Credit Rating Methodology Research Articles

Sovereign Credit Rating: Impact on Social Investment and Role in Financial Subordination

This article examines sovereign credit rating methodologies and their impact on fiscal space in developing economies. While sovereign ratings are meant to reflect default risk, the biases embedded in the rating methodologies result in overly punitive rating actions in developing economies that often limit their ability to implement countercyclical policies. In addition, with a singular focus on austerity, they tend to shift focus away from critical development priorities and social welfare spending. Using panel data of credit rating changes in 133 countries over the period 2000–2020 from Moody’s, we explored the long-term trends in the impact of ratings. Negative rating actions have been intensifying in developing economies since 2010. We found that rating changes did tend to influence fiscal priorities. Downgrades lowered the proportion of spending on health and education and increased the proportion of spending on interest payments. We situate this examination of credit ratings within the framework of the financial subordination literature. We suggest that credit ratings are a new manifestation of financial subordination and have created a new dimension in reproducing and deepening the inequalities in the global financial system. JEL Classification: B5, F34, F02

Modelling Financial Variables Using Neural Networking to Access Creditworthiness

Abstract This study examines the existing credit rating methodology proposed in the literature to explore the development of a new credit rating model based on the financial variables of the enterprise. The focus is on the period after the financial crisis of 2018. This study aims to develop a credit rating model using neural networking and tests the same for its accuracy. The goal of this study is to address the issue brought up by previous research on subjectivity in the data used to determine creditworthiness. The database for the study includes financial data up to July 2022 from December 2018. A model is created to assess an enterprise's creditworthiness using neural networking. This study first evaluated the existing credit rating models proposed in the literature. Next, based on financial data and neural networking, a model is developed. It was evident that the model developed in this study has an accuracy of 85.16% and 76.47% on train and test data respectively. There exist several models to determine the creditworthiness of borrowers but all failed to address the concern of subjectivity in the data. The model created in this study made use of cutting-edge technology such as neural networking and financial data. This paper's unique approach and model construction based on a comparison of existing models is rare in the literature and justify the originality of this paper with a practical value at the global level.

Can Credit Ratings be Modelled on the Basis of Financial Metrics? An Evidence from Ind-Ra Ratings of Indian Firms Using Conjoint Analysis Approach

The credit ratings play an important role in the allocation of capital among the enterprises, and thereby, in the growth of any economy. The different credit rating methodologies and criteria are used by different credit rating agencies, and the criteria may also differ from industry to industry. This research study tries to explore if it is possible to model credit ratings as the outcome of financial metrics. The study deploys the conjoint analysis approach to forecast the Ind-Ra ratings given to 50 firms, as a dependent variable and the key financial metrics as independent variables. First, the independent variables are computed based on financial statements. Then, the model is executed. It is found that the debt-equity ratio is negatively rated to credit rating, while the other three variables (profitability, asset turnover ratio and current ratio) are positively related to credit ratings. The study shows that financial metrics are not the only influencer of credit ratings but many subjective criteria such as future expected consumer trends, leadership overview, management aptitude and so on. Therefore, the model proposed in this study using financial statements has a 60% accuracy only because the subjective factors as mentioned above are difficult to be quantified and captured in the model as predictor variables.

Impacto do surto de COVID-19 nos ratings de crédito: aplicação da abordagem through-the-cycle

Abstract The objective of this study was to analyze how the COVID-19 crisis has affected the determinants and predictability of the domestic credit rating issued by Fitch Ratings in Argentina. Additionally, it aims to evaluate the effects of credit rating agencies using the through-the-cycle method. Given the subjective nature of credit rating categorization, researchers have developed models for explaining and predicting credit ratings. This subjectivity is significant during economic events. Therefore, it is important to investigate whether the factors that determine and predict credit ratings remained consistent before and during the COVID-19 crisis. This paper contributes significantly to understanding how the application of the through-the-cycle method affects the determinants and predictability of credit ratings in economic crises. Theapplication of the through-the-cycle method by credit rating agencies as a criterion during the COVID-19 crisis resulted in a breakdown of the usual correlation between determinants and credit rating. Understanding whether variables are permanent or transitory components is crucial for investors and borrowers to anticipate credit rating changes during economic downturns. The dependent variables are the long-term domestic credit rating categories. The independent variables are derived from the Fitch Ratings credit rating methodology and the literature, which includes quantitative and qualitative variables. The statistical methods used are ordinal logistic regression, generalized ordinal logistic regression, and support vector machines. The COVID-19 crisis was considered a transitory event due to the application of the through-the-cycle approach by rating agencies. During the pandemic, specific determinants of credit ratings are not considered due to their transitory nature. The study identifies interest coverage ratio and competitive position as transitory components. This approach led to less predictability but a more stable credit rating.

The Imperfect Science of Publicly Reported Hospital Rating Systems: Lessons From Credit Rating Agencies.

The number of publicly available hospital quality rating systems has substantially increased over the past 2 decades. These rating systems are meant to provide patients, clinicians, and payers with relevant information to select and pay differentially for better quality of care. However, there is evidence of inconsistency, unreliability, and bias in current hospital quality rating systems. Financial ratings are similarly intended to enable investors to identify stronger companies (as investment targets), and these rating systems could provide insight into strategies to improve hospital quality ratings. We evaluate the credit rating methodologies of Standard & Poor's, Moody's, and Fitch Group and propose principles to improve hospital quality rating systems through better standardized measures and the use of external audits of source data. Emulating key features of credit rating systems may advance the delivery of meaningful hospital quality ratings.

The Impact of Environmental Factors on Credit Ratings in Healthcare.

At their core, credit ratings are holistic assessments of relative credit risk, inclusive of both quantitative and qualitative factors. Environmental, social, and governance (ESG) considerations have always been implicitly incorporated in credit rating methodology as components of a hospital or health system's wider performance. More recently, however, ESG effects have been explicitly identified. While social and governance considerations are important to credit ratings, the impact of environmental factors on rating outcomes in the healthcare sector continues to expand exponentially. This movement reflects the varied ways in which climate change, resource and materials management, energy management, and water management can affect credit profiles. The shift to a lower carbon-dependent economy also presents opportunities for issuers that make meaningful transitions toward renewable energy sources.

Determination of Sovereign Credit Rating Model for European Countries

Credit rating agencies play a key role in financial markets, as they help to reduce asymmetric information among market participants via credit ratings. The credit ratings determined by the credit rating agencies reflect the opinion of whether a country can fulfil the liability or its credit reliability at a particular time. Therefore, credit ratings are a very valuable tool, especially for investors. In addition, the issue that credit rating agencies are generally criticised is that they are unsuccessful in times of financial crisis. Credit rating methodologies of credit rating agencies have been subject to intense criticism, especially after the 2007/08 Global Financial Crisis. Some of the criticised issues are that credit rating agencies’ methodologies are not transparent; they are unable to make ratings on time, and they make incorrect ratings. In order to create a more reliable credit rating methodology, the credit rating industry and the ratings determined by rating agencies need to be critically examined and further investigated in this area. For this reason, in this study credit rating model has been developed for countries. Supervisory and regulatory variables, political indicators and macroeconomic factors were used as independent variables for the sovereign credit rating model. As a result of the study, the new sovereign credit rating calculates exactly the same credit rating with Fitch Rating Agency for developed countries, but there are 1 or 2 points differences for developing countries. In order to better understand the reason for these differences, credit rating agencies need to make their methodologies more transparent and disclose them to the public.

Sovereign rating methodologies, ESG and climate change risk: an overview

We review the sovereign credit rating methodologies of three credit rating agencies (Moody’s, S&P and Fitch) and analyze how they currently accommodate climate change risk and ESG considerations. We elaborate on the differences between the three rating methodologies and critically evaluate their suitability and limitations. We propose lines of improvement with respect to the indicator selection, normalization, aggregation and weighting procedures as well as the use of the sovereign rating indicator in connection with climate change scenarios.

Global Threats as COVID-19: Improvement for the Determination of Sovereign Credit Ratings

New type of coronavirus show that economic, political and health systems of many countries worldwide are vulnerable to global threats. This experience may suggest that there is a need to reevaluate credit rating methodology for countries. Broadly speaking, these credit ratings facilitate our investment decision, so it is important that they reflect the possible risk surrounded for a particular country to the largest extent possible. In this regard, this paper is aimed to call on credit rating agencies to integrate new factors so called global threat into their methodologies. Firstly, the paper tries to explore status-quo in sovereign rating determination, makes literature review on gaps in this sphere and introduces new proposals.

未来现金流ABS风险分析：国外评级方法比较与借鉴 (Risk Analysis of Future Flow Securitization: A Comparative Study of International Rating Methodologies)

Chinese Abstract: 未来现金流证券化产品在国际资产证券化市场是一个市场份额极低的小众型市场分支，与此形成鲜明对比，这类产品在国内资产证券化市场已成为一个有显著市场份额的主流市场分支，且近年来涉及的信用风险事件频发，国内已有文献认为相关产品的信用评级虚高。本文填补了以下三个方面的研究空白：第一，比较多个国际信用评级机构对于未来现金流ABS的评级方法之异同；第二，深入介绍、剖析、解构、梳理国外未来现金流ABS评级方法；第三，从方法论比较研究的角度，识别和阐述国内未来现金流ABS信用评级存在的三个突出偏差。这三个偏差对应于本文梳理归纳出的“四大风险环节”中的前三个环节，因而可以参照相关理念进行纠正。本文详细探讨的风险分析思路，不仅适用于信用评级，对于未来现金流ABS的投资分析亦有借鉴价值。 English Abstract: Future flow securitization is an esoteric segment with a minimal market share in the international securitization market. In contrast, it has become a mainstream segment with a sizable market share in the Chinese securitization market. In recent years, China’s future flow securitization segment has witnessed multiple credit risk events, and some scholarly work have expressed opinions that the products involved in those credit risk events have overrated credit ratings. This paper is the first-ever comparative study of credit rating methodologies for future flow securitization. It also provides the Chinese audience with the first-ever comprehensive survey of international rating methodologies for future flow securitization, complete with deconstruction and synthesis. Furthermore, this paper is the first-ever research endeavor to pinpoint and analyze through a comparative lens the three prominent methodological biases in the credit rating practices of China’s future flow securitization products. Those three biases are associated with the first three modules of the four-risk-module analytical framework we summarized, which would be useful in correcting such biases. The thought process detailed in this paper is useful not only in credit rating but also in investment analysis of future flow securitization.

Novel Approaches on Sovereign Credit Ratings

Credit ratings that are transparent, impartial and reliable as well as being up to date, quickly and easily calculated will provide convenience to investors and countries. In this study, sovereign credit rating methodologies of CRAs and studies in relevant literature are examined in detail, and two dynamic methods are proposed. These models classify countries as investable or speculative in the short term. In the first model, we used stock market values and macroeconomic variables with the Normalized Least Mean Square (NLMS) algorithm. Ratings for 15 countries are determined according to the short-term domestic currency. The results that we obtained from this model are fully consistent with those of Fitch. When we compared the results with Standard and Poor’s, we obtained different results for Turkey and Portugal. In the second model, we used only stock market closing data from 40 composite indexes with the Artificial Neural Networks (ANNs). Ratings are determined according to short-term foreign currency. The results that we acquired from these two models are fully compliant with Standard and Poor's. However, when compared to the ratings of Fitch, the results differed in the case of Russia. It has been shown that contrary to standard approaches, high predictability is achievable for countries using short-term data. The suggested models are more objective and dynamic due to only short-term data being required.Â

中小企業金融의 活性化方案에 관한 硏究 : 신용평가사의 현행신용평가방법에 대한 문제제기를 기초하여

中小企業金融의 活性化方案에 관한 硏究 : 신용평가사의 현행신용평가방법에 대한 문제제기를 기초하여

A Study on the Means to Activate Financing by Small and Medium Enterprises - Based on the Problematic Issues Raised on the Current Credit Rating Methodology by Credit Rating Agencies -

A Study on the Means to Activate Financing by Small and Medium Enterprises - Based on the Problematic Issues Raised on the Current Credit Rating Methodology by Credit Rating Agencies -

Development and comparison of payment behaviour prediction models for two South African state departments

Background: No credit rating methodology currently exists for any of South Africa’s sub nationals.Aim: To develop a generic, quantitative credit rating methodology for the Department of Health and the Department of Education combined, as well as specific quantitative credit rating methodologies, for each department, individually.Setting: A comparison between generic and specific subnational credit rating methodologies to assess which fits the South African subnational environment best. Studies and results obtained from other nations were used to construct the approach.Methods: In a typical credit rating methodology, both quantitative and qualitative information is considered. In South Africa (as a developing economy), the quantitative information equates to a smaller portion of the final credit rating. A generic quantitative credit rating methodology, as well as specific credit rating methodologies, was developed. The appropriateness of these generic and specific models was tested with regards to prediction accuracies using Red, Amber or Green (RAG) statuses on a traffic light series. An illustration of the predicted versus actual ranks is provided, as well as an example to illustrate how model-predicted RAG statuses, based on quantitative information, may be overlaid with more recent qualitative information to derive a final ranking.Results: A generic, quantitative credit rating methodology for the Departments of Health and the Department of Education combined was developed, as well as specific credit rating methodologies for each department separately. The specific subnational credit rating methodology outperformed the generic methodology considerably; more precisely, the generic models predicted a maximum of 50% of the new cases correctly as opposed to the specific Health and Education models’ 78%.Conclusion: The primary contribution of this study was to develop and compare generic and specific subnational credit rating methodologies. A further contribution was to test the appropriateness of these models’ prediction accuracies using RAG statutes. The specific subnational credit rating methodology was found to outperform the generic methodology considerably.

Credit rating process

PurposeThe purpose of this paper is to analyze which key financial factors are appropriate for measuring a credit rating score for family firms. In the recent literature, there exists a vast number of studies which evaluates performance differences between family and non-family firms (NFF). However an analysis with regards to a distinction between credit rating scores of family-orientated businesses compared to their counterparts in Austria has not been examined so far.Design/methodology/approachIn order to bridge this research gap, an empirical model based on Moody’s credit rating methodology is used to address these issues. Therefore, the relevant data were taken from the 600 largest, both listed and non-listed, companies of Austria. The statistical measurements refer to a comparison of the means resulting from quantitative rating categories (profitability, leverage structure, liquidity development and firm size).FindingsThe results of this empirical research show that family firms achieve better values in profitability, leverage structure and liquidity development based on credit rating scores. Only firm size represents no significant differences between family and NFF.Originality/valueThis study will contribute to the existing literature in the academic area of family business research and offers a framework for future empirical analysis in this field. Furthermore, this paper provides important information that will help both family and NFF accomplish their financial strategies related to credit rating transitions.

A Comparison of the 'Risk Management and Own Risk and Solvency Assessment Model Act' and Insurer Ratings

The Own Risk and Solvency Assessment (ORSA) requires an increase in reporting for insurers. However, it is possible that many insurers already gather a significant amount of this information for other groups such as rating agencies. This study provides a comparison of the ORSA Summary Report requirements given in the NAIC Own Risk and Solvency Assessment (ORSA) Guidance Manual (ORSA Guidance Manual) and the information requested by ratings agencies such as A.M. Best as stated in the Credit Rating Methodology: Global Life and NonLife Insurance Edition to assess the similarities in information needed for ORSA reporting and rating agencies. We find significant similarities between ORSA reporting and the materials needed for credit rating. Given the overlap, the total cost of ORSA compliance may be less, in terms of time and effort, in preparing the ORSA Summary Report compared to firms that have not gathered information for ratings agencies. We analyze the number of insurers subject to ORSA, as well as the percentages that are both subject to ORSA and are rated by A.M. Best. We find that 69% of insurers subject to the ORSA Model Act also are rated by A.M. Best. This is roughly 72% of the insurance market by premium.

When Do Differences in Credit Rating Methodologies Matter? Evidence from High Information Uncertainty Borrowers

ABSTRACTThis study investigates whether and when differences in the credit rating agencies' methodologies result in differences in rating properties. In particular, this study focuses on differences in information processing constraints between a rating agency that utilizes qualitative analysis and direct access to borrowers' management in its rating process (Standard & Poor's) compared to one that does not (Egan Jones Ratings Company) and how these differences affect rating quality. We find that as information uncertainty about borrowers increases, Egan Jones's rating accuracy, informativeness, and timeliness decrease relative to Standard & Poor's. Our findings suggest that Egan Jones's more restricted rating methodology can lead to limitations in information processing and, thus, reductions in Egan Jones's rating quality advantage for borrowers with greater information uncertainty.JEL Classifications: G10; G24.

A proposed quantitative credit-rating methodology for South African provincial departments

The development of subnational credit-rating methodologies affords benefits for subnationals, the sovereign and its citizens. Trusted credit ratings facilitate access to financial markets and above-average ratings allow for the negotiation of better collateral and guarantee agreements, as well as for funding of, for example, infrastructure projects at superior (lower) interest rates. This paper develops the quantitative section of a credit-rating methodology for South African subnationals. The unique characteristics of South African data, their assembly, and the selection of dependent and independent variables for the linear-regression model chosen, are discussed. The methodology is then applied to the provincial Department of Health using linear regression modelling.

Credit Rating - Financial Aspects

Fund procurement is one of the key functions of a business undertaking. Because of this, credit Rating has assumed an important place in the modern and developed financial markets. It is a boon to the companies as well as investors. It facilitates the companies in raising funds in the capital market and helps the investors to select their risk-return trade off. This paper can be divided into 3 parts: 1) What is credit Rating? 2) Credit Rating Methodology and 3) Credit Rating Agencies and its symbols. The authors analyzes the significance of credit rating through this paper.

Wybrane aspekty oceny wiarygodności kredytowej państw

The purpose of this paper is to present and analyse the prevailing credit rating methodologies, as an element of due diligence process of countries, in the light of the attributes of the sovereigns and associated risks. The concept of sovereignty introduces many variables to the due diligence analysis and in particular to credit risk analysis. The multidimensional character of a sovereign and its complex decision-making process require special attention from the creditors. The prevailing methodologies stress the fact that both quantitative and qualitative elements need to be taken into consideration. Debt affordability, referring to debt size and financial ability to repay it, remains an important factor in a quantitative analysis, but not a decisive one. Qualitative elements such as the assessment of the institutional capacity become essential, since in the case of the sovereigns, the ability to repay does not necessarily imply the willingness to repay. Due diligence of IFIs goes beyond traditional credit risk assessment in the domains, where states ‘surrender’ their sovereignty to the regulation of international law, particularly in the sphere of human rights and environment.