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By Krzysztof Kil Krzysztof Kil Scilit Preprints.org Google Scholar * , Radosław Ciukaj Radosław Ciukaj Scilit Preprints.org Google Scholar and Justyna Chrzanowska Justyna Chrzanowska Scilit Preprints.org Google Scholar
The aim of the research presented in the article was to analyse the legitimacy of the use of scoring models in banking activities, together with the assessment of the effectiveness of this tool in reducing the high value of the NPL ratio in Polish cooperative banks on the example of banks belonging to the BPS S.A. association in the period between 2004 and 2020. We used a variety of research methods for this purpose including a depth review of the literature, analysis of statistical data regarding the sector of Polish cooperative banks, analysis of financial data of cooperative banks, construction of an econometric panel model, and the designing a questionnaire (which was later sent to the management board of selected cooperative banks). Our research confirmed the significant impact of the use of scoring models in lending activities on the value of the NPL ratio in cooperative banks. The analysed cooperative banks, which used the scoring models proposed by BIK in their lending activity, showed significantly lower values of the NPL ratio in each analysed year than banks that used other scoring models. Our study also confirmed the different direction of the impact of the models offered by BIK and individual scoring models on the value of the NPL ratio. We have also shown that the scoring models proposed by BIK have a statistically significant negative impact on the level of the NPL ratio, and the banks’ own scoring models have a statistically significant positive impact on the level of the NPL ratio.
Granting loans is a fundamental area for commercial banking operations. Even though this activity brings the largest income, it is also burdened with the highest risk. Thus, banks undertake a series of various actions meant to minimise its negative results. One of the most important methods aimed at limiting the credit risk and assessment of the future solvency of the borrower is the analysis of their credit check and their creditworthiness at every stage of the loan agreement (Spuchláková et al. 2015). Reliable credit check assessment is a significant matter both for the bank and the borrower. It protects both parties in the loan agreement from negative consequences resulting from a failure to repay the contracted liability. A properly conducted analysis of the credit check has, in addition, been deemed as a key condition for the stability of the financial system (Herring 1999). In their practice, banks use different methods to serve the analysis of the credit check. However, until now, a uniform template has not been created in this regard (Genriha and Voronova 2012). The provisions of the acts in force in Poland do not impose a method or the criteria for creditworthiness, something which banks ought to follow. Consequently, this practice varies significantly depending on the credit provider, which in consequence can lead to differences in the final assessment.
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The quality of credit exposure has been one of the most important issues in the banking literature for many years. It is also considered to be an important indicator in assessing the condition of banks and the entire banking sector. Deterioration in the quality of banks’ loan portfolios also represents one of the biggest threats of the COVID-19 pandemic.
Considering the changes in Europe in the level and dynamics of impaired loans, Polish cooperative banks represent a very interesting object of analysis. They comprise a group of 530 entities (a number ten times bigger than the number of commercial banks, but with only a 7.8% share of banking sector assets). These entities are highly diversified in terms of size, area of operation, and financial condition. The average level of nonperforming loans (NPL-the share of impaired loans in the bank’s total loan portfolio) at cooperative banks in Poland increased by 220% (from 2.8% to 8.8%) between 2009 and 2020. This upward trend is essentially continuous (a stabilization of values was observed between 2018 and 2020). This tendency is different than in commercial banks operating in Poland and cooperative banks in other countries with a significant role of cooperative bank sectors (Germany, France), as well as for the entire population of banks in the European Union countries. Undoubtedly, one of the reasons for this phenomenon is the fact that during the 2007–2009 crisis Polish cooperative banks sustained lending activity, entering (at the same time) into the segment of small and medium enterprises where they hardly had experience. The negative effects of decisions made at that time could be observed in subsequent years. Additionally, cooperative banks were much less interested in using scoring models (both external or their own) in the credit risk assessment process. This process may also explain the rise in the level of NPL ratio in this banking sector.
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The main objective of the paper is to assess the impact of the use of scoring models by Polish cooperative banks on the quality of their loan portfolio (measured by the NPL ratio) between 2004 and 2020. The authors try to verify two research hypotheses:
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The use of scoring models by Polish cooperative banks in the credit risk assessment process results in a statistically significant reduction in the scale of credit risk materialization;
The effectiveness of internally built scoring models by Polish cooperative banks is lower than the effectiveness of general models offered by BIK.
Biuro Informacji Kredytowej (BIK-Polish Credit Information Bureau, which is established to collect, integrate and share data on the credit history of bank customers).
Loan Default Prediction Of Chinese P2p Market: A Machine Learning Methodology
This article has been divided into three basic parts, including a literature review on the significance of scoring models in the process of mitigating bank credit risk, a description of the research method and sample, and the presentation of conclusions and recommendations resulting from the studies.
The basic tool for limiting credit risk in the banking activity on the pre-contractual and contractual stages is the credit check assessment. In the literature, two basic categories are distinguished relating to the credit check: formal and legal capacity and substantive capacity. The substantive check is a broader and more complex concept since it contains in itself two significant aspects of assessment, personal and economic (Caplinsk and Tvaronavičienė 2020). In the personal dimension of assessment, the elements are analysed that determine the confidence in a borrower himself. These characteristics include, among others, the character, family status, previous experience, acquired professional qualifications, reputation, and managerial skills. What’s more, this category of credit check also contains the ethical and moral assessment of personal responsibility and reliability of the borrower relating to the interests of the business they run. The economic dimension of the substantive capacity assessment focuses on the analysis of the mostly objectified elements that characterize the previous, current, and future financial and economic situation of the borrower (Ritonga et al. 2017).
The most common method used by banks to assess the creditworthiness of a homogeneous group of borrowers is credit scoring (Emel et al. 2003). In the functioning of any bank, this is considered to be a key element that has a real impact on future financial results. Initially, the concept of credit scoring referred only to simple expert scoring cards. However, with the development of technology, simple scoring turned into predictive models with a high degree of advancement. Credit scoring has been defined as a method of assessing the amount of credit risk of a customer who applies for a loan. By using historical data and various statistical techniques, the scoring system is designed to distinguish the impact of individual characteristics of applicants that significantly affect the timely payment of their obligations. This method generates a certain point (called a cut-off point) by means of which the bank can easily classify applicants or borrowers into groups showing a different level of risk. In order to build an effective scoring model, historical data (collected on the basis of previously granted loans) and selected features helpful in
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The use of scoring models by Polish cooperative banks in the credit risk assessment process results in a statistically significant reduction in the scale of credit risk materialization;
The effectiveness of internally built scoring models by Polish cooperative banks is lower than the effectiveness of general models offered by BIK.
Biuro Informacji Kredytowej (BIK-Polish Credit Information Bureau, which is established to collect, integrate and share data on the credit history of bank customers).
Loan Default Prediction Of Chinese P2p Market: A Machine Learning Methodology
This article has been divided into three basic parts, including a literature review on the significance of scoring models in the process of mitigating bank credit risk, a description of the research method and sample, and the presentation of conclusions and recommendations resulting from the studies.
The basic tool for limiting credit risk in the banking activity on the pre-contractual and contractual stages is the credit check assessment. In the literature, two basic categories are distinguished relating to the credit check: formal and legal capacity and substantive capacity. The substantive check is a broader and more complex concept since it contains in itself two significant aspects of assessment, personal and economic (Caplinsk and Tvaronavičienė 2020). In the personal dimension of assessment, the elements are analysed that determine the confidence in a borrower himself. These characteristics include, among others, the character, family status, previous experience, acquired professional qualifications, reputation, and managerial skills. What’s more, this category of credit check also contains the ethical and moral assessment of personal responsibility and reliability of the borrower relating to the interests of the business they run. The economic dimension of the substantive capacity assessment focuses on the analysis of the mostly objectified elements that characterize the previous, current, and future financial and economic situation of the borrower (Ritonga et al. 2017).
The most common method used by banks to assess the creditworthiness of a homogeneous group of borrowers is credit scoring (Emel et al. 2003). In the functioning of any bank, this is considered to be a key element that has a real impact on future financial results. Initially, the concept of credit scoring referred only to simple expert scoring cards. However, with the development of technology, simple scoring turned into predictive models with a high degree of advancement. Credit scoring has been defined as a method of assessing the amount of credit risk of a customer who applies for a loan. By using historical data and various statistical techniques, the scoring system is designed to distinguish the impact of individual characteristics of applicants that significantly affect the timely payment of their obligations. This method generates a certain point (called a cut-off point) by means of which the bank can easily classify applicants or borrowers into groups showing a different level of risk. In order to build an effective scoring model, historical data (collected on the basis of previously granted loans) and selected features helpful in
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