Assessment Of Creditworthiness Research Articles

The Role of Credit Rating of the Eurobond Issuers from Central and Eastern Europe

<p><strong>Theoretical background</strong>: The increase in the issuance of Eurobonds by the issuers from Central and Eastern Europe has become a reason for considering the impact of the issuer’s creditworthiness assessment on the interest rate of the coupon of the issued debt instruments.</p><p><strong>Purpose of the article</strong>: The aim of the study was to assess whether having a creditworthiness assessment from more than one agency affects the interest rate on the Eurobond coupon. This objective was achieved through the process of analysis of the ratings assigned by the rating agencies. Based on the analysis of the literature and the available data, the research hypothesis was developed and verified in an empirical study. The results were analyzed in the discussion section.</p><p><strong>Research methods</strong>: The credit ratings for the Eurobonds corporate and government issuers, announced on the issue date, have been analyzed. The analysis covered the fixed interest rate debt instruments issued in EUR in the years 2005–2020 (the first half of the year). The empirical research was carried out using the observation method, the analysis of source documents, and the method of deduction.</p><p><strong>Main findings</strong>: The results of the conducted research indicate that the coupon rate is not affected by the number of ratings given to the issuer. Due to the fact that the lowest average coupon interest in 2005–2020 was held by Eurobonds of the issuers with one credit rating, there is no need for an additional creditworthiness assessment by other agencies, and for any additional costs to be incurred by the issuer. It is one of the few studies on the Central and Eastern Europe market of which the author is aware.</p>

THE USE OF FUZZY LOGIC WHILE MODELING THE CREDITWORTHINESS OF LEGAL ENTITIES

The purpose of the article is to develop a methodological approach to support the decision-making process in determining the creditworthiness of legal entities, as well as to create economic mathematical models based on this approach using the theory of fuzzy logic and fuzzy sets. Methodology. In the author's work (Palamarchuk, 2013), 49 real financial statements (Form 1 and Form 2) of Ukrainian enterprises were selected, 25 of which were potentially bankrupt and 24 were normally operating enterprises. As a result, 7 coefficients were obtained. Here we continue our modelling and building rule base. Result of the experiment is based on statistical data of domestic enterprise. The model has been constructed with the use of theory of fuzzy logic. Considering the expert knowledge, this model helps to make decisions on whether to provide the legal entity with the loan. Practical implications. The model and methodology can be used in commercial banks of Ukraine for calculating application risks. The known models do not fit to every economy. This is the reason which provides value originality of the topic of this study, which solves the problem of creating a method that would give the most sufficient assessment of creditworthiness.

PECULIARITIES OF USING ARTIFICIAL INTELLIGENCE TECHNOLOGY BY SELF-REGULATED ORGANIZATIONS IN THE ACTIVITIES OF ENTREPRENEURIAL LAWS

Artificial intelligence technology (hereinafter — AI) is used in all areas of entrepreneurial activity. In the financial industry, marketing and marketing technology is used, the prevention of fraud and illegal actions, the assessment and verification of creditworthiness, chat bots, etc. e. A consultant robot can also apply technology if investment advisory provides large and necessary expenses. He has a positive function in this area that he is able to generate popular customers and create new customers and services. However, the technology of the robot consultant that uses AI is still at the initial stage of technology implementation, and currently there are legal, institutional and legal restrictions in providing comprehensive and specialized consulting services. Robot-oriented — advisory, basic issues, existing legal systems and security self-regulatory parameters should be identified and analyzed in order to provide basic provisions for the development of artificial intelligence technologies for business entities. Thus, the author increased the efficiency of business processes, and AI can destroy their integrity.

Methods of assessing the creditworthiness of the natural person borrower

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.

An Alternative Credit Scoring System in China's Consumer Lending Market: A System Based on Digital Footprint Data

Ever since the late 1990s, China has experienced explosive growth in consumer lending, especially in short-term consumer loans, among which, the growth rate of non-bank lending has surpassed bank lending due to the development in financial technology. On the other hand, China does not have a universal credit scoring and registration system that can guide lenders during the processes of credit evaluation and risk control, for example, an individual’s bank credit records are not available for online lenders to see and vice versa. Given this context, the purpose of this paper is three-fold. First, we explore if and how alternative digital footprint data can be utilized to assess borrower’s creditworthiness. Then, we perform a comparative analysis of machine learning methods for the canonical problem of credit default prediction. Finally, we analyze, from an institutional point of view, the necessity of establishing a viable and nationally universal credit registration and scoring system utilizing online digital footprints, so that more people in China can have better access to the consumption loan market. Two different types of digital footprint data are utilized to match with bank’s loan default records. Each separately captures distinct dimensions of a person’s characteristics, such as his shopping patterns and certain aspects of his personality or inferred demographics revealed by social media features like profile image and nickname. We find both datasets can generate either acceptable or excellent prediction results, and different types of data tend to complement each other to get better performances. Typically, the traditional types of data banks normally use like income, occupation, and credit history, update over longer cycles, hence they can’t reflect more immediate changes, like the financial status changes caused by business crisis; whereas digital footprints can update daily, weekly, or monthly, thus capable of providing a more comprehensive profile of the borrower’s credit capabilities and risks. From the empirical and quantitative examination, we believe digital footprints can become an alternative information source for creditworthiness assessment, because of their near-universal data coverage, and because they can by and large resolve the thin-file issue, due to the fact that digital footprints come in much larger volume and higher frequency.

Assessment of the borrower's credit capacity using discriminative analysis

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.

Machine Learning, Big Data and the Regulation of Consumer Credit Markets: The Case of Algorithmic Credit Scoring

Recent advances in machine learning (ML) and Big Data techniques have facilitated the development of more sophisticated, automated consumer credit scoring models — a trend referred to as 'algorithmic credit scoring' in recognition of the increasing reliance on computer (particularly ML) algorithms for credit scoring. This chapter, which forms part of the 2018 collection of short essays 'Autonomous Systems and the Law', examines the rise of algorithmic credit scoring, and considers its implications for the regulation of consumer creditworthiness assessment and consumer credit markets more broadly. The chapter argues that algorithmic credit scoring, and the Big Data and ML technologies underlying it, offer both benefits and risks for consumer credit markets. On the one hand, it could increase allocative efficiency and distributional fairness in these markets, by widening access to, and lowering the cost of, credit, particularly for 'thin-file' and 'no-file' consumers. On the other hand, algorithmic credit scoring could undermine distributional fairness and efficiency, by perpetuating discrimination in lending against certain groups and by enabling the more effective exploitation of borrowers. The chapter considers how consumer financial regulation should respond to these risks, focusing on the UK/EU regulatory framework. As a general matter, it argues that the broadly principles and conduct-based approach of UK consumer credit regulation provides the flexibility necessary for regulators and market participants to respond dynamically to these risks. However, this approach could be enhanced through the introduction of more robust product oversight and governance requirements for firms in relation to their use of ML systems and processes. Supervisory authorities could also themselves make greater use of ML and Big Data techniques in order to strengthen the supervision of consumer credit firms. Finally, the chapter notes that cross-sectoral data protection regulation, recently updated in the EU under the GDPR, offers an important avenue to mitigate risks to consumers arising from the use of their personal data. However, further guidance is needed on the application and scope of this regime in the consumer financial context.

The Effect of Governance and Corporate Social Performance on Lending Judgment and Decision

The objective of the paper is to examine the effect of governance strength on the lenders’ overall risk assessment judgment and their lending decision. It also examines whether the Corporate Social Performance (CSP) of a firm can moderate lenders’ judgment about the firms’ overall risk and decision making. This study adopts a 2x2 full factorial experimental approach to investigate the relationship. As board-related governance reforms are seen to be more frequently considered by regulators as a way to increase confidence about the reliability of the financial statement, this study assumes that it will also be an important factor of consideration for lenders for approving loan assessments. Study results show that board governance strength does not affect the loan assessment significantly, but Corporate Social Performance has a significant effect on loan assessment. So, given the board strength scenario, the subjects’ loan assessment is affected by borrowers' CSP information. As a result, the corporate social image has a significant influence on lenders' creditworthiness assessment. It is concluded from the results that corporate social performance information of the borrower has more effect on loan assessment then governance strength.

Modern methods of assessing creditworthiness of borrowers – small and medium business entities

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.

Інтегральна оцінка фінансового стану та кредитоспроможності комунальних підприємств України

Інтегральна оцінка фінансового стану та кредитоспроможності комунальних підприємств України

Improving the Altman Method for Assess the Creditworthiness of Enterprises with Economic Indicators in the Form of Fuzzy Numbers

The article describes the Altman Five-factor Model to assess the creditworthiness of the enterprise with the apparatus of the theory of fuzzy sets. There were two improvements. The early method used the square integral approximation for the accurately calculating of the quantitative assessment of creditworthiness and the apparatus of fuzzy sets for ordering the sets according to the degree of confidence of the probability obtained. The new method described in this article is expanded by presenting the input data as triangular fuzzy numbers. This article describes the simulation of the credit assessment procedure and the possibility of functioning of the model as well. This approach helps to adequately assess the creditworthiness of the enterprise, also to make it possible to predict the change in the result of the model due to possible errors in the input data. The results were tested at the Krasnodar cryptic plant.

DEBTOR RATING AS A TOOL OF DEBT MANAGEMENT

IFRS 9 “Financial Instruments” introduced a new model of impairment based on expected credit losses, in which the impairment is based on expected credit losses, and the provision for losses is recognized before the credit loss, i.e. companies recognize losses immediately after initial recognition of the financial asset and revise the amount of the provision for expected credit losses at the reporting date. To create a provision for credit losses, IFRS 9 allows using several practical tools, including the rating debtors’ method. However, IFRS 9 does not express a clear opinion on how the expected credit loss for receivables should be calculated. In this regard, in our opinion, it is possible to apply an individual approach to the choice of credit risk assessment method, determining the debtor’s credit rating and the choice of the default probability, and so on. The paper substantiates that the debtors’ rating by the level of corporate default risk is a method that can reliably assess the probable risks. This method uses credit ratings. The paper proposes using the international credit ratings, which will allow a more objective creditworthiness assessment of both foreign and domestic debtors, taking into account macroeconomic factors used by rating agencies to determine the class of credit risk. The article presents the credit rating of Ukraine and changes in the credit rating of Ukraine for 15 years (2004-2019), shows the model of applying the international default probability rates. Two variants of applying this model are offered. Under the first option, the total amount of receivables from the counterparty / group of debtors is multiplied by the percentage of default probability. The second option involves applying the selected ratio according to the credit rating class at the last stage of calculating the expected credit losses by the simplified method. Due to the fact that there is no single approach to choosing the probability of default and everything relies on expert opinion, we propose using the data of the Annual Global Corporate Default And Rating, which is an analysis of market conditions in the world, the corporate defaults overview, the coefficient of bankruptcy probability of economic entities for each of the risk groups. The paper proposes using the annual rate of corporate defaults, as the expected credit losses must be calculated by companies on a regular basis and revalued at least once a year (on the balance sheet date). It is substantiated that the use of the average rate (Average Rate) to assess the probability of default, it is this rate that takes into account the past experience of companies that are in the corresponding zone of default risk for all the periods under consideration.

Framing Duties of Responsible Credit Policies in EU Law

Scope of this paper is to highlight the areas of private law in which policies aiming at the promotion of ‘responsible credit’ have been implemented, especially after the 2007-2008 financial crisis. Within the wider array of tools at the disposal of legislators for establishing these duties, the paper focuses on a few of the most meaningful preventive instruments (such as the duty of creditworthiness assessment and duties of disclosure). It then tentatively assesses the impact of some of these duties on contract law.

Bankruptcy Risk Assessment in Corporate Lending Based on Hybrid Neural Networks and Fuzzy Models

The purpose of this article is the presentation of a novel and unconventional algorithm for bankruptcy risk management in banking technologies catered towards lending to legal entities (enterprises and companies). The challenges of assessing risk in this area primarily relate to the reduction of type I and type II errors when making decisions on the terms of lending (i.e. loan amounts and repayment parameters) on the ostensibly objective basis of a borrower’s creditworthiness assessment.
 
 As such, it is necessary to use a unified procedure to select appropriate economic indicators for any bankruptcy model in order to reduce the high degree of uncertainty and noisiness of publicly available databases, and to take into consideration the specific character of knowledge-intensive, high-tech and “green” manufacturing. In order to approach this challenge, a mix of various methods is presented in this article, including credit scoring, neural simulation, a fuzzy model description, fuzzy inference rules, and a fuzzy Pospelov scale.
 
 The research results are as follows: the authors have developed an unconventional algorithm for diagnosing corporate bankruptcy stages. This algorithm is based on the application of a system-wide law relating to decreases in integrated system entropy, contrasted with the sum of entropies of the relevant collated subsystems. This algorithm has been tested on a series of experimental observations of 30 agricultural enterprises in the Sterlitamak District of the Republic of Bashkortostan. We have thusly assessed the financial condition of borrowing companies, while controlling for the probability of a wide range of indicators.
 
 Using this algorithm, the authors decided not to apply the rigorous requirements of the classical ‘least squares’ method used in regression analyses. A switch to a neural simulation approach in this algorithm necessitated an evaluation of the adequacy of the obtained model on the basis of a Bayesian approach. On the basis of this research, the authors propose that a regularisation of bankruptcy models has been achieved.

Loan officer rotation and credit access: evidence from Madagascar

PurposeWith exclusive data from a commercial microfinance institution (MFI) in Madagascar, the purpose of this paper is to investigate if loan officer rotation (change of loan officer) has an effect on credit access (loan approval) in rural and in urban areas. The authors further analyze how the frequency of loan officer rotation affects credit access in rural and in urban areas.Design/methodology/approachThe authors apply propensity score matching to compare credit access between loan applicants who experienced loan officer rotation and loan applicants who experienced no loan officer rotation in rural and in urban areas.FindingsResults show that loan officer rotation has a positive and statistically significant effect on credit access. The authors observe further that loan officer rotation has a different effect on credit access in rural and in urban areas. Whilst rural loan applicants who experienced loan officer rotation are more likely to have credit access, urban loan applicants show no statistically significant effect of loan officer rotation on credit access. For the frequency effect on credit access, the authors observe that one loan officer rotation has a positive and statistically significant effect on credit access whereas results are mixed for two loan officer rotations.Research limitations/implicationsEven though the authors can show that loan officer rotation can improve credit access to loan applicants, especially in rural areas, the conditions in Madagascar are unique. Therefore, results need to be verified in other countries and institutional contexts.Practical implicationsFrom the perspective of MFI, the authors recommend that the management of MFI needs to provide better tools to loan officers to improve on the evaluation of agricultural loan products or standardize the assessment of agricultural loan products to improve on lending decisions. Further, if applicable, the authors recommend that MFI should consider using credit worthiness assessment procedures which rely less on loan officer’s judgment for loan evaluation, such as automated systems. From the perspective of loan applicants, the authors recommend that loan applicants should request for a change of loan officer if they experience successive loan applications rejection.Originality/valueTo the authors’ knowledge, this paper is the first to provide empirical evidence on the effect and frequency of loan officer rotation on credit access in Sub-Sahara Africa, and Madagascar, in particular.

Assessment of consumers’ creditworthiness

Creditworthiness assessment is a valuable tool in avoiding irresponsible lending. Both the Consumer Credit Directive and the Mortgage Credit Directive provide for the requirement of a creditworthiness assessment before the conclusion of the credit agreement. However, neither the Consumer Credit Directive nor the Mortgage Credit Directive adequately regulate the content of the information to be collected by creditors in order to assess creditworthiness, with the result that quite different approaches are followed in different Member States. At the same time, while the Mortgage Credit Directive provides clear direction as to the granting or not of the loan depending on the outcome of the assessment, the corresponding provision of the Consumer Credit Directive leaves much room for interpretation.

Modeling hard and soft facts for SMEs: Some international evidence

AbstractThis paper asks how well the use of quantitative and qualitative variables can improve the assessment of companies' creditworthiness and how this result can be influenced by the economic and financial peculiarities of countries. We harden qualitative variable measures to model soft information aimed at scoring microfirms, small, and medium‐sized firms. The structural survey covers Germany, Italy, and the UK in a sample of about 17 thousand companies observed during the financial crisis. Soft facts are determined within the balanced scorecard framework in order to find out the impact of customers, business processes, learning and growth, and financial perspectives. Our findings show that credit models integrating soft variables optimize the risk estimation, but estimates are country‐specific and should be tailored to the characteristics of each economic system.

The system of intrabank control as a way to prevent the emergence of problem loans in banks

The article determines that the legislation of Ukraine lays down the concept of priority of debtor’s rights and such a situation provoke the irresponsibility of borrowers to fulfill their obligations and puts the rights of creditors and depositors in dependence on the borrower’s credibility. The purpose of this article is to evaluate the approaches to managing problem of loans of banks and to develop the system for preventing the occurrence of such indebtedness in banking institutions through the introduction of the internal banking control system. The tasks of the research are: the determination of approaches to the management of problem indebtedness of banks; providing a description of the methods for managing problem loans with their advantages and disadvantages; the formation of elements of intra-bank control as the system aimed at preventing the emergence of doubtful debts in the future. In the course of the research, the authors apply a systematic approach (for the formation of the structure of the internal banking control system); the methods of analysis and comparison (to assess existing approaches and the methods for managing bad debts). The authors highlight two main approaches to the problem of debt management and the advantages and disadvantages of using the methods of restructuring the problem loans of Ukrainian banks in the current economic conditions are highlighted. It is concluded that in order to prevent the emergence of problem loans in the future, it is necessary for commercial banks to introduce the system of early warning of the problem debt occurrence at the stage of assessment of the borrower's creditworthiness and the issuance of a loan that can be realized by creating the effective system of internal banking control. The formation of such a system involves the determination of the following components: the subject of control; the object of control; the goals and objectives of control; control actions that are implemented through the use of control tools. The introduction of the system of internal banking control in banks will result in reducing problem loans and the amount of credit risk, increasing the profitability of credit operations.

ДІАГНОСТИКА ФІНАНСОВОГО СТАНУ ПІДПРИЄМСТВ ЯК ІНСТРУМЕНТ УПРАВЛІННЯ ФІНАНСОВОЮ БЕЗПЕКОЮ

The instability of the economy causes a high riskiness of economic activity, and, consequently, there are threats to the financial security of the enterprise. In these conditions, before the management of enterprises there are many problematic issues in assessing the financial condition of the company. The solution of these problematic issues is possible using the tools of financial analysis, which will ensure the financial security of the enterprise. The purpose of the article is to outline the methodological provisions of the financial analysis, which make it possible to carry out a diagnosis of the financial state of enterprises to manage its financial security. The research objective is to review the methods of financial analysis in the normative documents and works of predecessors; outline a financial analysis tool that will ensure the financial security of the enterprise. According to the results of the study, it was established that the diagnosis of the financial condition of the company to manage its financial security is best carried out in the following stages: phase 1. Express analysis, which involves a general assessment of the financial condition of the enterprise based on a number of indicators that characterize the enterprise from different sides; Stage 2. In-depth analysis of the financial condition of the company in the following areas: assessment of property potential; assessment of liquidity, solvency and creditworthiness; assessment of financial stability; assessment of business activity; valuation of cash flows; evaluation of financial results; performance evaluation; assessment of the probability of insolvency and bankruptcy. Prospects for further research is the development of means of computerization of calculations according to this method.

Открытая персональная интеллектуальная технология разработки и применения адаптивных методик оценки инвестиционной привлекательности и кредитоспособности предприятий

Открытая персональная интеллектуальная технология разработки и применения адаптивных методик оценки инвестиционной привлекательности и кредитоспособности предприятий