scholarly journals Asymmetry in Empowering and Disempowering Private Intermediaries

Author(s):  
Andreas Kruck

This article analyzes the empowerment and disempowerment of credit rating agencies (CRAs) as private regulatory intermediaries. Until the recent financial crisis, regulators heavily relied on private credit ratings to impose risk-sensitive requirements on financial market actors (targets). Regulatory use of credit ratings was instrumental in empowering CRAs because regulatory authority was delegated to them and their own private power was bolstered by public endorsement. But regulators’ subsequent efforts to disempower the CRAs—more recently regarded as dysfunctional “runaway” intermediaries—have proven costly, complicated to do, and hardly consequential in limiting CRAs’ de facto power. This dynamic reveals a path-dependent power shift in favor of private intermediaries that is more pronounced (1) the larger the intermediary’s own sources of power when an RIT arrangement is established, (2) the larger the transfer of authority to the intermediary, and (3) the longer regulators rely on the intermediary.

Banking law ◽  
2020 ◽  
Vol 6 ◽  
pp. 7-19
Author(s):  
Gulnara F. Ruchkina ◽  

Separate provisions of the law regulating the activities of credit rating agencies are analyzed. Attention is drowned to the implementation of the provisions of this law, which is implemented by by-laws of the Bank of Russia. Examples of ratings assigned to banks by financial supermarkets are given, as well as up-to-date information in the form of tables about credit ratings assigned to banks. It are concluded that the ratings assigned to banks are more informative in comparison with the financial indicators of banks posted on official websites, as part of the assessment of their financial reliability.


Author(s):  
Natalia Besedovsky

This chapter studies calculative risk-assessment practices in credit rating agencies. It identifies two fundamentally different methodological approaches for producing ratings, which in turn shape the respective conceptions of credit risk. The traditional approach sees ‘risk’ as an only partially calculable and predictable set of hazards that should be avoided or minimized. This approach is particularly evident in the production of country credit ratings and gives rise to ordinal rankings of risk. By contrast, structured finance rating practices conceive of ‘risk’ as both fully calculable and controllable; they construct cardinal measures of risk by assuming that ontological uncertainty does not exist and that models can capture all possible events in a probabilistic manner. This assumption—that uncertainty can be turned into measurable risk—is a necessary precondition for structured finance securities and has become an influential imaginary in financial markets.


2017 ◽  
Author(s):  
Ulrich G. Schroeter

Journal of Applied Research in Accounting and Finance, Vol. 6, No. 1 (2011), pp. 14-30As demonstrated by the market reactions to downgrades of various sovereign credit ratings in 2011, the credit rating agencies occupy an important role in today’s globalized financial markets. This article provides an overview of the central characteristics of credit ratings and discusses risks arising from both their widespread use as market information and from the increasing references to credit ratings contained in laws, legal regulations and private contracts.


Author(s):  
Mathias Dewatripont ◽  
Jean-Charles Rochet ◽  
Jean Tirole

This introductory chapter begins by briefly setting out the book's purpose, which is to offer a perspective on what happened during the recent financial crisis and especially on the lessons to be learned in order to avoid a repetition of this large-scale meltdown of financial markets, industrial recession, and public deficits. It then provides a historical perspective on the regulation of the banking sector, followed by discussions of the challenges facing prudential regulation and the development of an adaptive regulatory system in a global world. It argues that the previous trend toward decreasing capital requirements and increasing delegation of oversight to banks and credit-rating agencies clearly requires a correction, namely a strengthening of regulation. In the recent crisis, the pendulum can be expected to swing in this direction.


2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Misheck Mutize ◽  
McBride Peter Nkhalamba

PurposeThis study is a comparative analysis of the magnitude of economic growth as a key determinant of long-term foreign currency sovereign credit ratings in 30 countries in Africa, Europe, Asia and Latin America from 2010 to 2018.Design/methodology/approachThe analysis applies the fixed effects (FE) and random effects (RE) panel least squares (PLS) models.FindingsThe authors find that the magnitude economic coefficients are marginally small for African countries compared to other developing countries in Asia, Europe and Latin America. Results of the probit and logit binary estimation models show positive coefficients for economic growth sub-factors for non-African countries (developing and developed) compared to negative coefficients for African countries.Practical implicationsThese findings mean that, an increase in economic growth in Africa does not significantly increase the likelihood that sovereign credit ratings will be upgraded. This implies that there is lack of uniformity in the application of the economic growth determinant despite the claims of a consistent framework by rating agencies. Thus, macroeconomic factors are relatively less important in determining country's risk profile in Africa than in other developing and developed countries.Originality/valueFirst, studies that investigate the accuracy of sovereign credit rating indicators and risk factors in Africa are rare. This study is a key literature at the time when the majority of African countries are exploring the window of sovereign bonds as an alternative funding model to the traditional concessionary borrowings from multilateral institutions. On the other hand, the persistent poor rating is driving the cost of sovereign bonds to unreasonably high levels, invariably threatening their hopes of diversifying funding options. Second, there is criticism that the rating assessments of the credit rating agencies are biased in favour of developed countries and there is a gap in literature on studies that explore the whether the credit rating agencies are biased against African countries. This paper thus explores the rationale behind the African Union Decision Assembly/AU/Dec.631 (XXVIII) adopted by the 28th Ordinary Session of the African Union held in Addis Ababa, Ethiopia in January 2017 (African Union, 2017), directing its specialized governance agency, the African Peer Review Mechanism (APRM), to provide support to its Member States in the field of international credit rating agencies. The Assembly of African Heads of State and Government highlight that African countries are facing the challenges of credit downgrades despite an average positive economic growth. Lastly, the paper makes contribution to the argument that the majority of African countries are unfairly rated by international credit rating agencies, raising a discussion of the possibility of establishing a Pan-African credit rating institution.


2020 ◽  
Vol 8 (3) ◽  
pp. 49
Author(s):  
Vasilios Plakandaras ◽  
Periklis Gogas ◽  
Theophilos Papadimitriou ◽  
Efterpi Doumpa ◽  
Maria Stefanidou

The aim of this study is to forecast credit ratings of E.U. banking institutions, as dictated by Credit Rating Agencies (CRAs). To do so, we developed alternative forecasting models that determine the non-disclosed criteria used in rating. We compiled a sample of 112 E.U. banking institutions, including their Fitch assigned ratings for 2017 and the publicly available information from their corresponding financial statements spanning the period 2013 to 2016, that lead to the corresponding ratings. Our assessment is based on identifying the financial variables that are relevant to forecasting the ratings and the rating methodology used. In the empirical section, we employed a vigorous variable selection scheme prior to training both Probit and Support Vector Machines (SVM) models, given that the latter originates from the area of machine learning and is gaining popularity among economists and CRAs. Our results show that the most accurate, in terms of in-sample forecasting, is an SVM model coupled with the nonlinear RBF kernel that identifies correctly 91.07% of the banks’ ratings, using only 8 explanatory variables. Our findings suggest that a forecasting model based solely on publicly available financial information can adhere closely to the official ratings produced by Fitch. This provides evidence that the actual assessment procedures of the Credit Rating Agencies can be fairly accurately proxied by forecasting models based on freely available data and information on undisclosed information is of lower importance.


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