Credit Risk （Based on Analysis of Financial Statements） as the Decisive Factor Influencing the Risk of Investors

Banks as the key subjects in the financing of investment have a strong influence on the risk of investors. Hence, the solvency of the bank is of crucial importance for the risk management in the investment process. Given the fact of underdevelopment of financial markets and the lack of trading activities in securities, it is evident that the investments of banks in the developing countries mostly include lending investments. Looking at the key categories of risk that influence the overall risk of the banking business in such conditions, it can be concluded that credit risk presents the dominant and decisive factor. The aim of the paper is to select the bank determinant key factors of credit risk and to determine the extent to which non-performing loans （NPL） of bank credits affect the solvency of banks, and therefore also the risk of investors. This selection of the main determinants will be based on the analysis of financial statements. This is essential, especially taking into account the impact of the global financial crisis and the increasingly frequent falling into insolvency customers. Finally, liquidity of customers is that of the bank, and it is crucial for investors to timely identify possible risks associated with bank loans in order to proactively manage risk investment.

The Mechanics Analysis of the Credit Focus Performance and the Formation of its Credit Risk in China Commercial Bank

The paper firstly gives a brief introduction of the credit focus as a result of the competition among the branch banks of the Commercial Bank. Then from the viewpoint of the performance of the branch bank, an analysis is made on the mechanism of the formation of the credit focus. Based on the analysis, the paper points out that the Commercial Bank branches, under competition of the deposit restrain, have brought about excessive credit, which exceeds the finance required by the normal business. And finally the paper forms the credit risk of the bank.

Evaluation and Empirical Analysis of the Individual Housing Mortgage Loan Credit Risk

The paper applles the methods of discriminant analy-sis,logistic regression and artificial neural networkto the credit risk evaluation of individual housingmortgage loan made by commercial banks.On thebase of the comparison among the results of thesethree methods,the article analyzes their effectivenessand concludes that artificial neural network methodshould be the best choice.

Credit Risk Analysis of Chinese Companies by Applying the CAFÉApproach

It is known that the current Credit Rating in financial markets of China is facing at least three problems:1)the rating is falsely high;2)the differentiation of credit rating is insufficient;and 3)the poor performance of predicting early warning,thus we must consider how to create a reasonable new credit risk analysis approach to deal with issues for financial markets in China for those listed companies’performance.This report shows that by using a newmethod called the“Hologram approach”as a tool,we are able to establish a so-called“CAFÉRisk Analysis System”(in short,“CAFÉApproach”,or“CAFÉ”)to resolve three issues for credit rating in China.In particular,the main goal in this paper is to give a comprehensive report for credit risk assessments for eight selected list companies by applying our“CAFÉ”from different industry sectors against actual market performance with the time period from the past one to three years through our one-by-one interpretation for event screening and true occurrence and related events.In this way,we show how“CAFÉ”is able to resolve current three major problems of“rating is falsely high,the differentiation of credit rating grades is insufficient,and the poor performance of predicting early warning”in the current credit market in China’s financial industry in practice.

The Default Risk： An Empirical Analysis on the Automotive Companies

In Italian companies, especially in small and medium enterprises （SME）, the management of financial risks, that is considered out of the core business, has not taken yet the role that it should compete in the logic of value creation that a lot of the company＇s management argues. Towards risk is witnessing a real cultural rejection, mostly it originated from the widespread belief that its operation is fraught with positive effects only in companies that have particular degrees of complexity, because they are organized in groups or because they operate in markets and different contexts. This was due to an erroneous conception of the value that drives most of the businesses to remain, in fact, and still anchored to traditional forms of management, aimed at maximizing performance accounting. The paper after analyzing the default risk proceeds to calculate the Zeta-score through discriminant analysis of a panel of companies belonging to the automotive sector.

Analysis on Risk Prevention Mechanism for Farmers' Default in Small Amount Credit

Through analysis, it is believed that major reasons for default risks in operation of small amount credit include low management level and vacancy of normative system, vacancy of risk sharing mechanism, rating distortion due to imperfect credit investigation system, and uncertainty of borrower's credit. On the basis of these, static and dynamic models are established to analyze the prevention mechanism for default risk in small amount credit. It is concluded that we must establish a restriction mechanism during operation of small amount credit as long as three values increase, namely, N (potential loss of bad credit record due to farmers' default), Q (probability of successful recovery by small amount credit institution), and S (cost of small amount credit institution punishing farmers after successful recovery). Finally, following countermeasures and suggestions are put forward: perfect laws and regulations and credit reward and punishment mechanism for risk management of small amount credit; bring into play proper function of loan officer in small amount credit practice; widely promote rural "Group Credit Union" system.

Risk Analysis of Industrial Internet Identity System

The risks of the current identity system represented by Domain Name System(DNS)and Object Identifier(OID)are studied.According to the characteristics of the industrial Internet Identity(Ⅲ)system,four open ecosystem planes are divided,and a corresponding risk analysis view is established to analyze risks for various planes.This paper uses Isaiah Berlin’s definition of liberty to more generally express the concept of security as positive rights and negative rights.In the risk analysis view,the target system is modeled from four dimensions:stakeholders,framework,architecture,and capability delivery.At last,three defensive lines are proposed to establish the identity credit system.

A Novel DBN-EFA-CFA-Based Dimensional Reduation for Credit Risk Measurement

Affected by the Federal Reserve's interest rate hike and the downward pressure on the domestic economy,the phenomenon of default is still prominent.The credit risk of the listed companies has become a growing concern of the community.In this paper we present a novel credit risk measurement method based on a dimensional reduation technique.The method first extracts the risk measure indexes from the basal financial data via dimensional reduation by using deep belief network(DBN),exploratory factor analysis(EFA)and confirmatory factor analysis(CFA)in turn.And then the credit risk is measured by a systemic structural equation model(SEM)and logistic distribution.To validate the proposed method,we employ the financial data of the listed companies from Q12019 to Q22022.The empirical results show its effectiveness on statistical evaluation,assessment on testing samples and credit risk forecasting.

Risks in Credit Financial Analyze

This article aims to study the indicators used in the financial analysis for credit and explain them. Also it checks the impact of each indicator in credit analysis and what happens if the pointer is changed deliberately to get the loan, giving some possible ways to do it and analyzing them. It proposes a new model to evaluate the indicators and the assignment of weights in formula evaluation of each indicator, so the risks of granting credit will be smaller as well as the evaluation of the financial terms of a company will be more balanced and optimal. The scope is to equilibrate the weights of each indicator in the fmancial credit analyze not by rescoring its value but by assigning shares in the evaluation formula. Doing this, it can be considered as a double checking using the same parameters and it lowers the risks in the money recovering. As it is debated in the article anyone can do fxaud to obtain a loan by altering the documents they provide through which some can do it good and even get uncaught. The scope is not to find what they did; it is to get protected even if they do it.

Functional Analysis of Chemometric Data

The objective of this paper is to present a review of different calibration and classification methods for functional data in the context of chemometric applications. In chemometric, it is usual to measure certain parameters in terms of a set of spectrometric curves that are observed in a finite set of points (functional data). Although the predictor variable is clearly functional, this problem is usually solved by using multivariate calibration techniques that consider it as a finite set of variables associated with the observed points (wavelengths or times). But these explicative variables are highly correlated and it is therefore more informative to reconstruct first the true functional form of the predictor curves. Although it has been published in several articles related to the implementation of functional data analysis techniques in chemometric, their power to solve real problems is not yet well known. Because of this the extension of multivariate calibration techniques (linear regression, principal component regression and partial least squares) and classification methods (linear discriminant analysis and logistic regression) to the functional domain and some relevant chemometric applications are reviewed in this paper.

我国中小企业信用评级质量检验的实证研究——基于因子分析模型和有序Logit模型的分析

通过对我国中小企业的发展能力、盈利能力、运营能力、偿债能力等指标进行统计分析,运用因子分析法提取公因子成分并建立有序回归模型,对我国中小企业的信用评级质量进行检验。结果表明,有序回归模型对于构建中小企业信用评级质量验证机制有着良好的效果。最后,提出提高我国信用评级质量的政策建议。

灾害天气下高速公路风险评估的Logit模型改进

Logit模型使用时要求自变量数量少、相互独立.灾害天气下高速公路风险评估的自变量种类和数量较多,变量之间存在相关性.因此,利用主成分分析将多个相关的自变量转化为少数、相互独立且包含绝大部分原始信息的新自变量,避免自变量共线性对Logit模型的影响.主成分分析表明,风险分析自变量相关性较强,不能直接使用Logit建模;主成分依次为:天气、交通流、交通标志,灾害天气的等级和持续时间是最主要变量,二者负相关,交通量与车型比例正相关,标志的清晰度和可视性正相关.Logit模型表明,天气、交通流与风险等级正相关,标志标线与风险等级负相关.实测数据证明改进模型比Logit模型评估精度更高;风险等级越高时,改进模型评估精度越高.

上市公司资信评级的多元因变量Logit模型

文章应用多元统计中的因子分析、Logit模型对上市公司企业素质、经营效益、偿债能力、发展前景等方面的综合信息进行统计分析,构建企业资信评级的多元有序变量Logit模型,进而对新上市公司进行资信等级评估。

Logitboost法与累积比数Logit模型在判别分析中的应用分析

目的:探讨Logitboost和累积比数Logit模型这两种方法应用于判别分析的优缺点。方法:简要介绍Logitboost和累积比数Logit模型的原理,并采用此两种方法分别对同一个实例进行判别分析。结果:两种方法的判别正确率均较高。Logitboost判别效果高于累积比数Logit模型判别。讨论:在迭代轮数适当的情况下,Logitboost判别正确率更高,受迭代次数影响较大;而累积比数Logit模型的稳定性较强。在对事件进行判别时,可根据数据资料的具体特点选用判别方法,也可将两种方法结合应用,取其判别效果较好者。

基于Logit模型的电动自行车驾驶人受伤严重程度影响因素研究

基于来源于交警的500起电动自行车与汽车碰撞的视频事故数据,从人、车辆、道路、环境4方面选取15个自变量进行分析,通过建立有序Logit与多项Logit事故伤害严重程度预测模型,分析15个因素对电动车驾驶人受伤严重程度的影响状况,并对比分析2个模型的预测效果.研究表明:汽车驾驶人的避险动作和违章类型、电动车驾驶人避险动作和违章类型、汽车类型、事故发生的时段、天气状况以及电动车可见时间8个自变量与伤害严重程度显著相关.

绿色供应链金融风险评估研究——基于Logit模型与BP神经网络的比较研究

近年来,由于低碳回收、绿色环保在当今社会中的地位不断提高,绿色供应链金融已经成为国家和政府促进环境可持续发展及产业全面升级的重要手段。但由于绿色供应链金融兴起的时间较晚,因素的不确定性很多,因此绿色供应链中的企业所面临的风险较为复杂和隐蔽。本文设计了较为完整的绿色供应链金融风险综合评价指标体系,通过有效性检验和敏感性分析对指标进行了优化处理,应用主成分分析将指标进行降维处理,并运用Logit模型对绿色供应链金融风险进行评估,进而与BP神经网络模型的评估结果进行对比。此外,由于针对沿海地区的绿色供应链金融研究较少,因此本文选取河北省内包含秦皇岛港、唐山港、黄骅港等的沿海地区的企业进行实证分析,结果表明当选择的样本企业比较少时,Logit模型在进行风险评估时更具有优越性,同时证实了绿色供应链金融风险评估指标体系能够准确地判断核心企业以及回收商的状况,有助于缓解融资困境。

Logit模型在商业银行中小企业信用风险评估中的应用研究

商业银行中小企业信用风险理论特指的是中小企业违约或者信用评级改变对商业银行产生损失的可能性。实际应用中通常使用预测表现最优的Logit模型进行风险评估。将影响企业信用的风险划分为定量指标与定性指标,用因子分析方法实施降维,基于公共因子建立Logit模型对中小企业信用风险实施预测。

三元Logit模型的Bayesian推断及应用

离散选择模型,特别是Logit模型在各领域均有广泛应用,Logit模型的建立难点在效用函数的确定及参数估计.借助随机游走M-H抽样方法对三元Logit模型进行Bayesian分析,得到模型参数的后验条件分布.在最小后验均方误差准则下对中小样本的模拟实验显示参数估计值十分接近真实值,其标准偏差也很小.对我国2000-2016年的外汇风险分析显示:目前一些经济基本面指标表现良好,外汇风险发生的可能性较小.

Identification of the Credit Guarantee Network of Steel Trade Enterprises in China

The risk points in the credit guarantee network of steel trade enterprises were identified by using the network analysis method in this paper. Firstly, the formation and operation mechanism of steel trade credit guarantee network was analyzed.Secondly,a guarantee network was established to analyze the related network structure indexes based on the mutual guarantee data of 83 enterprises in a steel trade market. These indexes included centrality,honest broker,and structural hole. The results suggest that network analysis method can be used to find out the risk points of the guarantee network. Additionally,some recommendations are brought forth to reduce or prevent future crises.

供应链合作伙伴信息在供应链金融信用风险预测中的作用——基于多机器学习模型的比较分析

供应链金融是中小企业缓解融资困难的有效途径。为缓解供应链金融信用风险预测面临的信息不对称和样本选择偏差等问题,文中将供应链合作伙伴信息引入风险指标体系,基于2010-2021年A股上市企业披露数据,通过随机森林、XGBoost、逻辑回归和MLP四种机器学习模型进行比较分析。结果显示,合作伙伴信息的使用提高了供应链金融信用风险预测的准确性与稳定性。最后通过Lime可解释性分析,发现合作伙伴的速动比率、销售利润率、资产负债率等6个指标是供应链合作伙伴信息中影响信用风险预测的主要因素。