Probability of Default Model to Estimate Ex Ante Credit Risk

Burova, Anna; Henry, Ian; Popova, Svetlana

doi:10.31477/rjmf.202103.49

Cited by 2 publications

(1 citation statement)

References 24 publications

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“…Additionally, it constructed a probability of default (PD) model to estimate the likelihood that a borrower will enter delinquency within a one-year timeframe. The study's findings revealed noteworthy associations between the two variables (Burova et al, 2021). Also, similar studies are performed using increased financial ratios and a greater pool of companies.…”

Section: Performance Assessment Using Financial Ratiossupporting

confidence: 51%

Hybrid Approach for the Financial Assessment of Companies using Fuzzy Multi-Criteria Decision-Making and Self-Organizing Maps

Yiğit

2024

İnsan Ve Toplum Bilimleri Araştırmaları Dergisi

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This paper presents a 3-stage innovative approach for company assessment, integrating financial ratios with the Fuzzy Analytic Hierarchy Process (FAHP) and using an unsupervised artificial intelligence method, Self-Organizing Maps (SOM), for classification. Addressing the challenges of decision-making in resource allocation, the study combines accurate data with robust tools essential in turbulent economic times. FAHP, known for handling complex, uncertain information, is applied to refine the traditional company assessment methods by integrating different experts' opinions and conversion to numerical values. This study presents an innovative framework by integrating financial ratios, commonly used in company evaluation methodologies, with FAHP, which is capable of processing complex and uncertain data. The integration of financial ratios into FAHP enhances the accuracy and clarity in decision-making processes for evaluating and ranking companies while also allowing for the management of the inherent uncertainties in economic data. Furthermore, SOM, an unsupervised artificial intelligence method for company classification, is used. Net Profit Margin is the financial ratio evaluated with the highest weight among financial ratios by 0.38. After the FAHP phase, financial ratios obtained from the income statements and balance sheets of companies are multiplied by the respective weights for valuation. In the final phase, a total of 6 companies listed in the Borsa Istanbul Insurance Index are divided into 3 classes. The two companies receiving the highest valuation, AGESA (Agesa Life and Pension) and ANHYT (Anadolu Life Pension Joint Stock Company), have been classified as Class A. To show the performance of the proposed model, companies registered in the Electricity Sector XELKT registered 31 companies. Classification also performed well in that set. The paper contributes to the field by providing a detailed literature review, methodology, case study results, and discussions on the practical implications of this integrated assessment method and possible areas for further research and applications.

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Section: Performance Assessment Using Financial Ratiossupporting

confidence: 51%

Hybrid Approach for the Financial Assessment of Companies using Fuzzy Multi-Criteria Decision-Making and Self-Organizing Maps

Yiğit

2024

İnsan Ve Toplum Bilimleri Araştırmaları Dergisi

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Study of the Impact of the Pandemic on the Stability of the Russian Banking Sector

Khasyanova

2022

Vopr. stat.

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The purpose of this study is to investigate how the COVID-19 pandemic affected the stability of Russian banks. To achieve this goal, an economic and statistical analysis of the risk and liquidity indicators of the Russian banking sector for the period 2008–2020 was performed. The analysis was based on the methodology for assessing the financial stability of deposit institutions developed by the International Monetary Fund.The analysis includes the following steps: determining the level and dynamics of sustainability indicators in 2020 in comparison to the pre-pandemic levels in 2019; constructing historical trends of the indicators over the last 12 years, including the pandemic crisis, applying the Hodrick – Prescott method used in macroeconomics to filter time series; identifying deviations of the indicators’ actual values from the trends, which made it possible to detect cyclicity in the indicators’ dynamics.The findings revealed that the pandemic crisis of 2020 did not lead to a deterioration in the stability of the Russian banking sector, moreover, the liquidity risk indicators improved in comparison to the pre-crisis period. At the same time, the historical trends for the period 2008–2020 showed an increase in risks in the banking sector, however, this was caused by a sharp "outlier" of risk indicators during the previous crises of 2009 and 2015. The identified deviations of the indicators from the trends allowed us to conclude that the risk raises and the liquidity increases in the sector during recession of the credit cycle and crises, and vice versa during the cycle expansion and credit boom, with the exception of 2016–2018 and 2020, which is explained, respectively, by the structural changes in the banking sector and the pandemic crisis. The results of this study could be valuable for analysts and regulators in the course of macroeconomic analysis and forecasting, as well as for banks when improving internal risk management procedures to address the economic cyclicity concern.

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Probability of Default Model to Estimate Ex Ante Credit Risk

Cited by 2 publications

References 24 publications

Hybrid Approach for the Financial Assessment of Companies using Fuzzy Multi-Criteria Decision-Making and Self-Organizing Maps

Hybrid Approach for the Financial Assessment of Companies using Fuzzy Multi-Criteria Decision-Making and Self-Organizing Maps

Study of the Impact of the Pandemic on the Stability of the Russian Banking Sector

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