Table 3 - available via license: CC BY-NC-ND
Content may be subject to copyright.
Calibration of the rating scale of S&P and probability of default.

Calibration of the rating scale of S&P and probability of default.

Source publication
Article
Full-text available
The paper is aimed at comparing the divergence of existing credit risk models and creating a synergic model with superior forecasting power based on a rating model and probability of default model of Russian banks. The paper demonstrates that rating models, if applied alone, tend to overestimate an instability of a bank, whereas probability of defa...

Context in source publication

Context 1
... scale clearly shows the non-linear pattern of PD and rating grade. In or- der to correspond the scale provided in Table 3 to the base rating's scale of this research (see Appendix Table), one exponential and two polynomial transforma- tions were applied. The results of extrapolation of PD to all numeric rating grades of the base scale are provided in Fig. 2. Fig. 2 shows that the rating scale corresponds to PD non-linearly. ...

Similar publications

Article
Full-text available
Within bank activities, which is normally defined as the joint exercise of savings collection and credit supply, risk-taking is natural, as in many human activities. Among risks related to credit intermediation, credit risk assumes particular importance. It is most simply defined as the potential that a bank borrower or counterparty fails to fulfil...
Article
Full-text available
This paper takes the credit risk management of commercial banks in China as the mainline, and puts forward a quantitative model that is suitable for the credit risk management of commercial banks in China at present – Logistic regression model, and takes a commercial bank as an example, using the regression model to conduct empirical research on th...
Article
Full-text available
The main aim of the research was to determine the key factors determining the level of credit risk of individual clients (clients in the form of natural persons, excluding companies) on the example of Polish cooperative banks according to the following features: transaction characteristics, socio-demographic characteristics of the customer, the cus...

Citations

... Le and Viviani (2018) considered 6 indicators of efficiency and concluded that this group of variables was one of the most important in predicting the banks failure. The indicators for banks' efficiency can be also met in the articles (Altman, 1968;Peresetsky, 2009;Le & Viviani, 2018;Ashbaugh-Skaife et al., 2006;Jiao et al., 2007;Karminsky & Khromova, 2018). Age and size of banks also influence on the credit risk (Alrabadi & Hamarneh, 2016;Altman & Rijken, 2004;Sahut & Mili, 2011;Gogas et al., 2014). ...
Chapter
Product development teams at ICT companies are using various innovation tools (e.g., Business Model Canvas, Lean Startup) and management methodologies (e.g., Lean Startup, Kaizen). The aim of this chapter is to align selection of innovation tools with company growth in subsequent stages of product development before and during commercialization stage. This chapter introduces a conceptual framework to be applied for creation of new ICT products by technology startups. This model describes the ICT product development path and availability of methods taking into account the product development stages. The choice of the tools and methods for development of innovative ICT products is found to be also correlated with the product IRL (innovation readiness level), choice of the growth financing (self-financing vs. venture money), and internal environment factors. The main findings of the research related to the validation of the proposed model for ICT product development by a number of emerging university spin-offs. The novelty of the research is related to introduction of relationship between currently available product development (innovation) tools and managerial processes, and the product development cycle.
Article
Assessment of borrowers' creditworthiness is the most important process affecting the activities of a modern commercial bank. Creditworthiness assessment processes occur both at the stage of decision-making to issue a credit product and during the process of regular creditworthiness assessment for the purposes of reserving and calculating economic capital. This is the reason why the commercial bank needs to develop and maintain the effective models of credit rating estimation, which are able to determine the borrower's solvency accurately and steadily by predicting its probability of default. This examines with the problem of determining the criteria for the effectiveness of shadow rating models used to estimate the probability of default of low-default segments of bank lending. Shadow rating models can be used both for business purposes and for regulatory purposes. Depending on the goal set, a number of problems specific to this class of models arise at each stage of shadow rating model development, which form the basis for the definition of performance criteria: correct specification of data samples, harmonization of rating agencies' assessments, correct choice of calculation algorithm, satisfaction of quantitative validation criteria and validity of expert corrections. Compliance with these criteria, taking into account the established objective, allows us to conclude on the effectiveness of the obtained model.
Article
Full-text available
The subject of the research are the companies of the IT sector, as a strategically important sector in the information age. Their development of companies in the IT sector is associated with high risks and requires large volumes of investments, including attracting bank loans. In this regard, the purpose of the study was to develop an adequate sectoral methodology for rating companies in the IT sector by the level of creditworthiness risks using mathematical and statistical tools that make it possible to reliably assess the potential risks of investors. To achieve this goal, the study proposes a methodology for assessing the creditworthiness of IT companies based on a system of risk factors, which makes it possible to quantify the exposure of companies to two generalized risk groups: financial risk and business risks. Based on the cluster analysis, a rating table has been developed, according to which, depending on the calculated score, the category of the company’s creditworthiness is determined. The study concluded that the key factors affecting the creditworthiness of companies are: indicators of financial stability, return on assets, liquidity ratio, online advertising market size, as well as the share of intangible assets in the structure of assets and the amount of research costs. development and capital investments. The constructed scoring model was tested on the Mail.ru Group company (from 12.10.2021 — VK). Practical significance of the research results includes in the fact that the developed model can be applied not only for assessing creditworthiness, but also as one of the express methods of risk management in an organization.
Chapter
The analysis of the reliability of modeling the risk of default by Russian companies on bonds using boolean variables is carried out. When determining the type of Boolean variables, the operations of logical addition and logical multiplication were used, which makes it possible to take into account the ratio of the company’s liabilities and various sources of financing the company’s liabilities, such as sales proceeds, company profits, and current assets. When analyzing the applicability of complex Boolean variables, the Fisher criterion was used. A regression analysis of the effectiveness of modeling the risk of default by Russian companies on bonds has been carried out. From the whole variety of variables reflecting the financial condition of the company, we have identified those variables that can be most accurately used in the study of the risk of default by Russian companies on securities.
Article
Finans sektöründe çevrimiçi ve mobil işlemlerin sayısı ve hızının artması beraberinde farklı riskleri ve denetleme maliyetlerini de getirmiştir. Bu riskler sahtecilikten kredi riskine, veri tabanı hatalarından, operasyonel problemler ve müşteri kayıplarına kadar çok farklı alanlarda gerçekleşebilir. Bu çalışmada faktoring işlemleri için senaryo bazlı aykırılık analizi bu riskleri oluşma aşamasında ve gözetimli bir istatistiksel bir model kurmadan tespit etmeyi amaçlamaktadır. Aykırılık analizi bağlamında karakteristikleri ana kümeden büyük sapma gösteren çek, müşteri ya da müşteri temsilcisi gözlemleri aykırı olarak tanımlanmaktadır. Bu karakteristikler faktoring uzmanlarının tecrübelerine dayanılarak geliştirilen senaryo kurguları içinde seçilip bir araya getirilmiştir. Karakteristiklerin ana kümeden sapmaları Mahalanobis, Minimum Kovaryans, ve Ortogonolize Gnanadesikan- Kettenring uzaklıkları ile hesaplanmaktadır. Çalışmada kullanılan veritabanı bir faktoring şirketinin 2018-2020 arası çek faktoring işlem bilgileri ile Kredi Kayıt Bürosu Çek ve Risk raporlarını birleştirmekte ve 7 farklı senaryo kullanılarak aykırı işlemler bulunmaktadır. Kurulan modelin aykırı değer eşik seviyesinin finansal kurumun tolere edebileceği hata tespit oranları ve istihbarat bütçesi çerçevesinde nasıl ayarlanıp optimize edilebileceği de çalışmada gösterilmiştir. Geliştirilen model bankacılık, faktoring, leasing, sigortacılık alanlarındaki hemen her finansal işlemde risk taşıyan aykırı gözlemleri bulabildiği gibi finansal sektörü düzenleyici ve denetleyici kurumlar tarafından da kullanılabilir.