A credit scoring approach for the commercial banking sector

For managing credit risk, commercial banks use various scoring methodologies to evaluate the financial performance of client firms. This paper upgrades the quantitative analysis used in the financial performance modules of state-of-the-art credit scoring methodologies. This innovation should help lending officers in branch levels filter out the poor risk applicants. The Data Envelopment Analysis-based methodology was applied to current data for 82 industrial/manufacturing firms comprising the credit portfolio of one of Turkey's largest commercial banks. Using financial ratios, the DEA synthesizes a firm's overall performance into a single financial efficiency score—the “credibility score”. Results were validated by various supporting (regression and discriminant) analyses and, most importantly, by expert judgments based on data or on current knowledge of the firms.     

Environmental Credit Risk Management in Banks and Financial Service Institutions

How do Canadian banks integrate environmental risks into corporate lending and where are they located compared with their global peers? In this paper we report a mixed method analysis of the integration of environmental risks into the credit management. The qualitative and quantitative analyses suggest that all analyzed Canadian commercial banks, credit unions and Export Development Canada manage environmental risks in credit management to avoid financial risks. Some of the institutions even connect environmental and sustainability issues with their general business strategies. Compared with other countries, Canadian banks are best in class, as all six Canadian commercial banks, comprising over 90 percent of Canadian assets, systematically examine environmental risks for credits, loans and mortgages. We conclude that Canadian banks are proactive regarding environmental examinations of loans and that there is a need for a more accountancy related reporting on environmental risk management in financial institutions. Further research is needed to be able to calculate costs and benefits of integrating environmental and sustainability issues into the credit risk management. Copyright © 2011 John Wiley & Sons, Ltd and ERP Environment.     

国外信用风险度量方法对我国的借鉴与启迪

国外信用风险度量方法可分为传统和现代信用风险度量方法两大类,与其相比,我国信用风险度量方法存在定性分析多、缺乏较好的信用资料历史数据库,征信法规建设滞后、信用中介机构实力不强,证券市场有效性不高,信用文化基础薄弱等问题。因此,我们要静态与动态、定量与定性分析相结合,尽快建立大型违约数据库,加快征信立法、大力扶持国内专业信用评级机构,进一步开拓资本市场功能,加强信用文化建设。     

An evaluation of financial institutions: Impact on consumption and investment using panel data and the theory of risk-bearing

The theory of the optimal allocation of risk and the Townsend Thai panel data on financial transactions are used to assess the impact of the major formal and informal financial institutions of an emerging market economy. We link financial institution assessment to the actual impact on clients, rather than ratios and non-performing loans. We derive both consumption and investment equations from a common core theory with both risk and productive activities. The empirical specification follows closely from this theory and allows both OLS and IV estimation. We thus quantify the consumption and investment smoothing impact of financial institutions on households including those running farms and small businesses. A government development bank (BAAC) is shown to be particularly helpful in smoothing consumption and investment, in no small part through credit, consistent with its own operating system, which embeds an implicit insurance operation. Commercial banks are smoothing investment, largely through formal savings accounts. Other institutions seem ineffective by these metrics.     

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.     

Credit ratings of Chinese online loan platforms based on factor scores and K-means clustering algorithm

The rapid development of Chinese online loan platforms (OLPs), as well as their risks, has attracted widespread attention, increasing the demand for a complete credit rating mechanism. The present study establishes a credit rating indicator system for 130 mainstream Chinese OLPs that combines 12 quantitative metrics of online loan operations similar to commercial bank credit rating indicators, including platform transaction volume and average expected rate of return. We also consider two qualitative indicators of online loan background, namely platform background and guarantee mode, that reflect Chinese characteristics. Subsequently, a factor analysis was conducted to reduce the 14 indicators’ dimensions. The loads of the rating indicators in the resulting rotating component matrix were refined into an OLP operation scale factor, fund dispersion factor, security factor, and profitability factor. Finally, a K-means clustering algorithm was employed to cluster the factor scores of each OLP, thereby obtaining credit rating results. The empirical results indicate that the proposed machine learning–based credit rating method effectively provides early warnings of problem platforms, yielding more accurate credit ratings than those provided by two mainstream online loan rating websites in China, namely, Wangdaitianyan and Wangdaizhijia.     

Central bank disclosure as a macroprudential tool for financial stability

The Basel Capital Accord (pillar 3) states that disclosure of information (transparency) is essential to financial stability. This study analyzes, through inflation reports, the disclosure of information from the Central Bank of Brazil concerning the credit market. We consider credit risk and capital buffers as measures of financial stability in this analysis. Furthermore, in order to measure the perception of the monetary authority on the credit market, we built two indices based on the central bank’s communication on credit development. We performed a panel data analysis based on a sample of 125 banks for the period from June 1999 to September 2014 (7000 observations). The findings suggest that central bank communication regarding expectations concerning the credit market contributes to financial stability. Therefore, this kind of communication of central banks (about credit development) may constitute an important macroprudential tool to improve financial stability.     

电信客户信用评价实证分析

文章主要立足于客户长期价值提升的思想,基于定性和定量结合的层次分析法建立电信企业的客户信用评价指标体系,重点分析了个人用户的信用评价指标体系的建立过程,最后给出了数据实证分析。     

产业集群的金融风险及其控制研究

本文对产业集群作为信贷主体的优劣势做出了分析,并对产业集群的金融风险预警指标进行了设计,对产业集群金融风险管理提出了对策性分析。     

Modeling hard and soft facts for SMEs: Some international evidence

This paper asks how well the use of quantitative and qualitative variables can improve the assessment of companies' creditworthiness and how this result can be influenced by the economic and financial peculiarities of countries. We harden qualitative variable measures to model soft information aimed at scoring microfirms, small, and medium‐sized firms. The structural survey covers Germany, Italy, and the UK in a sample of about 17 thousand companies observed during the financial crisis. Soft facts are determined within the balanced scorecard framework in order to find out the impact of customers, business processes, learning and growth, and financial perspectives. Our findings show that credit models integrating soft variables optimize the risk estimation, but estimates are country‐specific and should be tailored to the characteristics of each economic system.     

基于AHP对我国上市公司信用风险评价

AHP法作为信用评级的一种方法,在信用风险评价过程中有着十分重要的作用。它以定性与定量相结合的方式处理各种决策因素,方法灵活简洁,适应性较广。通过对该方法在煤炭行业中股市表现优劣的两家公司应用结果的分析和比较,着重说明AHP对于我国上市公司信用风险评价的可行性。     

农产品物流金融的信用风险评价研究

农产品物流的资金短缺问题成为农产品物流发展的瓶颈,为此农产品物流金融的快速发展也给农产品物流的发展带来了巨大的运营风险。为了评估农产品物流金融的信用风险,文中首先研究农产品生产加工企业参与物流金融业务的必要性及信用风险评价要素,在此基础上建立了农产品物流金融信用风险评价指标体系,并利用层次分析法及模糊综合评价法构建了农产品物流金融信用风险评价模型,最后把理论模型应用于某公司的农产品物流金融信用风险评价,对于实施农产品物流金融业务具有一定的参考价值。     

Bagging方法在基于日常交易数据解决中小企业的信用评价问题中的应用

关于信用风险评价问题至今已经做了很多研究,各种信用评价模型与方法也已被开发。但是这些模型与方法几乎都是基于财务数据、股票价格或风险调研机构发表的各种调查结果。因为几乎所有的中小企业的财务数据都是非公开的,至今开发的信用评价模型与方法都不免成为无米之炊。为此,本文提出了一个新的途径,只需要根据销售额、顾客付款额、拖欠款额等日常业务处理数据来评价顾客企业的信用度。本文提出一个应用Sagging方法评价顾客信用的系统,其目的在于解决由于异常顾客数比正常顾客要少很多而带来的问题,提高分辨异常顾客的能力。本文所提出的信用评价系统将应用到一个实际企业的信用评价问题中,借此来验证系统的性能和效果。     

The role of banking regulation in an economy under credit risk and liquidity shock

This paper develops a Dynamic Stochastic General Equilibrium model which includes a financial sector to analyze the effects of liquidity shock and credit risk in the Brazilian economy. Banks use equity capital and deposits from agents to finance investments of the productive sector. The sources of financial frictions are default rate and liquidity shock, due to deposits withdrawn in advance. The banking supervisor injects liquidity in the deposit market. Using data for the Brazilian economy in the period from 1995 to 2009, the structural parameters are estimated by Bayesian methods. Impulse response functions are computed to describe the dynamic effects of exogenous shocks. The major results show that credit risk is pro-cyclical and default risk depends on structural features. The banking regulator is able to set up a policy to promote financial stability and efficiently reduce fluctuations in the output.     

Credit behavior and financial stability in an emerging economy

One relevant issue for the management of financial stability is the monitoring of the credit market. In this sense, Basel III proposed the credit gap as the most appropriate measure to anticipate financial stability issues. However, the adoption of the credit gap has been criticized, especially for emerging markets. Through panel data analysis, this study investigates the effect of the credit gap and the credit growth rate on financial stability in Brazil, which represents a relevant emerging economy. For this purpose, we use a set of financial stability measures traditionally found in the literature: the z-score, regulatory capital and credit risk. The results suggest that the credit gap and credit growth rates are adequate metrics to indicate the sustainability of credit growth in Brazil. However, credit growth rates are more attractive, since they indicate a threshold for credit growth in the Brazilian economy concerning financial stability.     

基于CCA模型的信用风险定价分析与实证研究

信用风险一直是银行和其他金融机构关心的主要话题。对待信用风险的传统方法是由信用风险部门根据过去的数据进行统计估计。然而,在最近几年,随着金融市场的迅速发展以及金融工具的日益复杂化,这种方法已经显得无法适应了。从最广义的风险说起,把讨论范围逐渐缩小,最后缩小至信用风险的定价问题。通过Merton模型对信用风险定价过程作一般性推导,同时给出一个例子以便掌握运用这种方法。     

信息不对称视角下信用担保的风险成因及治理研究

从信息经济学角度,通过运用数理金融中的定量分析方法,并结合现代金融学中的定性分析方法,深入探讨信用担保风险形成的金融机理问题,为我国信用担保业的科学运营提供重要的决策参考。研究对于构建完备有效的中小企业信用担保体系,切实有效地发挥其在中小企业融资中的作用,具有很好地理论指导和现实意义。     

Global Credit Risk: World,Country and Industry Factors

We investigate the dynamic properties of systematic default risk conditions for firms in different countries, industries and rating groups. We use a high‐dimensional nonlinear non‐Gaussian state‐space model to estimate common components in corporate defaults in a 41 country samples between 1980:Q1 and s2014:Q4, covering both the global financial crisis and euro area sovereign debt crisis. We find that macro and default‐specific world factors are a primary source of default clustering across countries. Defaults cluster more than what shared exposures to macro factors imply, indicating that other factors also play a significant role. For all firms, deviations of systematic default risk from macro fundamentals are correlated with net tightening bank lending standards, suggesting that bank credit supply and systematic default risk are inversely related. Copyright © 2016 John Wiley & Sons, Ltd.     

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。     

How can banks and finance companies incorporate value chain factors in their risk management strategy? The case of agro-food firms

A value chain framework for guiding the financial firms in their credit decisions is urgent, as the current COVID-19 pandemic has highlighted, but missing in the extant literature, particularly for those that lend to industries sensitive to value and supply chain bottlenecks. This study creates knowledge in value chain finance, a big untapped and un-researched market. It constructs, confirms, and validates a value chain framework for assessing risks in lending to Agro and Food Processing firms in which value chain risks are major business concerns globally. To pursue the objectives of the study, we use a novel methodology that integrates the Modified Delphi technique, exploratory factor analysis, confirmatory factor analysis, and discriminant analysis. Based on testing and analysis of primary data, including loan data, a framework comprising six factors is proposed for use in conjunction with existing risk assessment models of finance companies to improve the quality of their credit decisions, contributing to their performance sustainability.