Optimal Trade Credit Policy for Supplier under Asymmetric Information in the Supply Chain

Most papers about trade credit in supply chain studied retailer's inventory policy based on information shared.Few papers paid attention to supplier's trade credit policy under asymmetric information.So this paper tries to propose supplier's optimal trade credit policy to reveal retailer's private information.The aim is achieved by developing an incentive model with revelation principle.The retailer's private information can be found out through this trade credit policy.This contract is more general than the wholesale price contract.For the retailer's private information,the order quantity and ratio of delay in payment are distorted.Sensitivity analysis shows that the contract is influenced by sales ability and discount rate.Finally,the indirect mechanism with the same effect is proposed to make it easy to be put into practice.

Credit Rationing in Medium-small Enterprises Credit Market under Asymmetric Information

Credit rationing has been an objective phenomenon in medium-small enterprises credit market of China. By analyzing the present situation of medium-small enterprises credit market of China, this study gives a new credit rationing model fitting medium-small enterprises credit market of China well. It has been showed in the empirical study that different factor has each different influence on medium-small enterprises credit market; further more, only the change of chastisement factor can make the medium-small enterprises credit market achieve whole success, but other factors can merely get integrant success even though under the most ideal condition.

The Demographic Impact on Credit Scores＂ Evidence From Statistical Methods and Geographic Information Systems （GIS） Mapping

Average credit scores for people in the United States （US） differ from state to state. Some states have high, and some states have low average credit scores. Since lenders and employers use credit scores to make loan and employment decisions, people living in states where average credit scores are high should experience the benefits of living where credit scores tend to allow more favorable loan and employment decisions. Although credit scores are the direct result of credit histories, credit histories may be impacted by demographic factors. If the demographic factors that impact credit histories are identified, ways to improve credit scores are likely to be discovered and available to people and state government policymakers. This study looks for demographic factors to indirectly explain the average credit scores for people living in each state of the US. The methodology includes statistical analyses and geographic information systems （GIS） mapping. Statistical analyses provide evidence to suggest that state average credit scores are explained by the demographic factors of education, family, income, and health. GIS mapping reveals clusters of states with similar demographics and credit scores.

The Role of Comprehensive Information Sharing in Credit Market： Theoretical Analysis and New Evidence from the European Union

This paper investigates the effect of the comprehensive information sharing on aggregate credit volume and the default ratio. Firstly, we utilize a three-stage game model developed by Dell＇Ariccia and Marquez （2006） to illustrate that the comprehensive information sharing would change the credit resource allocation and produce negative ＂composition effects＂ stated by Jappelli and Pagano （2005）. Then we use European Union （EU） data to test these theoretical implications. We find that when the information sharing system develops to a relatively high level, comprehensive information sharing improvements, for both the width and depth, are associated with the rise in macro credit access but also the aggregate default risk. We further find that the macro-consequences of variations in information sharing just differ in OECD and non-OECD group in EU countries. For OECD countries, the negative ＂composition effects＂ mainly arise from the increase in the width of information sharing while these effects are correlated with both the rise in depth and width indicators for non-OECD countries.

Survey of the Creditor＇s Ability to Collect and Use the Enterprise Information

This paper is concerned with the analysis of the creditor＇s ability to collect, analyze and judge business information, which is a realistic problem for the bank to control the risk of loan effectively. We not only know the bank＇s application of financial and non-financial information during the process of credit extension but also investigate the use of non-financial information by questionnaire. It is discovered that the bank even believes the information that directly acquired by itself while collecting, analyzing and judging the reliability of business information. Through some sensitive information such as the changing of accounts receivable and cash flow and the connection trade, it can predict the potential risk further. In addition, the results show that it is the perfection of internal control system of intermediary （such as accounting firm） and the business enterprise itself that make the bank get the true information of business enterprise.

Why The Constitution Should Protect Personal Credit Information?——An Approach of Right Argumentation

Protecting personal credit information through constitutional rights is not only essemtial for individuals to defend against infringements on their personal credit information rights and interests by public power in the social credit system,but also a requirement for unified legislation on social credit to explore the basis for constitutional norms.In the era of the credit economy,personal credit information has become a vital resource for realizing personal autonomy.Along with the increase in the state’s supervision and control of personal credit,the realization of the autonomous value in the interests related to personal credit information has also set more obligations for the state.Therefore,interests related to personal credit information should be regarded as a constitutional right.Because of its significant economic interest and value,the right to personal credit information should be classified as a constitutional property right.As a constitutional property right,the right to personal credit information can not only help protect people’s economic interests,but also achieve the goal of safeguarding their personality interests.

The Impact of Bank-Specific and Macroeconomic Factors on Non-performing Loans in Sri Lankan Commercial Banks

The main purpose of this study is to ascertain the effect of bank-specific and macroeconomic factors on non-performing loans in systemically and non-systemically important commercial banks in Sri Lanka over 10 year’s period from 2004 to 2013.Also,the study examines the impact of civil war that prevailed in the country for 30 years on the ex-post credit risk of the banking sector.The study employed panel data methodology to investigate the effect of bank-specific and macroeconomic factors on non-performing loans.Panel unit root test has been undertaken in order to test the stationary of the variables.Hausman test and Wald coefficient restriction test were used to select the appropriate model out of pooled,random,and fixed effect.A dummy variable panel regression model adopted to study the war effect,considering 2009 as the structural year.Findings revealed that return on assets as a proxy for bank efficiency has a significant negative influence,while non-interest income as a proxy for income diversity is positively correlated with non-performing loans of systemically important banks.Both real gross domestic products and lending rates were highly significant in both bank types.On contrary with literature,growth in bank branches is negatively correlated.Public banks do not account for higher level of non-performing loans compared to their private counterpart.Finally,it was identified that civil war had an effect on the level of non-performing loans in commercial banks.The research would have benefited if the analysis is carried out among classified types of loans offered by commercial banks.Future researchers should involve in identifying the most significant contributing loan type to the non-performing loans and its determinants.This study is one of the few studies which have investigated the causes of non-performing loans in the commercial banking industry in Sri Lanka.The analysis of civil war and its impact on non-performing loans is the first study of that nature to be conducted in the context.

Substitution or Complementarity Between ＂Soft＂ Information and ＂Hard＂ Information： Why and Which Effect on Bank Profitability？

The Basel II committee sets their customers. This new up directives encouraging banks to use internal scores in order to assess the risk of form of information competes with the existing ones. Small and medium-sized enterprises （SMEs） are most concerned by these new stakes, due to the lack of transparency. The aim of this paper is to understand the determinants of the choice between substitution and complementarity between the two types of information： ＂soft＂ and ＂hard＂, to test a potential effect of this choice on the banking performance and to describe which variables are involved in the decision-making process. The originality of this work is to try to quantify the information costs and to use it as a variable which is affecting the adopted choice.

A dynamic credit risk assessment model with data mining techniques:evidence from Iranian banks

Giving loans and issuing credit cards are two of the main concerns of banks in that they include the risks of non-payment.According to the Basel 2 guidelines,banks need to develop their own credit risk assessment systems.Some banks have such systems;nevertheless they have lost a large amount of money simply because the models they used failed to accurately predict customers’defaults.Traditionally,banks have used static models with demographic or static factors to model credit risk patterns.However,economic factors are not independent of political fluctuations,and as the political environment changes,the economic environment evolves with it.This has been especially evident in Iran after the 2008-2016 USA sanctions,as many previously reliable customers became unable to repay their debt(i.e.,became bad customers).Nevertheless,a dynamic model that can accommodate fluctuating politicoeconomic factors has never been developed.In this paper,we propose a model that can accommodate factors associated with politico-economic crises.Human judgement is removed from the customer evaluation process.We used a fuzzy inference system to create a rule base using a set of uncertainty predictors.First,we train an adaptive network-based fuzzy inference system(ANFIS)using monthly data from a customer profile dataset.Then,using the newly defined factors and their underlying rules,a second round of assessment begins in a fuzzy inference system.Thus,we present a model that is both more flexible to politico-economic factors and can yield results that are max compatible with real-life situations.Comparison between the prediction made by proposed model and a real non-performing loan indicates little difference between them.Credit risk specialists also approve the results.The major innovation of this research is producing a table of bad customers on a monthly basis and creating a dynamic model based on the table.The latest created model is used for assessing customers henceforth,so the whole process of customer assessment need not be repeated.We assert that this model is a good substitute for the static models currently in use as it can outperform traditional models,especially in the face of economic crisis.

Value of big data to finance:observations on an internet credit Service Company in China

Background:his paper presents a case study on 100Credit,an Internet credit service provider in China.100Credit began as an IT company specializing in e-commerce recommendation before getting into the credit rating business.The company makes use of Big Data on multiple aspects of individuals’online activities to infer their potential credit risk.Methods:Based on 100Credit’s business practices,this paper summarizes four aspects related to the value of Big Data in Internet credit services.Results:1)value from large data volume that provides access to more borrowers;2)value from prediction correctness in reducing lenders’operational cost;3)value from the variety of services catering to different needs of lenders;and 4)value from information protection to sustain credit service businesses.Conclusion:The paper also discusses the opportunities and challenges of Big Databased credit risk analysis,which needs to be improved in future research and practice.

Relationship Between Credit Access and Agri-economy

With the rapid development of Chinese economy, the question of credit is becoming more and more important. Especially in China rural area, building a new socialist countryside needs the support of finance. While as we all known, the financial system in rural area is not effective enough to promote the productivity and the level of welfare of household.

Research on the Influencing Factors of Personal Credit Based on a Risk Management Model in the Background of Big Data

Between states, between enterprises and enterprises, between people, it can be stated that credit is full of every corner of our lives. But the current lack of social credit is fundamental. Credit risk is particularly prominent. In the extensive data generation today, the information on personal credit statistics is very large, but still lack the data system processing and screening. Through the information retrieval of 200 credit information reports, this paper constructs the evaluation system of personal credit by using the basic information of the individual. The basic information of these individuals has great convenience in information collection and information statistics, and this basic information covers all aspects that are likely to result in the breach of contract. Through the use of single factor analysis and logistic model to solve the index system, you can not only find the impact of individual indicators on the degree of personal credit, but also see the overall impact of indicators on the degree of credit, that is, the weight of the indicators. Finally, four different credit ratings are divided by assigning the indicators to the scores. Credit rating can clearly measure the respective credit situation. Through the classification of these levels, measuring the credit line when a person in the individual credit operation, at the same time, it can provide reference and proval to administrative departments, which is benefit for managing credit risks. It has a substantial meaning and value in use. The solution to the rating system cannot only be applied to individuals, but also to the enterprises, with a wide range of versatility.

Agricultural Credit Sources and Determinants of Credit Acquisition by Farmers in Idemili Local Government Area of Anambra State

The study is focused on agricultural credit sources and determinants of credit acquisition by farmers in ldemili local government area of Anambra State, Nigeria with specific objectives to： describe socio-economic characteristics of rural farmers; identify sources of agricultural credit available to rural farmers; determine socio-economic factors that influence agricultural credit acquisition of farmers; ascertain reasons for any credit misappropriation and identify problems that constrain farmers from agricultural credit acquisition. Ninety farmers were randomly selected by multi stage random sampling technique. Semi-structured questionnaire was used to elicit data for the study. Descriptive statistics and multiple regression model were used in achieving the objectives. Results indicated that 74.44% of respondents were males with a mean age of 45 years. Majority （76.67%） were married with large house hold sizes. Majority （93.33%） received different level of education, with sources of credit from friends/relatives （30.00%）, cooperative societies （43.33%）, money lenders （14.44%）, and cumulatively from formal sources （（12.22%）. The result of the multiple regression analysis revealed age, household size, membership of cooperative societies, marital status, education level, farm size and amount of loan repaid at varied signs and levels as significant predictors of amount of agricultural credit acquired by farmers. The most common reason given among the respondents （55.89%） of those who misappropriated acquired agricultural credit, was meeting nonfood needs of the household. The farmers encountered problems of high interest rate （78.89%）, lack of collateral （75.56%）, long distance from source of credit （50.00%）, poor harvest （37.78%）, moratorium （33.33%） and delay in loan approval/disbursement （44.44%） as constraints to acquire credit. The study recommends that the state government should pass policies aimed at providing free educative seminars to all illiterate farmers to teach them possible ways and methods of acquiring credit. To ensure mass attendance to such seminars, little incentives should be given to farmer participants.

The Empirical Estimation of the Influence of Credit Risk Determinants in Baltic States＇ Banking Sector

There have been investigated empirically the influence of macroeconomic and real estate market variables on the level of non-performing loans in the Baltic States. A secondary goal was to analyze the effect of constant loan portfolio growth on the level of non-performing loans in mentioned countries and to define the type of influence of the variables （i.e., long-term or short-term）. The research indicates that all variables except the growth rate of the real estate market （RRE） have long-term influence on the level of non-performing loans. RRE has short-term influence and variables influence is associated with the development of another variables. The influence of RRE played an important role, but it was not as crucial as it has been previously assumed. If a respective credit risk management is applied, the influence of RRE is to be eliminated. The research results indicate that the most significant reason for the growth of non-performing loans for the Baltic States presented by rapid growth of aggregated loan portfolio and unemployment rate. The increasing influence of rapid loan portfolio growth proves the assumption that banks＇ credit risk management policies underestimated the changes in the macroeconomic variables during the analyzed period. The changes in the real GDP had initial influence on the economic situation deterioration for Baltic States.

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 Source of Flowing Water”:How Targeted Poverty Alleviation Helps China’s Rural Poor Access Credit

Based on the China Household Finance Survey(CHFS)data of 2011-2017,this paper investigated the effects of China’s targeted poverty alleviation policy on rural credit access and amount using the“difference-in-differences”methodology.This study found that the targeted poverty alleviation policy increased the availability and amount of formal credit to poor households and reduced the proportion and amount of their borrowing through informal channels,and that the effects increased amid the policy’s implementation over time.This paper further found that the policy effects were more significant for China’s western regions,reflecting a positive role of targeted poverty alleviation in coordinating pro-poor finance across regions.Compared with poor counties,poor households from non-poor counties experienced a greater increase in their probability and amount of formal credit access,reflecting China’s approach of reducing regional poverty before targeting more precisely at individual poor households.This paper also uncovered that no significant“elite capture”effect had existed in the allocation of formal agricultural credit under targeted poverty alleviation,but extremely poor households experienced no significant change in their access to formal credit.While the targeted poverty alleviation policy has helped create a sound rural credit market,it should further improve access to formal finance for extremely poor households.

Research on Personal Credit Evaluation Based on Mobile Telecommunications Data

With the rapid development of big data technology, the personal credit evaluation industry has entered a new stage. Among them, the evaluation of personal credit based on mobile telecommunications data is one of the hotspots of current research. However, due to the complexity and diversity of personal credit evaluation variables, in order to reduce the complexity of the model and improve the prediction accuracy of the model, we need to reduce the dimension of the input variables. According to the data provided by a mobile telecommunications operator, this paper divides the data into a training sets and verification sets. We perform correlation analysis on each indicator of the data in the training set, and calculate the corresponding IV value based on the WOE value of the selected index, then binning data with SPSS Modeler. The selected variables were modeled using a logistic regression algorithm. In order to make the regression results more practical, we extract the scoring rules according to the results of logistic regression, convert them into the form of score cards, and finally verify the validity of the model.

The Reasolis Why Informal Finance Exists and Some Suggestions on Policy

Compared with formal finance, informal finance owns advantages in information and collateral. These are the reasons why informal finance exists widely in many ways. However, informal finance has its deficiencies too. On the basis of the analysis of the advantages and deficiencies of informal finance, the paper also offers some suggestions on policy that government should adopt on informal finance.

A Literature Review of the Influence of Social Capital on Commercial Credit

As a typical informal system,social capital plays an important supplementary role in China’s economic transition period.Informal finance based on commercial credit plays a role in the economic cycle.However,there is currently a lack of literature to directly examine the impact of social capital on the use of commercial credit by enterprises.This article aims to systematically sort out the theoretical development of social capital on commercial credit,which mainly includes the definition of social capital,its effects,the influencing factors of commercial credit,and the summary of the existing research results of social capital on commercial credit.It is hoped that this literature review will provide guidance for future research.