Resumo

Credit risk assessment has become a vital tool in the financial market to aid lenders and investors in their decision-making. Based on that, enhanced risk management has become crucial for organizations to improve their credit quality. In this regard, Credit Rating Agencies are essential to the market’s functionality by providing investors and lenders with a creditworthiness profile of the Companies. They do that by identifying and explaining factors that affect their credit profile, mitigating default risk, and increasing transparency and credibility in the market.

Credit rating assessment is vital for the smooth operation of the financial market. The research problem of this article is "How to effectively identify the credit risk factors in predicting corporate default and mitigating financial losses for investors. Based on that, the objective of this article is to identify and explain the variables influencing credit risk evaluation, precisely a company's capacity to fulfill its financial commitments.

1-Default risk theory: This theory suggests that credit ratings are based on the probability of default by the borrower. 2-Agency theory: This theory emphasizes the role of credit rating agencies as independent third-party evaluators who provide valuable information to investors and other stakeholders. 3-Efficient market theory: This theory assumes that financial markets are efficient and that prices reflect all available information. 4-Capital structure theory: This theory suggests that the credit rating of a company is related to its capital structure.

This study's methodology is divided into (1) Hypotheses and their underlying theoretical justifications, (2) Statistical technique, variables, and proxies employed in the study, and (3) Data collection procedures and the sample used in the study. We utilized a Generalized Estimating Equations (GEE) model to accomplish our objective considering a panel structure where the credit rating is the categorical dependent variable of interest. Additionally, we considered ten independent variables: leverage, liquidity, interest coverage, profitability, market, survival, and macroeconomic factors.

H1-excluded, H2, H3, H6 were accepted, H4, H5, H7, H8, and H9 were rejected. The variables of profitability (ROA) and market (QTobin) demonstrated statistical significance at the 1% level, while interest coverage (EBITDAICOV), market (TSR), and survival (AZS) variables were significant at the 5% level.

Of the nine independent variables examined, only five were statistically significant in explaining the dependent variable, credit ratings. EBITDAICOV, ROA, and AZS exhibited a positive coefficient with statistical significance, indicating that a 1% increase in these variables has a positive impact on credit ratings.

Adams, M., Burton, B., & Hardwick, P. (2003). The determinants of credit ratings in the United Kingdom insurance industry. Journal of Business Finance and Accounting, 30(3–4). https://doi.org/10.1111/1468-5957.00007 Agu, S. C., Onu, F. U., Ezemagu, U. K., & Oden, D. (2022). Predicting gross domestic product to macroeconomic indicators. Intelligent Systems with Applications, 14. Ali Naqvi, P. A., Sulaiman Bagaba, A. S., & Ramzani, S. R. (2018). The consumer price index as a measure of consumer price inflation. International Journal of Innovative Technology and Exploring Engineering, 8(2S).