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The peculiar characteristics of Project finance compared to standard corporate loans pose relevant problems to credit risk managers in terms of methodologies and metrics for credit risk measurement. The issue is even more important as long as capital regulation and Basel II and III rules are concerned. Although theory and practice have clarified the main pillars of credit risk measurement and management for corporate loans, little is still known about the quantification of credit risk for structured transactions in project finance. After a review of the Basel Committee framework for credit risk in specialized lending (SL) and of the recent reforms triggered by the financial turmoil of the past few years, the chapter presents empirical data about default and recovery rates for project finance deals and shows that project finance is a very resilient asset class even in periods of severe financial distress. The chapter introduces also the concept of Value at Risk (VaR) and presents a specifically designed methodology for the quantification of the value at risk of project finance deals.

In this paper, I develop and estimate a dynamic equilibrium model of household borrowing and savings decisions in formal and informal credit markets. The model features households with heterogeneities in productivity and wealth, and characterizes credit market access by interest rates, fixed costs, and borrowing constraints. Households have access to an exogenous formal credit market and to an informal credit market in which the interest rate is endogenously determined by the local demand and supply of credit. My application focuses on Thailand which implemented policies in 2001 that primarily encouraged borrowing. I estimate the model by simulated maximum likelihood using data from the Townsend Thai Monthly Survey. Based on the estimated model, I find that lower fixed costs increased the proportion of households borrowing formally, and that relaxed formal borrowing collateral constraints lowered informal interest rates. In terms of welfare, I find that low wealth but productive households benefited from Thai policies to expand credit access, but the gains were smaller than suggested by previous studies that ignored the informal market. Moreover, approximately 18% of households suffered welfare losses because of diminished opportunities for informal saving. Counterfactual policy simulations suggest that policies that combine borrowing and savings subsidies could yield higher average social welfare at a cost similar to the implemented policies.

Credit system is generally associated with the banking and financial institutions, although it has far reaching implications for residents of countries, such as U.S., particularly for those with a poor credit history. Specifically, a credit score computation (CSC) quantifies an individual’s credit value or credit risk, which is used by banking and financial institutions, as well as other entities (e.g., during purchasing of insurance policies and application of rental properties), to facilitate their decision-making (e.g., whether to approve the insurance policy purchase or the level of premium). Although a number of CSC models have been proposed in the literature for supporting different application scenarios, privacy protection of CSC is rarely considered despite the potential for leakage of user private information (e.g., registration, hobbies, credit, relationships, and inquiry). Such information can then be abused for other nefarious activities, such as identity theft and credit card fraud. Thus, in this article, we first analyze the privacy strength of existing CSC models, prior to presenting the formal definition of a privacy-preserving CSC system alongside its security requirements. Then, we propose a concrete construction based on Paillier encryption with three proposed noninteractive zero-knowledge schemes. To demonstrate feasibility of our proposal, we evaluate both its security and performance.

How does market information affect credit ratings? How do credit ratings affect market information? We analyze a model in which a credit rating agency's (CRA's) rating is followed by a market for credit risk that provides a public signal - the price. A more accurate rating decreases market informativeness, as it diminishes mispricing and, hence, incentives for investor information acquisition. On the other hand, more-informative trading increases CRA accuracy incentives by making rating inflation more transparent. If the first effect is strong, policies that increase reputational sanctions on CRAs decrease rating inflation, but also decrease the total amount of information.

Ratings seem increasingly central to the regulatory system of modern capitalism and therefore to governments everywhere. Getting credit ratings “right” therefore seems vitally important to many observers. But in pursuing improvement in the rating system one needs to appreciate the challenges and limits to rating. This article argues, after due attention to the origins and work of the agencies, that our expectations of the agencies are founded on a limited rationalist or machine-like understanding of the workings of capital markets. A more appropriately social (and dynamic) view of markets makes the challenge of effective rating even more daunting. The increasingly volatile nature of markets has created a crisis in relations between the agencies and governments, which increasingly seek to monitor their performance and stimulate reform in their procedures.

As a pillar in the development of China’s economy, the financial industry plays a key role in the production and life of residents. Along with the widespread application of the internet, internet finance has gradually emerged as required by the times, and in the achievement of the collection and extraction of big data, related analysis and exploration technologies have been emphasized more. However, in the context of big data technology, there are still risks of unsound laws, inadequate business publicity, user information security, and capital liquidity in internet finance. Under this digital economy era, this article attempts to discuss these risks, which need to be prevented from establishing a good internet financial system, strengthening interindustry exchanges and cooperation, building a unified internet financial information supervision platform, as well as optimizing the internet financial credit reporting system, so as to promote a healthy and sound development of the whole financial industry.

The article aims to identify effective ways to combat bank fraud in Ukraine. Using the method of systematic analysis of theoretical experience, practical measures and international legislation in the field of combating banking fraud, the main factors influencing the bank fraud level are identified: financial instability of the banking institution, lack of information about the client's credit history, poor internal control, low level of corporate governance, lack of a standard procedure for customers verification, lack of a unified register of bank employees, imperfect legal regulators and a banking control system. The study allowed to identify the characteristics of an effective banking fraud combating system: a clear definition of the legal framework, regulation subjects and objects, strict and guaranteed liability for violations of laws, cooperation of structural units and regulatory authorities at the domestic and international level, state control of financial monitoring. As a result of the study, it was concluded that the successful experience of developed countries, comprehensive implementation of measures to combat bank fraud (at the legislative, bank management and technological level) will not only reduce the level of bank fraud, but also corruption, money laundering and terrorist financing rate.

This paper investigates firms’ access to bank credit in eleven euro area countries over the periods 2014–2019. Exploiting firm-level longitudinal data, we analyse loan demand and credit rationing probabilities, accounting for sample selection, unobserved heterogeneity and state dependence. Empirical results show that small and informationally opaque businesses, with deteriorated public support and credit history, face greater difficulties in obtaining bank loans. Furthermore, we provide evidence of a significant degree of state dependence in access to credit. In particular, firms that have already experienced credit restrictions are more likely to face further constraints, while enterprises that applied for bank financing in the past seem to have easier access to credit. Focusing on the subset of firms actually needing additional bank financing, we also find that past credit restrictions significantly reduce their current demand, providing evidence of a significant discouragement effect. Supplementary Information The online version contains supplementary material available at 10.1007/s11187-021-00545-x., Plain English Summary Access to bank credit is a key driver of firms’ survival and growth, especially in bank-based financial systems. Building on detailed longitudinal survey data, this study investigates the determinants of access to bank financing by firms in the euro area, both in a static and dynamic setting. Most importantly, we account for the intertemporal nature of firms’ loan demand behaviour and banks’ credit granting choices and show that they are both characterized by significant persistence over time. We also find that repeated lending interactions enhance access to credit and that firms needing additional financing tend to be discouraged from applying after having experienced an actual credit restriction. Our findings shed light on the existence of substantial and persistent financial frictions in banking markets, which play a key role in amplifying adverse economic shocks, and call for policy and regulatory interventions to improve firms’ access to credit and limit systemic vulnerabilities. Supplementary Information The online version contains supplementary material available at 10.1007/s11187-021-00545-x.

This study aims to determine the effect of efficiency ratios, non-perfoming loans, and profitability on the capital adequacy ratio in Islamic Commercial Banks in Indonesia 2014-2018. This research is a quantitative study with secondary data from financial reports. Purposive sampling is a sampling technique use in this study so that there are 14 samples of Islamic commercial banks during the 2014-2018 period. The data analysis used is multiple linear regression analysis with the SPSS application. The results obtained by two dependent variables, the efficiency ratio and non-performing loans have an influence on the capital adequacy ratio. Meanwhile, profitability partially has no effect on the capital adequacy ratio.

Small- and medium-sized enterprises (SMEs) have a crucial influence on the economic development of every nation, but access to formal finance remains a barrier. Similarly, financial institutions encounter challenges in the assessment of SMEs’ creditworthiness for the provision of financing. Financial institutions employ credit scoring models to identify potential borrowers and to determine loan pricing and collateral requirements. SMEs are perceived as unorganized in terms of financial data management compared to large corporations, making the assessment of credit risk based on inadequate financial data a cause for financial institutions’ concern. The majority of existing models are data-driven and have faced criticism for failing to meet their assumptions. To address the issue of limited financial record keeping, this study developed and validated a system to predict SMEs’ credit risk by introducing a multicriteria credit scoring model. The model was constructed using a hybrid best–worst method (BWM) and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). Initially, the BWM determines the weight criteria, and TOPSIS is applied to score SMEs. A real-life case study was examined to demonstrate the effectiveness of the proposed model, and a sensitivity analysis varying the weight of the criteria was performed to assess robustness against unpredictable financial situations. The findings indicated that SMEs’ credit history, cash liquidity, and repayment period are the most crucial factors in lending, followed by return on capital, financial flexibility, and integrity. The proposed credit scoring model outperformed the existing commercial model in terms of its accuracy in predicting defaults. This model could assist financial institutions, providing a simple means for identifying potential SMEs to grant credit, and advance further research using alternative approaches.

This paper augments a relatively standard dynamic general equilibrium model with financial frictions in order to quantify the macroeconomic effects of the credit deepening process observed in many Latin American (LA) countries in the last decade, most notably in Brazil. In the model, a stylized banking sector intermediates credit from patient households to impatient households and firms. The key novelty of the paper, motivated by the Brazilian experience, is to model the credit constraint faced by (impatient) households as a function of future labor income. In the calibrated model, credit deepening generates only modest abovetrend growth in consumption, investment, and GDP. Since Brazil has experienced one of the most intense credit deepening processes in Latin America, it is argued that the quantitative effects for other LA economies are unlikely to be sizeable.

The research objectives to be achieved are: (1) To analyze and reveal empirically whether the Capital Adequacy Ratio (CAR), OE, Financing to Deposit Ratio (FDR), Net Operating Margin (NOM) affects the performance of Islamic Commercial Banks as measured by the ratio ROA). (2) To determine and analyze whether the non-performing loan ratio (NPF) moderates the effect of Capital Adequacy Ratio (CAR), OE, Financing to Deposit Ratio (FDR), and Net Operating Margin (NOM) on the performance of Islamic Commercial Banks (Return On Assets). This type of research is a quantitative research. The population used in this study is a Islamic commercial banks registered with the Financial Services Authority consisting of 14 BUS from 2015-2019. The data used is secondary data and uses saturated sampling method. Researchers used this sampling technique because the total population of 14 Islamic commercial banks companies in Indonesia are registered with the Financial Services Authority (OJK). Analysis of research data using Moderating Regression Analysis. Simultaneously CAR, OE, FDR and NOM have a positive effect on BUS performance for the 2015-2019 period as measured by ROA, but the partial results are only CAR that has a positive effect on ROA while OE, FDR and NOM have a negative effect on ROA, this happens because The capital adequacy held in the current period in lending is currently decreasing when compared to the previous period so that it has an impact on decreasing income and profit for the next period. Simultaneously, NPF moderates CAR, OE, FDR and NOM have a positive effect on BUS performance for the 2015-2019 period as measured by ROA, while the partial results are only NPF which has an impact on reducing the effect of CAR on ROA, while other variables when NPF moderate the relationship with ROA moves towards improvement. This is because the capital adequacy ratio is currently used in handling the current bad credit ratio as a result of loans extended in the previous period so that the current capital that should be used to generate profits in the next period through an increase in the volume of credit at this time from the previous period is reduced so that an impact on the decline in Islamic commercial banks profitability in the next period. As for what makes the difference in this study is the moderation of NPF on the effect of CAR, BOPO, FDR and NOM on ROA.

This article aimed to analyze the problem of legal cases accumulation, especially default on credit contracts in court. It also analyzes the effectiveness of implementing a small claim court in contract default and the independence of a single judge in handling cases through the small claim court mechanism. Small claim court also to offer a breakthrough in the settlement of bad loans related to contract defaults to reduce the burden on courts in Indonesia and provide legal certainty to business actors. The sole judge also examine, resolve and decide on inheritance cases in a fast and efficient process to issue a fair decision for all parties. This normative study was carried out using statutory, case, comparative law, and analysis content approaches. The research results showed that the filing of small claim court increased 10 times from 2015 to 2020, with the plaintiffs dominated by banks in bad credit cases. A small claim court provides benefits the bank and the customer because it speeds up the settlement of the plaintiff's money in a bad credit case with a case value of not more than 500 million, especially for microloans in a maximum period of 25 days. Furthermore, the latest regulation of 2019 concerning small claim court gives judges the authority to confiscate guarantees and conduct auctions to carry out forced executions through the Court Execution Auction process.

The relevance of the study is due to the necessity to solve the problems of agricultural lending in the Kyrgyz Republic. The problems of financing and lending to agriculture are still urgent in the Kyrgyz Republic, therefore, specific financial instruments of Islamic banking, which are highly appreciated in the practise of other countries, are well suited for project financing, work in conditions of high uncertainty characteristic of agriculture in the Kyrgyz Republic. The purpose of the study was to identify alternative loan products for agricultural economic entities based on Islamic principles of financing in the Kyrgyz Republic. Research objectives: to provide brief information on the current state in the field of agricultural lending; give brief information on the development of Islamic principles of lending in the Kyrgyz Republic; define the concept and classification of Islamic banking instruments in agriculture; define the financial instrument “Ijara” and identify its advantages. Research methods: methods of the empirical level (studying of literature and other sources of information, observation, comparison), methods of the theoretical level (study and generalisation, analysis and synthesis). In the process of writing this article, Islamic banking instruments have been reviewed and classified. The concept of Ijara contract was considered, new modern technologies in the field of Islamic banking were investigated. The main distinctive principles of Islamic banking from the Western model of financial leasing were analysed. The credit history of agriculture and forestry of the Kyrgyz Republic was analysed.

Purpose: Credit information sharing cost positively influenced the profitability of banks in Kenya. The general objective of the study was to evaluate credit information sharing and profitability of banks in Kenya. Methodology: The paper used a desk study review methodology where relevant empirical literature was reviewed to identify main themes and to extract knowledge gaps. Findings: The study stablished that borrower’s credit history information had a positive influence on the profitability in Kenya. The study the respondents agreed that their banks collect information on the number of previous applications that a loan applicant has made, the bank collects information on the number of loans applied and declined, the bank asks for reasons that the loan applied was declined for all applicants, the bank asks loan applicants to indicate the discipline observed when repaying previous loans advanced, the bank asks clients to indicate if they have delayed in remitting their periodic loan repayment in the past, the banks collect more information about the loan applicants credit history from the CRB. Recommendations: The study recommended that while sharing information, the banks should do a cost benefit analysis to ascertain if the sharing of such information is material or not. It should pay its attention to the administrative costs that come with sharing information. This is because the cost of information sharing as seen from the study results have a negative and significant influence on performance Purpose: Credit information sharing cost positively influenced the profitability of banks in Kenya. The general objective of the study was to evaluate credit information sharing and profitability of banks in Kenya. Methodology: The paper used a desk study review methodology where relevant empirical literature was reviewed to identify main themes and to extract knowledge gaps. Findings: The study stablished that borrower’s credit history information had a positive influence on the profitability in Kenya. The study the respondents agreed that their banks collect information on the number of previous applications that a loan applicant has made, the bank collects information on the number of loans applied and declined, the bank asks for reasons that the loan applied was declined for all applicants, the bank asks loan applicants to indicate the discipline observed when repaying previous loans advanced, the bank asks clients to indicate if they have delayed in remitting their periodic loan repayment in the past, the banks collect more information about the loan applicants credit history from the CRB. Recommendations: The study recommended that while sharing information, the banks should do a cost benefit analysis to ascertain if the sharing of such information is material or not. It should pay its attention to the administrative costs that come with sharing information. This is because the cost of information sharing as seen from the study results have a negative and significant influence on performance

PurposeDespite the noticeable consequences of disruptive financial innovations, access to finance remains a major factor inhibiting the sustainable-growth potentials of young micro-entrepreneurs in informal settings. This study examines the determinants of financing options among micro-entrepreneurs in informal settings. Specifically, the study seeks to establish whether credit history, income, asset, gender, awareness and network capability have effects on formal and informal financing options among micro-entrepreneurs in informal settings.Design/methodology/approachThis article uses the survey research design and administers a structured questionnaire among 300 purposively selected micro-entrepreneurs within the University of Lagos, Nigeria. Only 291 completed questionnaires are retrieved. This article also uses the multiple regression analysis to estimate the empirical model and test the research hypotheses respectively.FindingsThis article establishes that: (1) credit history and assets-based financing are significant determinants of formal financing options among young micro-entrepreneurs in informal settings, (2) gender and network capability are significant determinants of informal financing options among young micro-entrepreneurs in informal settings and (3) awareness is significant of both formal and informal financing options among young micro-entrepreneurs in informal settings.Originality/valueThis article examines the determinants of financing option among young micro-entrepreneurs in informal settings. Specifically, the study seeks to establish whether credit history income asset gender awareness and network capability have effects on formal and informal financing options among micro-entrepreneurs in informal settings.

We show that consumers spend 15% more per day in the first week following the receipt of a credit card statement than in the days just prior to the statement. This increase in spending includes both an increase in the likelihood that they use the credit card in the first weeks following their statement and an increase in transaction amount on days they use the credit card. In contrast to the effect on credit card spending, debit card spending is unaffected by credit card statement issuance, suggesting that consumers are not simply switching among modes of payment. Our estimates are based on exogenous variation from bank-assigned statement dates. We propose and test several alternative explanations to this spending puzzle: optimization of the free float, salience effect of the credit card statement, mental accounting, liquidity constraints, and automatic payments. We find that the consumers most apt to spend early in the credit card cycle tend to be those who do not revolve balances and are not close to their credit limit. Thus, this paper documents a puzzle with mixed support for several alternative explanations. This paper was accepted by David Simchi-Levi, finance.

The role of credit in a cooperative is very important. With the credit can be a source of profit for the cooperative. The cooperative was founded with the aim of prospering its members. One of the advantages is that cooperative members can apply for credit loans. To approve the proposed loan, it is necessary to analyze the credit submitted by the members. This has become one of the difficulties for several cooperatives, one of which is KSU BMT Tunas Harapan Syari'ah which is located in thePringgasela village, Pringgasela District, East Lombok Regency. The problem that often arises is that the analysis conducted is often incorrect, resulting in a prolonged bad credit in installment payments. The reason is that cooperatives always use statistical data which is sometimes inaccurate because there is no processing using data processing methods. Therefore, the neural network data mining method can be used as a tool to analyze which customers are problematic and not problematic. From the results of the research that has been done, it produces an accuracy of 96.19% and an AUC of 0.976

Although many scoring models have been developed in literature to oer nancial institutions guidance in credit granting decision, the pur- pose of most scoring models are to improve their discrimination ability, not their explanatory ability. Therefore, the conventional scoring models can only provide limited information in the relationship among customer de- mographics, default risk, and credit card attributes, such as APR (annual percentage rate) and credit limits. In this paper, a Bayesian behavior scor- ing model is proposed to help nancial institutions identify factors which truly reect customer value and can aect default risk. To illustrate the proposed model, we applied it to the credit cardholder database provided by one major bank in Taiwan. The empirical results show that increasing APR will raise the default probability greatly. Single cardholders are less accountable for credit card repayment. High income, female, or cardholders with higher education are more likely to have good repayment ability.

A large-scale microcredit expansion program—together with a credit bureau accessible to all lenders—can enable unbanked borrowers to build a credit history, facilitating their transition to commercial banks. Loan-level data from Rwanda show the program improved access to credit and reduced poverty. A sizable share of first-time borrowers switched to commercial banks, which cream-skim less risky borrowers and grant them larger, cheaper, and longer-maturity loans. Switchers have lower default risk than nonswitchers and are not riskier than other bank borrowers. Switchers also obtain better loan terms from banks compared with first-time bank borrowers without a credit history.

Sharia and conventional business management system are often become a parameter in gaining profit and managing the risk faced by the entrepreneurs. This research aims to determine the comparison of profit and risk obtained by the property entrepreneurs in conducting their business when they use conventional or sharia system. This research is qualitative descriptive analysis. The variables that would be investigated are the profit obtained by the property business owner and the risks in conducting this business when the business owner uses sharia and conventional system in the capital investment or the buying and selling process of a certain property unit. The data was collected through an interview and documents. The article shows that conventional and sharia are a concept or system that generally used by the entrepreneurs in conducting their business to obtain the profit and face the risks. Both of the systems have advantages and disadvantages. This article further argues that sharia system gives a higher profit and fewer risks rather than the conventional system. It is because in the sharia system, entrepreneurs or costumers are not concerned about the burden of the interest and fines of the debt from a financing institution. Although there are risks considered such as bad credit and longtime cash flow, the profit obtained through the sharia system is higher than the conventional one.

One of the factors causing the bankruptcy of a company is bad credit. Therefore, prospective customers need to be selected so that bad credit cases can be minimized. This study aims to determine the classification of credit granting to prospective customers of company X in order to reduce the risk of bad credit. The method used is the binary logistic regression method and the Chi-Squared Automatic Interaction Detection (CHAID) method. In this study, data used in November 2019 were 690 motorcycle credit data for company X in Gresik. The independent variables in this study are the factors that affect bad credit such as gender, marital status, education, employment, income, expenses, home ownership status and the dependent variable is credit status (bad and current). The analysis results show that the binary logistic regression has an accuracy value of 76.38% with an APER of 23.62%, while CHAID has an accuracy value of 93.19% with an APER of 6.81%. The accuracy value of the CHAID method is greater than the binary logistic regression method, while the APER value of the CHAID method is smaller than the binary logistic regression method. So it can be concluded that the CHAID method is better than the binary logistic regression method in classifying bad credit at company X. Keywords: Credit, Classification, Binary Logistic Regression, CHAID.