © 2006 John Wiley & Sons, Ltd and ERP Environment.     

防范租赁业信用风险

一、客户信用风险产生的原因 客户的信用风险首先来自客户的失信行为,一是承租人的经济状况不佳,职业和收入不稳定,当经济情况恶化或者投资失败时,不能支付或者不能按时支付租金;二是承租人的素质较低,对租赁物缺乏责任感,造成非正常的、过度的磨损,或者偿债意愿不够强烈,不愿支付租金;还有极少数的顾客,在租赁之初就心存不轨,恶意骗租和欺诈。     

The pricing of credit risk derivatives

This paper considers the pricing of derivatives that protect holders of corporate bonds from a reduction in their value because of a deterioration in their credit quality. These derivatives are structured as either puts on the bond price or calls on the bond spread (above the risk free rate) in the context of models developed by Merton (1974) and Black and Cox (1976). The pricing properties of these options are derived using both analytical and numerical methods.     

运用信用监测模型度量上市公司信用风险的有效性研究

本文运用信用监测模型对我国上市公司的信用风险进行度量，并将度量结果与Z值模型的度量结果进行比较，以检验信用监测模型度量我国上市公司信用风险的有效性。     

论金融信用缺失及其风险防范

金融信用失灵,必然会导致全社会经济秩序的混乱,因此,防范金融信用缺失就显得尤其重要。文中分析了金融信用缺失的表现、原因,最后给出了防范金融信用缺失切实可行的建议。当然,良好社会风尚需要全民良好信用的构建。