IIFT International Business and Management
Review Journal
group_logo
issue front

Ankita Nagpal1, Gaurav Nagpal1 and Naga Vamsi Krishna Jasti1

First Published 19 Feb 2024. https://doi.org/10.1177/jiift.231225913
Article Information Volume 1, Issue 2 December 2023
Corresponding Author:

Gaurav Nagpal, Birla Institute of Technology and Science, Pilani, Rajasthan 333031, India.
Email: gaurav19821@gmail.com

Birla Institute of Technology and Science, Pilani, Rajasthan, India

Creative Commons Non Commercial CC BY-NC: This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (http://www.creativecommons.org/licenses/by-nc/4.0/) which permits non-Commercial use, reproduction and distribution of the work without further permission provided the original work is attributed. 

Abstract

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.

Keywords

Credit rating, credit risk, Ind-Ra Ratings, prediction model, conjoint analysis, credit worthiness, non-performing loans

References

Adegbite, G. (2018). 2008 Global financial crisis-ten years after; is another crisis ‘resonating’? SSRN.

Alissa, W., Bonsall, S. B., Koharki, K. & Penn, M.W. (2013). Firms’ use of accounting discretion to influence their credit ratings. Journal of Accounting and Economics, 55(2–3), 129–147.

Ashbaugh-Skaife, H., Collins, D. W., & LaFond, R. (2006). The effects of corporate governance on firms’ credit ratings. Journal of Accounting and Economics, 42(1–2),:203–243.

Baker, T. A., Lopez, T. J., Reitenga, A. L. & Ruch, G.W. (2019). The influence of CEO and CFO power on accruals and real earnings management. Review of Quantitative Finance and Accounting, 52(1),325–345.

Bar-Isaac, H. & Shapiro, J. (2011). Credit ratings accuracy and analyst incentives. American Economic Review, 101(3), 120–124.

Batten, J., & Vo,  X. V. (2019). Determinants of bank profitability—Evidence from Vietnam. Emerging Markets Finance & Trade, 55(1), 1417–1428. https://doi.org/10.1080/1540496X.2018.1524326

Berger, A. N., Imbierowicz, B. & Rauch, C. (2016). The roles of corporate governance in bank failures during the recent financial crisis. Journal of Money, Credit and Banking, 48(4), 729–770.

Cantor, R. & Packer, F. (1995). The credit rating industry. Journal of Fixed Income, 5(3), 10–34.

CARE. (2018). CARE’s credit rating process. https://www.careratings.com/pdf/resources/CARE'sCreditRatingProcess24May2019.pdf

Chen, Z. & Wang, Z. (2021). Do firms obtain multiple ratings to hedge against downgrade risk? Journal of Banking and Finance, 123, 106006.

Chou,  T. K., & Buchdadi,  A. D. (2016). Bank performance and its underlying factors: A study of rural banks in Indonesia. Accounting and Finance Research, 5(3), 79–91. https://doi.org/doi:10.5430/afr.v5n3p55

Choudhary, M. A. & Jain, A.K. (2021). Corporate stress and bank nonperforming loans: Evidence from Pakistan. Journal of Banking and Finance, 133,106234.

Coen, J., Francis, W. B. & Rostom, M. (2019). The determinants of credit union failure: Insights from the United Kingdom. International Journal of Central Banking, 15(4), 207–240.

Colak, G. & Oztekin, Ö. (2021). The impact of COVID-19 pandemic on bank lending around the world. Journal of Banking and Finance, 133, 106207.

Cole, R. A. & White, L.J. (2017). When time is not on our side: The costs of regulatory forbearance in the closure of insolvent banks. Journal of Banking and Finance, 80, 235–249

Cornaggia, K. J., Krishnan, G. V. & Wang, C. (2017). Managerial ability and credit ratings. Contemporary Accounting Research, 34(4), 2094–2122.

CRISIL. (2020). CRISIL’s approach to financial ratios. https://www.crisil.com/mnt/winshare/Ratings/SectorMethodology/MethodologyDocs/criteria/CRISILs%20Approach%20to%

20Financial%20Ratios.pdf

Cubas-Diaz, M., & Sedano, M. A. M. (2018). Do credit ratings take into account the sustainability performance of companies? Sustainability, 10(11), 1–24. https://doi.org/10.3390/su10114272

Delis, M. D., Kim, S. -J., Politsidis, P. N., & Wu, E. (2021). Regulators vs markets: Are lending terms influenced by different perceptions of bank risk? Journal of Banking and Finance, 122, 105990.

Demirguc-Kunt, A., Pedraza, A. & Ruiz-Ortega, C. (2021). Banking sector performance during the COVID-19 crisis. Journal of Banking and Finance, 133, 106305.

Dilly, M. & Mählmann, T. (2016). Is there a boom bias in agency ratings? Review of Finance, 20(3), 979–1011. https://doi.org/10.1093/rof/rfv023

Fernando, J. M. R., Li, L. & Hou, Y. (2020). Corporate governance and correlation in corporate defaults. Corporate Governance: An International Review, 28(3), 188–206.

Ghosh, C., Hilliard, J., Petrova, M. & Phani, B.V. (2016). Economic consequences of deregulation: Evidence from the removal of the voting cap in Indian banks. Journal of Banking and Finance, 72, S19–S38.

Hale, G., Krainer, J. & McCarthy, E. (2020). Aggregation level in stress-testing models. International Journal of Central Banking, 16(4), 1–46.

Hassani, H., Huang, X., & Silva, E. (2018). Banking with blockchain-ed big data. Journal of Management Analytics, 5(4), 256–275.

Hsieh, Y. T. (2022). Financial statement readability and credit rating conservatism. Journal of Corporate Accounting and Finance, 33(1), 145–163.

Huang, H., Svec, J. & Wu, E. (2021). The game-changer: Regulatory reform and multiple credit ratings. Journal of Banking and Finance, 133, 106279.

Ind-Ra. (2019). Corporate rating methodology: Master criteria. https://www.indiaratings.co.in/Uploads/CriteriaReport/CorporateRatingMethodology.pdf

Jensen, T. L., Lando, D. & Medhat, M. (2017). Cyclicality and firm size in private firm defaults. International Journal of Central Banking, 13(4), 97–145.

Jiang, J. X., Harris Stanford, M. & Xie, Y. (2012). Does it matter who pays for bond ratings? Historical evidence. Journal of Financial Economics, 105(3), 607–621.

Kaniovski, Y. M., Boreiko, D. V., & Pflug, G. C. (2016). Numerical modeling of dependent credit rating transitions with asynchronously moving industries. Computational Economics, 49(3), 499–516. https://doi.org/10.1007/s10614-016-9576-1

Kaur, K., & Kaur, R. (2011). Credit rating in India: A study of rating methodology of rating agencies. Global Journal of Management and Business Research, 11(12), 63–68.

Kellner, R., Nagl, M. & Rösch, D. (2022). Opening the black box - Quantile neural networks for loss given default prediction. Journal of Banking and Finance, 134, 106334.

Kovner, A. & Van Tassel, P. (2021). Evaluating regulatory reform: Banks’ cost of capital and lending. Journal of Money, Credit, and Banking, 54(5), 1313–1367.

Kullaya Swamy, A. & Sarojamma, B. (2020). Bank transaction data modeling by optimized hybrid machine learning merged with ARIMA. Journal of Management Analytics, 7(4), 624–648.

Lee, W. C., Shen, J., Cheong, T. S., & Wojewodzki, M. (2021). Detecting conflicts of interest in credit rating changes: A distribution dynamics approach. Financial Innovation, 7(1), 1–23.

Liu, J., Zhang, S. & Fan, H. (2022). A two-stage hybrid credit risk prediction model based on XGBoost and graph-based deep neural network. Expert Systems with Applications, 195, 116624.

Louzis, D. P., Vouldis, A. T. & Metaxas, V.L. (2012). Macroeconomic and bank-specific determinants of non-performing loans in Greece: A comparative study of mortgage, business, and consumer loan portfolios. Journal of Banking and Finance, 36(4), 1012–1027.

Luo, R., Fang, H., Liu, J., & Zhao, S. (2019). Maturity mismatch and incentives: Evidence from bank-issued wealth management products in China. Journal of Banking and Finance, 107, 105615.

Luo, Y., Tanna, S. & De Vita, G. (2016). Financial openness, risk and bank efficiency: Cross-country evidence. Journal of Financial Stability, 24(3), 32–148. https://doi.org/10.1016/j.jfs.2016.05.003

Marshall, A., McCann, L. & McColgan, P. (2014). Do banks really monitor? Evidence from CEO succession decisions. Journal of Banking and Finance, 46(1), 118–131.

Mathis, J., McAndrews, J. & Rochet, J.-C. (2009). Rating the raters : Are reputation concerns powerful enough to discipline rating agencies? Journal of Monetary Economics, 56(5), 657–674.

Meeker, L. G. & Gray, L. (1987). A note on non-performing loans as an indicator of asset quality. Journal of Banking and Finance, 11(1), 161–168.

Merriam-Webster. (2020, April 24). Credit rating. https://www.merriam-webster.com/dictionary/credit%20rating

Nozawa, Y. & Qiu, Y. (2021). Corporate bond market reactions to quantitative easing during the COVID-19 pandemic. Journal of Banking and Finance, 133, 106153.

Otchere, I. (2009). Competitive and value effects of bank privatization in developed countries. Journal of Banking and Finance, 33(12), 2373–2385.

Ozlem Dursun-de Neef, H. & Schandlbauer, A. (2021). COVID-19 and lending responses of European banks. Journal of Banking and Finance, 133, 106236.

Pan, Y., Wang, T. Y. & Weisbach, M.S. (2018). How management risk affects corporate debt. Review of Financial Studies, 31(9), 3491–3531.

Park, C. Y. & Shin, K. (2021). COVID-19, nonperforming loans, and cross-border bank lending. Journal of Banking and Finance, 133, 106233.

Pertaia, G., Prokhorov, A. & Uryasev, S. (2021). A new approach to credit ratings. Journal of Banking and Finance, 140, 106097

Pesaran, M. H., Schuermann, T., Treutler, B. -J. & Weiner, S.M. (2006). Macroeconomic dynamics and credit risk: A global perspective. Journal of Money, Credit and Banking, 38(5), 1211–1261.

Quagliariello, M. (2007). Banks’ riskiness over the business cycle: A panel analysis on Italian intermediaries. Applied Financial Economics, 17(2), 119–138.

Rebryk, M., Rebryk, Y., Sokol, S., & Kozmenko, Y. (2017). The potential of conflicts of interest arising in the activities of credit rating agencies in Ukraine. Problems and Perspectives in Management, 15(2), 222–233. https://doi.org/10.21511/ppm.15(2-1).2017.06

Rudden, R. (2015). Evolution of credit ratings. Caribbean Information and Credit Rating Service Limited.

Saleh, I., & Afifa, M. A. (2020). The effect of credit risk, liquidity risk and bank capital on bank profitability: Evidence from an emerging market. Cogent Economics & Finance, 8(1), 1–14. DOI: 10.1080/23322039.2020.1814509

Schechtman, R. (2017). Joint validation of credit rating PDs under default correlation. International Journal of Central Banking, 13(2), 235–282.

Sopitpongstorn, N., Silvapulle, P., Gao, J. & Fenech, J.-P. (2021). Local logit regression for loan recovery rate. Journal of Banking and Finance, 126, 106093.

Tente, N., Westernhagen, N. V., & Slopek, U. (2019). M-PRESS-CreditRisk: Microprudential and macroprudential capital requirements for credit risk under systemic stress. Journal of Money, Credit and sBanking, 51(7), 1923–1961.

White, L. (2013). Credit rating agencies: An overview. Annual Review of Financial Economics, 93–122.

Ye, X., Yu, F. & Zhao, R. (2022). Credit derivatives and corporate default prediction. Journal of Banking and Finance, 138, 106418.

Yin, J., Han, B. & Wong, H.Y. (2022). COVID-19 and credit risk: A long memory perspective. Insurance: Mathematics and Economics, 104, 15–34.

Zhang, E. X., & Schloetzer, J. D. (2021). Management tenure and the quality of corporate bond ratings. Journal of Management Accounting Research, 33(3), 213–235.

Zhang, X. E. (2018). Do firms manage their credit ratings? Evidence from rating-based contracts. Accounting Horizons, 32(4), 163–183.

Zhao, Q. (2017). Do managers manipulate earnings to influence credit rating agencies’ decisions? Evidence from watchlist. Review of Accounting and Finance, 16(3), 366–384. https://doi.org/10.1108/RAF-05-2016-0078


Make a Submission Order a Print Copy