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Journal articles on the topic 'Borrower creditworthiness'
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Kucherenko, Svitlana, and Oleh Kucherenko. "Methods of assessing the creditworthiness of the natural person borrower." University Economic Bulletin, no. 46 (September 1, 2020): 170–77. http://dx.doi.org/10.31470/2306-546x-2020-46-170-177.
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The purpose of the study is to analyze the methods of assessing the creditworthiness of the natural person borrower in terms of feasibility of its applying in various types of lending, as well as to provide the recommendations on the most effective method of implementing such an assessment in banking institutions practice. Both general scientific and special methods of scientific knowledge have become the methodological basis of the article. In the process of writing the article the following methods were used: dialectical, economic comparisons and generalizations, grouping, graphical, system-structural analysis and synthesis. Results of work. In the article the modern methods of assessing the creditworthiness of the natural person borrower used by banking institutions in their practice are thoroughly investigated. The advantages and disadvantages of using each of them and the feasibility of applying different methods in providing various types of loans are substantiated. It is determined that the most promising method of assessing the creditworthiness of the natural person borrower is credit scoring. The implementation of these recommendations will lead to the improvement and acceleration in providing the quality banking services for the client, as well as to the successful operation of the banking institution. Conclusions. The financial condition of the bank as a whole depends on the quality of assessing the creditworthiness of borrowers. Most often, the examination of the creditworthiness of individual borrowers is carried out on a point system for assessing the clients’ reliability. Based on the analysis of qualitative and quantitative indicators, the bank makes a conclusion about the reliability of a potential borrower and gives the assessment to the creditworthiness of the borrower. In considering the financial situation and economic condition of a potential borrower all the details are important, otherwise the bank may be at risk and suffer great losses. At the same time, the complexity of assessing the creditworthiness of the borrower makes financial institutions to apply the different approaches to evaluation methods. Careful clients’ selection based on the assessment of the borrower's creditworthiness allows the bank to minimize its credit resources loss.
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Масленников, Анатолий, and Anatoliy Maslennikov. "ANALYSIS AND ASSESSMENT OF THE CREDITWORTHINESS OF BORROWER." Services in Russia and abroad 10, no. 5 (August 29, 2016): 58–68. http://dx.doi.org/10.12737/21196.
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In modern conditions commercial banks and enterprises inadequate use the credit opportunities for innovative projects investment to ensure the continuity and acceleration of the reproduction process and timeliness of settlements with suppliers and creditors. Banks need to significantly change the approach to the analysis and assessment of the creditworthiness of borrower and methods for their implementation.
This article clarifies the concept of "creditworthiness", defines list of tasks to be solved in the process of analysis and assessment of borrower’s status.
The information provided by a borrower to the bank, the information that is available directly at the bank, and external information is used as the source data for the analysis of the creditworthiness of borrower.
Source data is used to assess the creditworthiness of borrower from legal and economic points of view. From a legal point of view it is necessary to explore and assess the legal capability of a potential borrower (the organization) to make a credit transaction.
From an economic point of view, to assess the creditworthiness of borrower the factors and conditions should be identified, in which he will not be able in full and in due time to pay his credit debt.
The purpose of assessment of the creditworthiness of borrower from legal and financial points of view is in aspiration of a bank to reduce risks of non-return loan.
For this analysis, a bank needs for information describing the financial status of borrower, which makes it necessary to study the financial and accounting reports of the organization, information about cash movement on the borrower’s bank accounts, information about the borrower’s potential previous cooperation with other banks and insurance companies.
The article discusses the various options for methods of solving this problem by the banks, investigates modern trends of borrower’s creditworthiness assessment, and proposes method of calculating the borrower’s rating on the basis of the expert method and the method of paired comparisons.
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Alexander Petruk, Olena Lagovska, Nataliya Vyhovska, and Volodymyr Vyhovskyi. "DEVELOPMENT OF METHODOLOGICAL PRINCIPLES FOR CREDITWORTHINESS ASSESSMENT AS A BASIS FOR CREDIT RISK IDENTIFICATION OF THE BANK." European Cooperation 9, no. 40 (October 31, 2018): 29–39. http://dx.doi.org/10.32070/ec.v9i40.25.
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The work deals with the methodological principles for creditworthiness assessment of the borrower, which serves as the basis for determining the bank credit risks and directions for improving the regulation. The authors took into account the off-balance sheet liabilities in order to improve the methodology of assessing the borrower's creditworthiness, which allowed to increase the accuracy of the bank's credit risk assessment and is the basis for effective management decisions on the credit approval. As a result of the analysis of methodological support for assessing the borrower's creditworthiness, the authors have proven the effect on the integral index and debtor class. These studies confirmed that their legal regulation is a prerequisite for the effective implementation of a new methodological approach to the creditworthiness assessment in banking institutions. The article defines three regulatory levels of the creditworthiness assessment of the borrower-legal entity (international, national and interbank) and directions for improving regulation at the national level, as well as at the domestic one.
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Orlova, Ekaterina V. "Methodology and Models for Individuals’ Creditworthiness Management Using Digital Footprint Data and Machine Learning Methods." Mathematics 9, no. 15 (August 1, 2021): 1820. http://dx.doi.org/10.3390/math9151820.
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This research deals with the challenge of reducing banks’ credit risks associated with the insolvency of borrowing individuals. To solve this challenge, we propose a new approach, methodology and models for assessing individual creditworthiness, with additional data about borrowers’ digital footprints to implement comprehensive analysis and prediction of a borrower’s credit profile. We suggest a model for borrowers’ clustering based on the method of hierarchical clustering and the k-means method, which groups actual borrowers having similar creditworthiness and similar credit risks into homogeneous clusters. We also design the model for borrowers’ classification based on the stochastic gradient boosting (SGB) method, which reliably determines the cluster number and therefore the risk level for a new borrower. The developed models are the basis for decision making regarding the decision about lending value, interest rates and lending terms for each risk-homogeneous borrower’s group. The modified version of the methodology for assessing individual creditworthiness is presented, which is to reduce the credit risks and to increase the stability and profitability of financial organizations.
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SHEPTUKHA, Olena, and Anna LAPTIEVA. "Assessment of the borrower's credit capacity using discriminative analysis." Economics. Finances. Law, no. 6 (June 26, 2020): 25–28. http://dx.doi.org/10.37634/efp.2020.6.6.
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Introduction. At the present stage of economic development in the organization of credit relations uses a significant number of approaches and methods to determine the creditworthiness of the borrower. Today, banking institutions are developing different approaches to the analysis of the borrower's creditworthiness. Moreover, each bank determines its own method of assessing the financial condition of a potential borrower, taking into account the specific terms of the contract. Assessment of creditworthiness of the enterprise by the method of discriminant analysis is carried out by calculating and interpreting the integrated indicator of financial condition. The purpose of the paper is to determine the nature and assessment of the borrower's creditworthiness using the methods of discriminant analysis. Results. Assessing the borrower's creditworthiness is a topical issue that affects the success and effectiveness of its lending activities. That is why the article is devoted to defining the nature and assessment of the borrower's creditworthiness using the methods of discriminant analysis. It assessed the creditworthiness of PJSC "Kharkiv Biscuit Factory" using foreign and domestic methods of assessing the creditworthiness of the borrower. It was determined that the main disadvantage of foreign models is that they are developed based on a study of enterprises in the United States and Western Europe. Weights are not adapted to modern conditions of transformation of the domestic economy and do not take into account the specifics of Ukrainian enterprises. These models have several significant limitations. They can be used only as additional models in parallel with modern domestic models. Calculating the probability of bankruptcy of PJSC "Kharkiv Biscuit Factory" according to foreign and domestic methods can give a clear conclusion about the financial condition of the enterprise. The above-mentioned methods demonstrate the absence of probability of bankruptcy at PJSC "Kharkiv Biscuit Factory". Conclusion. In general, the degree of reliability of the assessment of economic security of the enterprise and a set of necessary measures to prevent possible threats depend on the accurate identification of threats, the correct choice of a system of indicators for diagnosis. According to the results of calculations, it was determined that the company belongs to class A, which is characterized by high financial condition.
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Khomenko, Inna, Iryna Sadchykova, and Yuliia Krasnianska. "Current approaches to the analysis of the borrowers’ creditworthiness: Ukrainian and World experience." Economics ecology socium 3, no. 1 (March 31, 2019): 48–55. http://dx.doi.org/10.31520/2616-7107/2019.3.1-5.
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Introduction. Non-repayment of loans by borrowers not only jeopardizes the profitability of banking structures, but also the ability to calculate them under liabilities - deposit and borrowed funds. This situation is dangerous for the entire banking sector of the country, as it raises a number of acute problems: imbalance of loan and deposit portfolio by volumes and terms; distrust of the population to commercial banks, financial destabilization in the state as a whole, and others like that.
Aim and tasks. The main purpose of this work is to study modern domestic and foreign approaches to assessing the creditworthiness of borrowers.
Results. Based on the analysis of the definitions it is expedient to use the following interpretation of the term "creditworthiness": the financial, economic and legal capacity of the borrower to obtain a loan and return it to the commercial bank in accordance with the terms and conditions of the agreement. At the initial stages of the methodologies developing for the analysis of borrowers' lending, the leading role was played by the coefficient method, which by its nature is considered the simplest and is currently used as an express evaluation and preceded by other research. Currently, almost all commercial banks use a rating approach to assess the borrower's creditworthiness. Such methods also include calculation of coefficients, but contain a predictive component. The rating approach is valuable, because it requires a constant collection of updated information. Often, banks when building credit ratings use the methods of the relevant agencies. It is now believed that the formation of credit ratings allows you to get the most general idea of the borrower's creditworthiness (at the level of the commercial bank) and about the quality of the loan portfolio (at the level of the banking system of the state). Moreover, when assessing the creditworthiness of borrowers – individuals, the rating approach is most often used.
Conclusions. The conducted studies indicate that improving approaches to assessing the creditworthiness of borrowers by commercial banks is particularly relevant for Ukraine. It is important to carry out measures (including administrative) in order to increase the reliability of the input information of borrowers, training of specialized specialists – experts, assessment of qualitative data on the debtor, formation of constantly updated statistical databases, adjustment of methodological developments taking into consideration the variability of the economic situation in Ukraine, ensuring transparency of the analysis, etc.
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Zaruk, Natalia Fedorovna, and Elena Sergeevna Kolomeeva. "Analysis of the creditworthiness of agribusiness organizations as a tool for obtaining additional Bank financing." Buhuchet v sel'skom hozjajstve (Accounting in Agriculture), no. 9 (September 1, 2020): 39–48. http://dx.doi.org/10.33920/sel-11-2009-05.
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The article presents various approaches and methods for assessing the creditworthiness of agricultural organizations in order to obtain additional funding. Models of analysis of the borrower’s creditworthiness by foreign banks and some Russian credit institutions are considered. A comparative assessment of the main methods for determining the level of creditworthiness of a borrower — legal entity is given based on: statistical models (methods) of assessment; models of limited expert assessment; models of direct expert assessment. It is established that major Russian banks mainly use methods for analyzing the borrower’s creditworthiness, based on the analysis of the main performance indicators of the industry and organization, assessment of the borrower’s financial condition, and analysis of collateral. These rules allow agribusiness organizations to assess their ability to repay debt and interest on it on time and reduce Bank risks. The analysis of the creditworthiness of the agribusiness organization according to the methodology of JSC “Rosselkhozbank” was carried out.
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Дмитриева and Olga Dmitrieva. "Short credits and micro-loans for individuals: advantages, disadvantages, the main options." Vestnik of Kazan State Agrarian University 9, no. 3 (December 14, 2014): 11–15. http://dx.doi.org/10.12737/6505.
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In everyday life, unforeseen or unplanned purchases lead to a desire to borrow a small amount on the short term. This problem is known to many people. Currently, the only viable option is short-term loans from commercial banks or micro-loans provided by microfinance institutions. They have their own advantages and disadvantages, and it is designed for a specific audience of potential borrowers. Short-term bank credit is available at any bank that deals with consumer credit borrowers. There are four main types of loans in the short term: a term loan; line of credit; overdraft on a personal map; quick loans. The potential borrower has the ability to get a loan only if certain conditions of the credit institution. Microfinance institutions are engaged in issuing microloans. There are two main types of micro-loans to individuals: consumer loans for a period of one year; term loans to payday. In this type of lending the solvency of the borrower is not evaluated, not studied his income, credit history is not analyzed. The creditworthiness of the borrower is assessed through informal criteria. Despite some limitations and high cost, short-term loans and micro-loans is a great opportunity to purchase desired and necessary goods or solve other consumer problems.
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KRAMARENKO, Iryna, and Liliia KOZACHENKO. "METHODOLOGY FOR ASSESSING THE BORROWER’S CREDITWORTHINESS: PRACTICAL ASPECT." Economy of Ukraine 2018, no. 5 (May 10, 2018): 49–60. http://dx.doi.org/10.15407/economyukr.2018.05.049.
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Today, the banking system does not fulfill its main task, since it does not finance or lend to the real sector of the economy, and a quarter of the loans provided are written off and unpaid. The current situation in Ukraine necessitates studying the ways and means to improve the assessment of the borrower’s creditworthiness as the main direction for stabilizing and improving the efficient lending activity of com-mercial bank. The purpose of the study is: (i) to access the current state of bank lending to business; (ii) to access the borrower’s creditworthiness and its influence on the amount of overdue loans; (iii) to determine provision for impairment of loans; (iv) to provide practical recommendations for improving the borrower’s creditworthiness on the example of JSC Raiffeisen Bank Aval. The annual amount of loans granted by the banking system to enterprises in-creases, while the indebtedness of the customers also grows. Thus, the share of overdue loans in August 2017 amounted to 22.65% of the total loans granted in Ukraine. The JSC Raiffeisen Bank Aval is among the leaders in providing loans. During the period under study, interest income of the bank decreased significantly, this indicates a low profitability of credit operations. When analyzing the provisions for impairment, it was revealed that more than 28% of loans are written-off, and this is primarily due to a wrong assessment of the borrower’s solvency. When assessing the financial condition of the borrower, according to the meth-odology of JSC Raiffeisen Bank Aval, it is determined that performance indicators of the potential payer of loans are not taken into account. Also, the methodology has no rating or scoring of accounting ratios used in the analysis of solvency of the bor-rower. The rationale is to use, when assessing the solvency of the borrower of JSC Raiffeisen Bank Aval, the Decree “About the statement of Regulations about deter-mination of Ukrainian banks credit exposure in active banking operations”, which came into force on January 3, 2017.
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Song, Xiao, Hao Ying, Xiande Zhao, and Lujie Chen. "Improving assessment capability for accounts receivable pool financiers." Industrial Management & Data Systems 120, no. 3 (December 31, 2019): 547–66. http://dx.doi.org/10.1108/imds-04-2019-0239.
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Purpose The accounts receivable pool (ARP) is an e-invoice management system that provides suppliers with easy access to financial service. The purpose of this paper is to focus on the strength and weakness of ARP mechanism and suggest efficient methods to identify creditworthy borrowers. Design/methodology/approach By decomposing the sales records of 348 ARP borrowers and predicting the occurrence of overdue incidences, this study first portrays the creditworthy borrowers by sales features. Then, content analysis was applied to measure the loadings of soft and hard information, and examined the effectiveness of different information structures in creditworthiness assessment. Findings For ARP borrowers, upward trend and low volatility reveal their creditworthiness. In order to identify creditworthy borrowers beforehand, ARP financiers who have elaborated more soft information and less hard information can perform better. Originality/value This study first discussed ARP finance from a critical perspective and underlines borrower assessment to eliminate the defect of loose recourse. The empirical evidence presents the sales features of creditworthy borrowers. Moreover, the results suggest an efficient approach for ARP financiers to conduct better assessment.
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Bailey, Warren, Wei Huang, and Zhishu Yang. "Bank Loans with Chinese Characteristics: Some Evidence on Inside Debt in a State-Controlled Banking System." Journal of Financial and Quantitative Analysis 46, no. 6 (June 6, 2011): 1795–830. http://dx.doi.org/10.1017/s0022109011000433.
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AbstractWe study a transitional economy where state-controlled banks make loan decisions based on noisy inside information on prospective borrowers, and may lend to avert unemployment and social instability. In China, poor financial performance and high managerial expenses increase the likelihood of obtaining a bank loan, and bank loan approval predicts poor subsequent borrower performance. Negative event study responses occur at bank loan announcements, particularly for borrowers measuring poorly on quality and creditworthiness, or for lenders or borrowers involved in litigation regarding loans. Our results highlight dilemmas in a state-led financial system and the local stock market’s sophistication in interpreting news.
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Syrchyn, Oleksandr. "Theoretical basis for assessing the creditworthiness of bank borrower." Socio-Economic Research Bulletin, no. 1(65) (March 28, 2018): 153–60. http://dx.doi.org/10.33987/vsed.1(65).2018.153-160.
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Orlova, E. V. "Predictive Credit Risk Analytics Using Borrowers' Digital Footprint and Methods of Statistical Machine Learning." Programmnaya Ingeneria 12, no. 7 (October 11, 2021): 358–72. http://dx.doi.org/10.17587/prin.12.358-372.
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The article considers the problem of reducing the banks credit risks associated with the insolvency of borrowers — individuals using financial, socio-economic factors and additional data about borrowers digital footprint. A critical analysis of existing approaches, methods and models in this area has been carried out and a number of significant shortcomings identified that limit their application. There is no comprehensive approach to identifying a borrowers creditworthiness based on information, including data from social networks and search engines. The new methodological approach for assessing the borrowers risk profile based on the phased processing of quantitative and qualitative data and modeling using methods of statistical analysis and machine learning is proposed. Machine learning methods are supposed to solve clustering and classification problems. They allow to automatically determine the data structure and make decisions through flexible and local training on the data. The method of hierarchical clustering and the k-means method are used to identify similar social, anthropometric and financial indicators, as well as indicators characterizing the digital footprint of borrowers, and to determine the borrowers risk profile over group. The obtained homogeneous groups of borrowers with a unique risk profile are further used for detailed data analysis in the predictive classification model. The classification model is based on the stochastic gradient boosting method to predict the risk profile of a potencial borrower. The suggested approach for individuals creditworthiness assessing will reduce the banks credit risks, increase its stability and profitability. The implementation results are of practical importance. Comparative analysis of the effectiveness of the existing and the proposed methodology for assessing credit risk showed that the new methodology provides predictive analytics of heterogeneous information about a potential borrower and the accuracy of analytics is higher. The proposed techniques are the core for the decision support system for justification of individuals credit conditions, minimizing the aggregate credit risks.
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Выборова, Е., and E. Vyborova. "The Features of Analysis of Economic Consistency and the Creditworthiness of Borrower." Auditor 5, no. 7 (August 7, 2019): 45–50. http://dx.doi.org/10.12737/article_5d3984132eb668.16989225.
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In the article the content of systematization of systems and the models of financial analysis is presented. The paper examines the peculiarities of method of analysis of economic consistency, the creditworthiness of borrower and the technological regime of crediting in the part of the forms of collateral repayment.
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Githama, John Njenga, and Paul Gachanja. "Effects of Credit Appraisal Methods on Non-Performing Loans in Government Owned Financial Institutions, A Case of Kenya Commercial Bank Limited." International Journal of Current Aspects 4, no. 2 (September 6, 2020): 1–12. http://dx.doi.org/10.35942/ijcab.v4i2.123.
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Financial institutions have in the recent past become a major player in the Kenyan economy. Consequently, for the institutions to sustain viable credit programmes, the criteria for assessing credit risk are essential so as to minimize the loan default. There are various known methods and tools which can be employed by credit offices to ensure that they lend quality loan. These methods try to establish the creditworthiness of the potential borrower. Quality loans means good returns to the business since there is less provisions for bad debt in the books of the lending institution. One of the criteria for establishing the creditworthiness of a borrower is the C’s of credit model. These are initials for;-character, capacity , capital, collateral , common sense, contribution and conditions The C’s of credit refers to the borrower’s specific attributes which, if well used can help the lender arrive at a better decision of whether to lend or not to lend, the amount to lend and possibly the period to allow. Lending institutions, however, have continued to record non-performing loans, despite there being elaborate known methods to aid in credit appraisal. The objectives of this study were to establish the factors that have contributed to non performing loans in financial institutions, whether the appraising persons are well versed on C’s of credit and challenges affecting appraising persons during the appraising process. To arrive at reliable findings, the researcher engaged respondents from selected financial institutions who were supplied with questionnaires in order to collect the sought data. The researcher employed descriptive research design which entails distributing questionnaires to respondents. The respondents were sampled from twenty financial institutions where respondents were chosen randomly. The target population in this case was credit officers irrespective of their cadres. For ease of collection of data, the study was located in Nairobi County where most financial institutions are based. The data so collected was coded to facilitate analysis. The researcher employed both descriptive and inferential statistics to analyze the data. The researcher further employed the credit scoring model which uses data on observed borrower characteristics, either to calculate the probability of default or to sort out borrowers into different default risk classes.
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Wasilewska, Natalia, Mirosław Wasilewski, and Serhiy Zabolotnyy. "The Enterprise’s Financial Condition Assessment as a Component of its Creditworthiness." Zeszyty Naukowe SGGW w Warszawie - Problemy Rolnictwa Światowego 18(33), no. 4 (December 28, 2018): 493–503. http://dx.doi.org/10.22630/prs.2018.18.4.137.
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The article covers aspects of financial condition analysis regarding creditworthiness of Ukrainian agricultural enterprises that had to operate in unstable economic conditions in 2009-2017. It is proposed to improve methodological approaches to financial assessment of an enterprise – a potential borrower, due to changes in the economy, in particular in the financial sector, which have been influenced by crises that have shaken the Ukrainian economy twice in the past ten years. The proposed approaches to assessing the financial condition of an agricultural enterprise as a component of its creditworthiness increase the accuracy and credibility of such assessments and help to minimize credit risks.
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Pukala, Ryszard, Nataliya Vnukova, Tetiana Tokhtamysh, Oleksandr Yaholnytskyi, and Kateryna Hranko. "Evaluation of the creditworthiness of extractive industry companies." E3S Web of Conferences 168 (2020): 00035. http://dx.doi.org/10.1051/e3sconf/202016800035.
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The article uses the methodology of assessing the creditworthiness of the National Bank of Ukraine as a borrower for extractive industry companies taking into account the principles and recommendations of the Basel Committee on Banking Supervision. According to the financial statements of the extractive industry companies, variables and coefficients have been counted to calculate the objective function of the integral indicator. The classes of debtors of the surveyed enterprises by years are determined. It has been proved that, with average creditworthiness, the activity of extractive industry companies is risky, but these companies need to attract external funds and financial resources. To measure the risk level of the group of surveyed companies, we used the calculation of asymmetry parameters of the statistical distribution, which showed that the activity of extractive industry companies is risky due to the peculiarities of the industry.
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Zailani, Achmad Udin, and Nugraha Listiana Hanun. "PENERAPAN ALGORITMA KLASIFIKASI RANDOM FOREST UNTUK PENENTUAN KELAYAKAN PEMBERIAN KREDIT DI KOPERASI MITRA SEJAHTERA." Infotech: Journal of Technology Information 6, no. 1 (June 11, 2020): 7–14. http://dx.doi.org/10.37365/jti.v6i1.61.
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Credit is the provision of money or bills which can be equalized with an agreement or deal between the bank and another parties that requires the borrower to pay off the debt after a certain period of time through interest. Before the cooperative approves the credit proposed by the debtor, the cooperative conducts a credit analysis of borrowers whether the credit application is approved or disapproved. This study objectives to predict creditworthiness by applying the Random Forest Classification Algorithm in order to provide a solution for determining the creditworthiness.This research method is absolute experimental research that leads to the impact resulting from experiments on the application of the decision tree model of the Random Forest Classification Algorithm’s approach. The study results using the Random Forest Classification Algorithm’s are able to analyze problem credit and disproblems debtors with an accuracy value of 87.88%. Besides that,. decision tree model was able to improve the accuracy in analyzing the credit worthiness of borrowers who filed.
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D’yakonova, Iryna, Yevgeniya Mordan, and Kateryna Sokolenko. "The methodical framework of the development of adequate model of estimation of credit risk of the bank." Corporate Ownership and Control 13, no. 1 (2015): 769–73. http://dx.doi.org/10.22495/cocv13i1c7p4.
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It was considered the modern methods of assessment of credit risk which are used by the foreign banks, in particular, their essence, advantages and disadvantages were discovered in this article. It was proposed and characterized the criteria of judgmental estimate adequacy of the models intended for analysis and forecast of borrower creditworthiness assessment, in particular such criteria as general accuracy of the model, the errors of 1st and 2nd kind, ROC – curve and GINI index.
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Mubashar, Ammara, Sumayya Chughtai, and Abdul Raheman. "Trade Credit and Stock Return Predictability: Evidence from Pakistan." Abasyn Journal of Social Sciences, Volume 14 issue 1 (June 30, 2021): 145–57. http://dx.doi.org/10.34091/ajss.14.1.09.
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Trade credit transfers private information about borrower�s creditworthiness and future performance to other lenders and this information can also be translated into the stock market. The purpose of this study is to analyze the informational role of trade credit in predicting future stock returns of the firms in the context of Pakistan. After controlling for market and firm-specific characteristics in our proposed five-factor model, it is found that firms depending more on trade credit as compared to bank loans have higher future stock returns. These findings suggest that trade credit supply signals the information that the supplier has about the borrower and this information is gradually and positively translated in the market Keywords: Trade Credit, Stock return Predictability, Fama & French Three-Factor Model
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Razzaq, Shazma, Nadeem Maqbool, and Waseem Ul Hameed. "Factors Effecting The Elasticity Of Micro Credit Demand In Southern Punjab, Pakistan." International Journal of social Sciences and Economic Review 1, no. 2 (October 18, 2019): 46–53. http://dx.doi.org/10.36923/ijsser.v1i2.34.
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Purpose of the study: Microfinance institutions (MFIs) are delivering various services of microcredit, savings as well as insurance. The key objective of microcredit is to decrease the poverty level and for empowering the women as well as other poor people under various developing countries. There is the various factor which effects on the demand of microcredit. Therefore, the objective of the current study is to explore the factors which affect the demand for microcredit.
Methodology: In this conceptual study, the qualitative research technique was used. The data were collected from previous research studies and companies’ websites.
Main Findings: It is concluded that numerous factors may influence the demand for microcredit by the various borrowers. These comprise the interest rate, the relationship between lenders as well as borrowers, different government policies, gender differences, prospective beneficiaries, the creditworthiness of the borrower, transaction cost, limited access to credit, economic condition and the availability of information.
Applications: This helps analyze the barriers which the borrower and lender must face in operating the microcredit. In this way, microfinance institutions can take help from this study by considering these factors during the distribution of credit.
Novelty/Originality: The findings of this research study fulfilled the theoretical gaps in the literature by identifying the different fact which may help to revise the poverty level. Future research studies may focus on these factors, which may help to increase the economy and reduce poverty in southern Punjab, Pakistan.
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Onikiienko, Serhii, Yevheniia Polishchuk, Alla Ivashchenko, Anna Kornyliuk, and Nazar Demchyshak. "Prior credit assessment of long-term SME projects with non-standard cash flows." Banks and Bank Systems 16, no. 2 (June 17, 2021): 148–58. http://dx.doi.org/10.21511/bbs.16(2).2021.14.
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Over the past three decades, the relative bank loan demand has changed due to the arising small and medium-sized enterprises (SMEs). Therefore, banks in their operations face the problem of processing an ever-increasing number of loan applications. The aim of this paper is to develop an auxiliary approach to assessing the prior creditworthiness of long-term SME projects with nonstandard cash flows.This study reveals how the principles of value-based management can be incorporated into the process of borrower’s creditworthiness assessment to improve the process of screening loan applications. For this, the internal rate of return was used as a criterion for loan granting decision at the initial stage of loan underwriting.An algorithm for the preliminary evaluation of loan applications is proposed and is based on the principle of maximizing the shareholder value of banks. This algorithm helps to define the credit terms taking into consideration the distribution of positive cash flows throughout the project’s expected economic life, calculate the possible real effective interest rate concerning the borrower’s nonstandard cash flow schedule, make a rough analysis on the economic efficiency of lending and state the necessary criterion to initiate the procedure of loan underwriting for the projects with nonstandard cash flow schedules. The proposed estimation algorithm stemming from the IRR-approach for the cash flow analysis can also be initially used by a borrower as a tool for credit solvency self-testing via screening of periods with corresponding cash flows that can be used for loan servicing.
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Yendovitsky, D. A., I. V. Frolov, and R. R. Rakhmatulina. "A comparative analysis of approaches to the quantitative assessment of the creditworthiness of the borrower." Problemy ucheta i finansov, no. 25 (March 1, 2017): 3–14. http://dx.doi.org/10.17223/22229388/25/1.
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Gusarova, Lubov, Nadezhda Zhilina, and Marina Shamsutdinova. "COMPARATIVE CHARACTERISTICS OF THE METHODOLOGY FOR ASSESSING THE CREDITWORTHINESS OF THE BORROWER OF AB " DEVON-CREDIT»." Russian Journal of Management 7, no. 4 (January 28, 2020): 71–75. http://dx.doi.org/10.29039/2409-6024-2019-7-4-71-75.
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The article is devoted to the problem of credit rating under the unstable economic situation in the country, the negative impact of sanctions, reduced solvency of enterprises and the public which is becoming increasingly important for domestic commercial banks. In a crisis, both individuals and legal entities experience difficulties in fulfilling their obligations due to a lack of funds. Therefore, they are forced to apply for credit resources more often than in a stable economy. In this regard, banks should insure themselves against credit risks even at the initial stage of lending, which is possible only if the credit organization has an effective credit rating system, which allows obtaining the highest quality information about the borrower, his capabilities and readiness to return lent funds.
The main hypothesis of the study is that at present there is no uniform methodology that allows evaluating credit rating in full. In this regard, banks are developing their own methods, generally similar to each other.
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Ushanov, Aleksandr Evgenievich. "Analysis of corporate borrower’s solvency: complex approach." Vestnik of Astrakhan State Technical University. Series: Economics 2022, no. 1 (March 31, 2022): 103–12. http://dx.doi.org/10.24143/2073-5537-2022-1-103-112.
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The cancellation of regulatory relief due to the Covid-19 pandemic, which allowed banks to save on reserves for restructured loans, did not significantly affect the stability of the system in 2021. At the same time, there remains the probability of certain types of systemic risks, including credit risks. During the pandemic the Russian business debts increased by 14% and reached 62.6% of the countryʼs GDP, which significantly increased credit risks for banks. There is a high concentration of corporate liabilities in Russia - a great part of the debt falls on a small number of large borrowers who are serviced by large banks. It is found that reducing the credit risks and increasing the credit activity of market participants can be achieved both by methods of macroeconomic regulation and by improving the mechanism for analyzing the creditworthiness of corporate borrowers at the level of credit institutions. Measures to minimize credit risks are listed. The formula for the final calculation of the level of credit risk is given. The indicators are analyzed on the basis of the Russian Accounting Standards (RAS) and on the basis of the International Financial Reporting Standards (IFRS), the values of debt burden indicators are considered. There is offered a model of such an analysis based on a mixed complex-individual model including an assessment of industry and structural indicators based on expert opinion, existing threats from competitors or the market, transparency of the borrower's activities, as well as the expertise of leading international rating agencies. The model allows predicting the future position of the borrower in the market, as well as taking into account the specifics of lending conditions.
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Malakauskas, Aidas, and Aušrinė Lakštutienė. "Financial Distress Prediction for Small and Medium Enterprises Using Machine Learning Techniques." Engineering Economics 32, no. 1 (February 26, 2021): 4–14. http://dx.doi.org/10.5755/j01.ee.32.1.27382.
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Financial distress prediction is a key challenge every financing provider faces when determining borrower creditworthiness. Inherent opaqueness of Small and Medium Enterprise business complicates credit decision making process, therefore increasing cost to finance and lowering probability of receiving funds. This paper used data on 12.000 SMEs to estimate binomial classifiers for financial distress prediction using Logistic Regression, Artificial Neural Networks and Random Forest techniques. Classical financial ratios were used to estimate initial single-period predictors, which were later enhanced with time, credit history and age factors to retrieve multi-period models. Contrary to other studies, financial distress is understood as a significant challenge to company’s ability to cover liabilities rather than probability to go bankrupt. Highest prediction accuracy was reached using Random Forest algorithm with additional factors. It was concluded that period-at-risk adjustment is necessary to ensure highest financial distress prediction accuracy.
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Paul, Sohini. "Creditworthiness of a Borrower and the Selection Process in Micro-finance: A Case Study from the Urban Slums of India." Margin: The Journal of Applied Economic Research 8, no. 1 (January 22, 2014): 59–75. http://dx.doi.org/10.1177/0973801013506401.
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BARTEL, FRITZ. "Fugitive Leverage: Commercial Banks, Sovereign Debt, and Cold War Crisis in Poland, 1980–1982." Enterprise & Society 18, no. 1 (June 14, 2016): 72–107. http://dx.doi.org/10.1017/eso.2016.19.
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This article examines a familiar Cold War event, the Polish Crisis of the early 1980s, but from an unfamiliar perspective: international financial history. Historians have yet to examine how the growing international activity of Western commercial banks and the Eastern Bloc’s heavy borrowing on international capital markets during the 1970s influenced the course of the late Cold War. This article covers the history of the Eastern Bloc’s largest borrower—Poland—and its road to sovereign default in 1981. It examines how financial diplomacy among banks, communist countries, and the U.S. government catalyzed the formation of the labor union Solidarność (Solidarity). Ultimately, this article speaks to an important theme in the history of U.S. capitalism since World War II; namely, how the construction of global finance influenced U.S. foreign policy. The end of the Cold War in the fall of 1989 was the result not only of communism’s loss of legitimacy among the peoples of Eastern Europe, but also its loss of creditworthiness on global financial markets.
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Wasilewska, Natalia. "The functioning of the credit market in the European Union and the consequences of legal regulations regarding the cost of credit on the example of Poland." Economic Annals-ХХI 188, no. 3-4 (May 10, 2021): 158–73. http://dx.doi.org/10.21003/ea.v188-19.
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The purpose of this work is to determine the level of financial obligations the borrower assumes when obtaining a loan in Poland, depending on the conditions under a credit agreement, circumstances related to getting and repayment of the loan. It is found that from to January 2008 to January 2021 in emerging market economies the level of credit to the non-financial sector in the percentage of GDP is increasing to 240%, in Member states of the Euro area - about 292%. The study found that in countries in the emerging market group, the level of financing increases much quickly than in Euro area. Thus, in January 2021 compared to January 2008, the level of financing (credit to non-financial sector from all sectors at market value) in emerging market economies has tripled, while in Euro area member countries this ratio increased on 33%. In Poland, the level of financing during mentioned period increased to 141.1% and as of January 2021 amounted to USD 881.8 bln. The development of bank lending is only possible if there is a transparent relationship between the banks and the borrowers that helps to minimize credit risk. The analysis of credit legislation in the EU countries made it possible to find that there is a problem with presentation of information on the calculation of the credit costs in a transparent and understandable way. It was established that the credit costs in Poland, taking into account its maximum level, can have a significant impact on the borrower’s creditworthiness and obtaining information on the «real» credit costs is necessary to make good decisions by a potential debtor. According to the results of the study, algorithms for calculating the credit cost were proposed, that make it possible to present all components of the costs and its level depending on the conditions for granting a loan. The results of the research can be used by potential borrowers before deciding to take a loan in a Poland bank to determine all the costs related to the loan. The research is in line with an idea of «economisation of law» or «financialisation of law».
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Zailani, Achmad Udin, and Nugraha Listiana Hanun. "PENERAPAN ALGORITMA KLASIFIKASI RANDOM FOREST UNTUK PENENTUAN KELAYAKAN PEMBERIAN KREDIT DI KOPERASI MITRA SEJAHTERA." Infotech: Journal of Technology Information 6, no. 1 (June 10, 2020): 7–14. http://dx.doi.org/10.37365/it.v6i1.61.
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In English :
Credit is the provision of money or bills which can be equalized with an agreement or deal between the bank and another parties that requires the borrower to pay off the debt after a certain period of time through interest. Before the cooperative approves the credit proposed by the debtor, the cooperative conducts a credit analysis of borrowers whether the credit application is approved or disapproved. This study objectives to predict creditworthiness by applying the Random Forest Classification Algorithm in order to provide a solution for determining the creditworthiness.This research method is absolute experimental research that leads to the impact resulting from experiments on the application of the decision tree model of the Random Forest Classification Algorithm’s approach. The study results using the Random Forest Classification Algorithm’s are able to analyze problem credit and disproblems debtors with an accuracy value of 87.88%. Besides that,. decision tree model was able to improve the accuracy in analyzing the credit worthiness of borrowers who filed.
In Indonesian :
Kredit adalah penyediaan uang atau tagihan yang dapat dipersamakan atas persetujuan atau kesepakatan pinjam meminjam antara bank dengan pihak lain yang mewajibkan pihak peminjam melunasi utangnya setelah jangka waktu tertentu dengan pemberian bunga. Koperasi Mitra Sejahtera menghadapi masalah pembayaran pihak peminjam atas tunggakan kredit. Penelitian ini bertujuan untuk memprediksi kelayakan kredit dengan penerapan Algoritma Klasifikasi Random Forest agar dapat memberikan solusi untuk penentuan kelayakan pemberian kredit. Metode penelitian ini adalah riset eksperimen absolut yang mengarah kepada dampak yang dihasilkan dari eksperimen atas penerapan model pohon keputusan menggunakan pendekatan Algoritma Klasifikasi Random Forest. Hasil pengujian dengan algoritma klasifikasi Random Forest mampu menganalisis kredit yang bermasalah dan yang debitur yang tidak bermasalah dengan nilai akurasi sebesar 87,88%. Di samping itu, model pohon keputusan ternyata mampu meningkatkan akurasi dalam menganalisis kelayakan kredit yang diajukan calon debitur.
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Manzilati, Asfi, and Silvi Asna Prestianawati. "Informal financing or debt traps: are the UN sustainable development goals being met in emerging economies?" Review of International Business and Strategy 32, no. 1 (November 17, 2021): 132–45. http://dx.doi.org/10.1108/ribs-01-2021-0011.
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Purpose This paper aims to provide new insights into the financing system used in emerging economies and how they related to UN Development Goals for sustainable development. The study focuses on small businesses’ informal financing options and whether these lead the borrower into a debt trap. Design/methodology/approach The study uses the example of small-medium fisheries in Indonesia to highlight the formal/informal financing options availed by the businesses and their relationship with the lender. The authors use the qualitative method with a phenomenology approach and interview key stakeholders in the sector. Findings The authors find that the set interest repayments and the checks and balances involved in judging the borrower’s creditworthiness make the formal due to the strict requirements. Instead, the fishermen rely on the informal financing system and borrow from the mapak – a person who lends money on the condition that the fishermen’s catch will be sold to the lender as repayment. Research limitations/implications This study focuses on the financing system in emerging economies. Using the coastal business areas in the Indonesian fishing sector, the authors highlight the informal financing system and the potential debt trap. Future research could extend and study this issue in other industries and geographic regions to test whether emerging economies meet their targets and commitments under the UN Sustainability Development Goals. Emerging markets like Indonesia have a unique model of financing system and their business structure. Three conditions are highlighted in the financing system of business in coastal areas, namely, informal financing, close market access and social capital. Originality/value This study addresses financial inclusion and whether the UN Sustainability Development Goal 8 is being met in emerging economies. The study is one of the few to address this issue and highlights that emerging economies are yet to take concrete steps to make the formal financing sector more inclusive to achieve poverty alleviation.
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Beltrame, Federico, Luca Grassetti, Maurizio Polato, and Giulio Velliscig. "The impact of ECB loan valuation metrics on third-party loan pricing: A EU firm perspective." Risk Governance and Control: Financial Markets and Institutions 10, no. 2 (2020): 45–52. http://dx.doi.org/10.22495/rgcv10i2p4.
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This paper delves into the implications for the bank behaviour about firm loan pricing conditions of the new direction undertaken by supervisory and regulatory authorities in the aftermath of the deterioration of the loan portfolio quality that hit EU banks. The 2014 AQR exercise embraces the new direction and extensively uses debt service coverage measures to assess a firm’s loan quality. We, therefore, check whether the DSCR has influenced debt pricing conditions by analysing a panel of 655 listed EU firms from 2009 to 2017. Our findings show that Z-score is unable to discriminate between high and low credit risk firms. The DSCR becomes significant only after 2014, highlighting the incremented importance of this ratio in the bank’s loan pricing determination. Our work contributes to the literature investigating third-party interdependencies with the interplay between lender-borrower relationship and loan pricing and further extends the literature on creditworthiness metrics beyond their mere default-prediction ability (Beaver, 1966; Houghton & Woodliff, 1987). Our results highlight the relevance of the DSCR in the bank’s loan pricing determination and inform firm managers about the drivers that influence the cost of debt thereby enhancing their operational and financial planning.
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Evstifeev, Andrey. "Forecasting the Risks of an Organization Operating Natural Gas Vehicles Using a Scoring Model of Logistic Regression in the Presence of Expert Restrictions." Mathematical Physics and Computer Simulation, no. 3 (December 2021): 33–44. http://dx.doi.org/10.15688/mpcm.jvolsu.2021.3.4.
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The paper proposes a method and describes a mathematical model for express analysis of the attractiveness of the operation of vehicles running on natural gas for a motor transport company. The proposed solution is based on a logistic regression scoring model used by banks to assess the creditworthiness of a borrower. To improve the quality of the results, the model is extended with a set of expert restrictions formulated in the form of rules. During the analysis, signs were identified that require quantization, since individual intervals of values ??turned out to be associated with risk in different ways. The developed mathematical model is implemented in the form of software in a high-level programming language, the information of the model is stored in a database management system and is integrated with an information system for supporting management decisions when operating vehicles on natural gas. The developed athematical model was tested on a test training sample. The test results showed a satisfactory accuracy of the proposed model at the level of 77 % without the use of expert restrictions and 79 % with their use. At the same time, the share of Type II errors was 2.7 %, and Type I errors were 7.2 %, which indicates that the model is quite conservative, and a relatively high proportion of vehicles that meet the requirements were rejected.
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Shevchenko, Volodymyr, and Liliia Lutsenko. "PECULIARITIES OF DEBT FINANCING OF THE UKRAINIAN ECONOMY." THEORETICAL AND APPLIED ISSUES OF ECONOMICS, no. 39 (2019): 16–24. http://dx.doi.org/10.17721/tppe.2019.39.2.
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The article examines the impact of capital attracted through domestic state bond on a recipient economy. It investigates the features of global borrowing, major reasons for debt growth and proves the importance of internal borrowing on the example of Ukraine. Further, the article overlooks the structure of debt capital and changes in the main groups of bond loans over the last years. It explains the reasons for changing dynamics of debt capital engaged by Ukraine through external and domestic borrowing. The research substantiates functional purpose of state bonds and their crucial role in balancing budget deficit andpost-crisis recovery of the national economy. With regard to the global cut of the interest rates, the perspective directions of further research of debt capital can be a feasibility of its cost, volatility of investors’ demand and reliability of debt attraction due to the country risk of a borrower. The growth of public debt in developing countries requires clarifying the structure of debt capital and clarifying the directions for using public debt. In a view of the above analysis, it is appropriate to conclude that the functional appropriation of OVDP funds is only in financing the budget deficit and the trade balance. Strategically important areas of debt capital use in Ukraine include restoring the liquidity of the banking sector, maintaining the functioning of key government institutions, ensuring Ukraine's defense capability and the creditworthiness of the national economy.
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Zahynailo, Yuliia, and Oleksandr Doroshenko. "Role of Credit in the Development of Ukraines Economy." Modern Economics 22, no. 1 (August 27, 2020): 18–23. http://dx.doi.org/10.31521/modecon.v22(2020)-03.
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Introduction. It is known that credit is a significant achievement of mankind. The emergence and development of credit took place on the basis of the money function as a means of circulation. The development of commodity production and the need for increased working capital are the economic reasons for the credit need. Purpose .The aim of the article is to determine the role of bank credit in the economy of Ukraine and analysis of key indicators of credit activity. Results. The dynamics of loans to residents by sectors of the economy and the types of currencies and maturities for loans were studied. Loans issued by types of economic activity were analyzed. The current enterprise lending programs in 2020, initiated by the Government of Ukraine was considered. The main directions for improving bank lending were identified. Conclusions. Following conclusions are based on the analysis of the current state of bank lending in Ukraine: – the maximum value of loans in 2018 amounting to 1,073,131 million, and the lowest in 2012 – 815,142 million; – according to the sectors of the economy, the largest share of lending is lending to non-financial corporations (70-80% depending on the year); – over the period of lending in local currency dominated loans in foreign exception is 2015; – the structure of loans according to maturity prevails in local currency short-term loans and foreign currency structure of loans according to maturity – homogeneous; – The Cabinet of the Ministry of Ukraine introduced two programs to support small and medium-sized businesses in the country: «Available loans 5-7-9%» and the program «New Money»; For the development of bank lending and the establishment of financial stability in Ukraine should: conduct active banks to attract customers to the government lending programs, in turn, a borrower for the loan according to the program, to properly open the financial statements and maintain business activity at a high level for real bank assessment of the borrower’s creditworthiness.
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Patlasov, Oleg, and Natalia Vasina. "Financial Modeling of Borrowers' Creditworthiness." Olsztyn Economic Journal 5, no. 1 (June 1, 2010): 159–73. http://dx.doi.org/10.2478/v10021-010-0013-3.
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SOLOVEI, Nadiia, Larysa TUROVA, and Yuliia PYROZHENKO. "Current methods of the enterprise’s creditability assessment." Economics. Finances. Law, no. 12/1 (December 28, 2019): 31–35. http://dx.doi.org/10.37634/efp.2019.12(1).7.
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The article is devoted to the interpretation, analysis and systematization of the methods of credit assessment of enterprises. Taking into account the current state of the economy of Ukraine, as well as the financial state of most domestic enterprises, a considerable number of non-performing loans, Ukrainian banks are trying to develop, refine and improve the process of lending to customers. The number of non-performing loans in banks' portfolios indicates that banks do not cooperate with enterprises. Today, the issue of loan repayment is very painful: unstable economic situation, declining corporate incomes, devaluation of the national currency are among the main reasons for the large number of non-performing loans. In today's context, loans cannot be provided solely on the basis of trust, the lender must have other guarantees of repayment of own funds. Therefore, any financial institution examines the borrower for creditworthiness (evaluates its ability to repay debt on time). During the writing of the article, the authors noted that the problem is the determination of quantitative standards for comparison in the analysis, because there is no single clear value of the indicators. That is why it is impossible to single out the indicator, which is due to industry affiliation, and the standards given in the economic literature, the desired values of financial ratios, do not contain industry specifics and the specifics of the enterprise. The research problem is determined by the fact that there is no unified regulatory framework for a real assessment of the financial condition of the borrowing enterprise, and accordingly, there are no comparative indicators that are minimally acceptable for a particular industry in question.
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Baimuratova, B. B., E. D. Derbisheva, I. T. Derbishev, and J. J. Asanova. "THEORETICAL BASIS FOR ESTIMATING THE CREDIT CAPACITY OF BORROWERS." Herald of KSUCTA n a N Isanov, no. 2-2021 (June 24, 2021): 263–69. http://dx.doi.org/10.35803/1694-5298.2021.2.263-269.
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The article discusses the importance and role of assessing the creditworthiness of borrowers for banking institutions, the approaches used in modern banking practice to assess the creditworthiness of borrowers.
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Burov, Pavel Dmitrievich. "Modern methods of assessing creditworthiness of borrowers – small and medium business entities." Финансы и управление, no. 1 (January 2020): 91–102. http://dx.doi.org/10.25136/2409-7802.2020.1.31737.
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The subject of this research is the methods of assessing creditworthiness of borrowers of small and medium business, which allow assessing the level of risk for the bank. The author examines the dynamics of lending to small and medium businesses over the last decade in the Russian Federation, and analyzes the level of bad debt in the small and medium business loans credit portfolio. Critical analysis is conducted on the modern Russian and foreign methods of assessing creditworthiness of borrowers belonging to small and medium business, as well as highlights their merits and flaws. The author concludes on the fact of absence of a universal efficient method of assessing creditworthiness of small and medium business in Russian practice, overlapping of most of the indicators in the examined approaches, accent on qualitative indexes of the assessment of creditworthiness, and presence of subjective factor in the methodologies. The scientific novelty consists in substantiation of the list of absolute and relative indicators with consideration of existing research on this topic, in order to form express assessment of the creditworthiness of small and medium business, the integral indicator of which can be gained on the bases of taxonomic analysis. Improvements to the methodology of assessing creditworthiness of small and medium business can jump start development of lending to entities of small and medium entrepreneurship.
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Hjouji, Zaynab, and Mohamed M’hamdi. "A New Predictive Machine-learning Approach for Detecting Creditworthiness of Borrowers." International Journal of Circuits, Systems and Signal Processing 16 (April 6, 2022): 964–73. http://dx.doi.org/10.46300/9106.2022.16.118.
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We present in this paper a new approach for predicting creditworthiness of borrowers that we call “Method of splitting the learning set into two region”. The aim of this approach consists on the construction of two regions from a learning set, the first called "Solvency Region" that contains the feature vectors of the elements that have paid their financial obligations on time and the second one called "Non-Solvency Region", which contains the feature vectors of the elements that have defaulted in paying their debts. Therefore, to predict creditworthiness borrowers, it is sufficient to identify which of the two regions includes his feature vectors; if it doesn’t correspond to any region, the credit decision-making requires further analysis. To develop and test our predictive proposed approach, a large set of real and recent credit data obtained from the UCI repository is used, we trained also on a real credit database from a Moroccan bank and the creditworthiness of borrowers are analyzed using two performance measurement indicators such as Classification accuracy and the AUC of the ROC curve as a robustness measurement criteria. The proposed model was compared to three traditional machine-learning algorithms: LR, RBF-NN and the MLP-NN. The experimental results show the improved performance of our proposed predictive method for predicting creditworthiness of borrowers.
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Sidorin, A. A., A. A. Polyakova, A. B. Dudareva, and N. Y. Kozhanchikova. "IMPROVED METHODS OF ASSESSING THE CREDITWORTHINESS OF POTENTIAL BORROWERS." Russian Journal of Agricultural and Socio-Economic Sciences 67, no. 7 (July 31, 2017): 102–7. http://dx.doi.org/10.18551/rjoas.2017-07.11.
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Lanzarini, Laura Cristina, Augusto Villa Monte, Aurelio F. Bariviera, and Patricia Jimbo Santana. "Simplifying credit scoring rules using LVQ + PSO." Kybernetes 46, no. 1 (January 9, 2017): 8–16. http://dx.doi.org/10.1108/k-06-2016-0158.
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Purpose One of the key elements in the banking industry relies on the appropriate selection of customers. To manage credit risk, banks dedicate special efforts to classify customers according to their risk. The usual decision-making process consists of gathering personal and financial information about the borrower. Processing this information can be time-consuming, and presents some difficulties because of the heterogeneous structure of data. Design/methodology/approach This paper presents an alternative method that is able to generate rules that work not only on numerical attributes but also on nominal ones. The key feature of this method, called learning vector quantization and particle swarm optimization (LVQ + PSO), is the finding of a reduced set of classifying rules. This is possible because of the combination of a competitive neural network with an optimization technique. Findings These rules constitute a predictive model for credit risk approval. The reduced quantity of rules makes this method useful for credit officers aiming to make decisions about granting a credit. It also could act as an orientation for borrower’s self evaluation about her/his creditworthiness. Research limitations/implications In spite of the fact that conducted tests showed no evidence of dependence between results and the initial size of the LVQ network, it is considered desirable to repeat the measurements using an LVQ network of minimum size and a version of variable population PSO to adequately explore the solution space in the future. Practical implications In the past decades, there has been an increase in consumer credit. Retail banking is a growing industry. Not only has there been a boom in credit card memberships, specially in emerging economies, but also an increase in small consumption credits. For example, it is very common in emerging economies that families buy home appliances on installments. In those countries, the association of a home appliance shop with a financial institution is usual, to provide customers with quick-decision credit line facilities. The existence of such a financial instrument aids to boost sales. This association generates conflict of interests. On one hand, the home appliance shop wants to sell products to all customers. Therefore, it is in its best interest to promote a generous credit policy. On the other hand, the financial institution wants to maximize the revenue from credits, leading to a strict surveillance of loan losses. Having a fair and transparent credit-granting policy favors a good business relationship between home appliances shops and financial institutions. One way of developing such a policy is to construct objective rules to decide to grant or deny a credit application. Social implications Better credit decision rules generate enhanced risk sharing. In addition, it improves transparency in credit acceptance decisions, giving less room to arbitrary decisions. Originality/value This study develops a new method that combines a competitive neural network and an optimization technique. It was applied to a real database of a financial institution in a developing country.
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Ampountolas, Apostolos, Titus Nyarko Nde, Paresh Date, and Corina Constantinescu. "A Machine Learning Approach for Micro-Credit Scoring." Risks 9, no. 3 (March 9, 2021): 50. http://dx.doi.org/10.3390/risks9030050.
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In micro-lending markets, lack of recorded credit history is a significant impediment to assessing individual borrowers’ creditworthiness and therefore deciding fair interest rates. This research compares various machine learning algorithms on real micro-lending data to test their efficacy at classifying borrowers into various credit categories. We demonstrate that off-the-shelf multi-class classifiers such as random forest algorithms can perform this task very well, using readily available data about customers (such as age, occupation, and location). This presents inexpensive and reliable means to micro-lending institutions around the developing world with which to assess creditworthiness in the absence of credit history or central credit databases.
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Филобокова and L. Filobokova. "Adaptation lending mechanism and methodological approaches to assessing the creditworthiness of small businesses implementing the strategy for innovation and growth." Auditor 1, no. 3 (March 25, 2015): 85–92. http://dx.doi.org/10.12737/12781.
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Methodological approaches to assessing the creditworthiness of large and medium-sized enterprises do not provide objective opinions when appropriate estimates
of small businesses, distinctive, and the imperatives of transformation to an innovative type of reproduction necessitate the study of the adaptation mechanism
and the development of a formalized approach to the identification and differentiation of the creditworthiness, of the author’s rationale presented in this article, under
the proposed creditworthiness to understand the ability of the entity to preserve the solvency of the receipt of borrowed funds and their placement in the assets
(or to regroup liabilities) until full payment received prior lender obligations.
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Hjouji, Zaynab, and Mohamed M’hamdi. "A New Machine Learning Method for Bank Credit Risk Analysis." WSEAS TRANSACTIONS ON CIRCUITS AND SYSTEMS 21 (May 20, 2022): 108–17. http://dx.doi.org/10.37394/23201.2022.21.12.
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We present in this article a new approach to predict the creditworthiness of borrowers that we call “Method of separating the learning set into two regions”. The goal of this approach is to build two regions from a training set. Thus, to predict the solvency of borrowers, it suffices to identify which of the two regions has its characteristic vectors; if it does not correspond to any region, credit decision-making requires further analysis. To test our approach, a large set of real and recent credit data obtained from the UCI repository is used, we trained also on a real credit database of a Moroccan bank and the creditworthiness of borrowers is analyzed at using two performance measurement indicators such as classification accuracy and AUC of the ROC curve as a robustness measurement criterion. The proposed model was compared with three traditional machine learning algorithms: LR, RBF-NN and MLP-NN. The experimental results show the superiority of the proposed approach.
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Dmytryshyn, Lesia, and Ivan Blahun. "A model for achieving the allocative efficiency of credit resources in Ukraine’s banking system." Banks and Bank Systems 11, no. 3 (October 12, 2016): 8–16. http://dx.doi.org/10.21511/bbs.11(3).2016.01.
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The article presents a model for achieving the allocative efficiency of credit resources in Ukraine’s banking system. The research involves establishing a set of criteria for assessing a borrower’s creditworthiness and analyzing them by means of the discriminant analysis, Helwig’s methods, cluster analysis, the dendrite method, and principal component analysis; the methods are, then, contrasted. This is followed by designing an optimal credit portfolio of the banking system and comparing it with actual credit portfolios with the help of similarity metrics. Keywords: banking system, borrower’s creditworthiness, credit portfolio, statistical methods, similarity metrics. JEL Classification: G22, E51, C14, C18, C61
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Alferov, V. N., and V. V. Khudyakova. "MONITORING THE CREDITWORTHINESS OF BORROWERS, AS AN ANTI-CRISIS MANAGEMENT MECHANISM." Business Strategies, no. 4 (January 1, 2017): 23–34. http://dx.doi.org/10.17747/2311-7184-2017-4-23-35.
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Li, Qiang, Liwen Chen, and Yong Zeng. "The mechanism and effectiveness of credit scoring of P2P lending platform." China Finance Review International 8, no. 3 (August 20, 2018): 256–74. http://dx.doi.org/10.1108/cfri-06-2017-0156.
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Purpose The purpose of this paper is to investigate the mechanism how the platform obtains and uses undisclosed information to determine individual borrowers’ credit score and to examine the effectiveness of credit scoring in predicting default. The motivation stems from the fact that there is little evidence about the role of P2P platform, which has been positioned as a kind of information intermediary. Design/methodology/approach Using a sample of 5,176 unsecured P2P loans having expired before December 31, 2015 on Renrendai.com and an approach of two-stage regression, the paper first estimates the undisclosed information embedded in credit score by regressing credit score on four types of public information about a borrower’s creditworthiness. Then, the authors use a Logit regression to examine the role of the excess information in predicting the default probability. Findings The certification information provided by the platform is the most important determinant for a borrower’s credit score and the undisclosed information embedded in credit score can predict the loan performance better than the public information of posted listings. Moreover, the predictive ability of the undisclosed information is better for high-risk borrowers than for low-risk ones. Research limitations/implications Providing a credit score for each individual is a way for P2P platforms to play an information intermediary role. More evidence about whether or how a platform plays its role are worthy to be exploited by investigating a platform’s operating policies in detail and doing cross-platform comparative studies. Practical implications The results about the effect of various types of information on loan performance can provide an insightful guidance for P2P platforms to optimize their mechanism on information disclosure and credit scoring. Originality/value The existing literature mainly focuses on the effects of information voluntarily disclosed by borrowers and the behaviors of investors on P2P lending outcomes. The paper highlights the information intermediary role played by the platform and presents empirical evidence that credit scoring for individual borrowers is a way for P2P platforms to promote the direct lending for individual.
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НОЗИМОВ, ЭЛДОР АНВАРОВИЧ. "РАЗРАБОТКА СКОРИНГОВОЙ МОДЕЛИ ОЦЕНКИ КРЕДИТНОГО РИСКА." Archivarius 7, no. 3(57) (March 20, 2021): 45–47. http://dx.doi.org/10.52013/2524-0935-3-57-10.
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Исследовалась кредитоспособность заемщиков на основе клиентской базы банка. Было сформировано факторное пространство, позволяющее формализовать и объяснить различия между классами прежних заемщиков. Выявлены факторы, вносящие наибольший вклад в различение классов. В результате проведения дискриминантного анализа разработана скоринговая модель оценки кредитного риска, позволяющая адекватно и быстро оценить кредитоспособность потенциального клиента банка, что способствует росту конкурентоспособности на рынке кредитования. The creditworthiness of borrowers was investigated on the basis of the bank's client base. A factor space was formed to formalize and explain the differences between the classes of former borrowers. The factors that make the greatest contribution to the differentiation of classes are revealed. As a result of the discriminant analysis, a scoring model for assessing credit risk was developed, which makes it possible to adequately and quickly assess the creditworthiness of a potential client of the bank, which contributes to the growth of competitiveness in the lending market.
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Guskova, Vira G., and Petro I. Bidyuk. "Evaluating the borrower's creditworthiness of loans using data mining methods." System research and information technologies, no. 2 (June 25, 2019): 31–48. http://dx.doi.org/10.20535/srit.2308-8893.2019.2.04.
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