Measuring financial distress of non-bank financial institutions of Bangladesh using Altman’s Z-Score model
DOI:
https://doi.org/10.37134/ibej.vol13.sp.2.2020Keywords:
Altman Z-score, NBFI, financial distress, Dhaka stock exchange, working capital, total assets, EBIT, retained earningsAbstract
Non-bank financial institutions (NBFIs) are recognized as the fundamental of a financial market as they complement the banking institutions. Since 1981, NBFIs have been playing a vital role in the economic growth of Bangladesh. Unfortunately, in the recent years most of the NBFIs have been found financially distressed. However, few NBFIs that were included in our sample claimed themselves as potential companies with sound financial performance though it was highly criticized. Therefore, the motivation for conducting this study is to examine the financial soundness of selected NBFIs using Altman’s Z score (1995). This study involved 20 NBFIs out of 23 Dhaka Stock Exchange (DSE) listed institutions, which were selected based on information availability by considering A, B and Z categories from 2014 to 2018 period. The secondary data were collected from the annual reports of the selected companies over the period. The findings are as follows: 95% of the 20 NBFIs were in distress zone during the study period and only 5% NBFIs were in safe zone during 2017-2018 period. Therefore, the analysis predicted that within the upcoming years a few of the NBFIs will be approaching bankruptcy. Finally, it is suggested that the government, respective regulatory authority, and policy makers to pay an immediate attention on mitigating the factors affecting the financial distress.
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References
https://doi.org/10.1111/jifm.12053
Aminul, M., & Osman, J. (2004). Development Impact of Non-Bank Financial Intermediaries on Economic Growth in Malaysia : An Empirical Investigation. Journal of Business, 2(14), 187–198.
Ahmed, M. N., & Chowdhury, M. I. (2007). Non-bank financial institutions in Bangladesh: An analytical review. Working Paper Series: Bangladesh Bank, Bangladesh.
Beaver, W. H. (1966). Financial ratios as predictors of failure. Journal of accounting research, 4(1966), 71-111.
Carmichael, J., & Pomerleano, M. (2002). Development and Regulation of Non-Bank Financial Institutions. The World Bank.
Deakin, E. B. (1972). A discriminant analysis of predictors of business failure. Journal of Accounting Research, Spring(1), 167-179.
Hamid, T., Akter, F., & Rab, N. B. (2016). Prediction of financial distress of non-bank financial institutions of Bangladesh using Altman’s Z score model. International Journal of Business and Management, 11(12), 261.
https://doi.org/10.5539/ijbm.v11n12p261
Hayes, S. K., Hodge, K. A., & Hughes, L. W. (2010). A Study of the efficacy of Altman’s Z To predict bankruptcy of specialty retail firms doing business in contemporary times. Economics & Business Journal, 3(1), 1–13.
Hossain, M. (2004). Development of non bank financial institutions to strengthen the financial system of Bangladesh. January, 1–21.
Iovu, L. R., & Miloo, M. C. (2008). Importance of non-banking financial institutions and of the capital markets in the economy: The case of Romania. Theoretical and Applied Economics, 05(522)(05(522)), 3–10.
Jaisheela, B. (2015). A study of financial health of leasing companies: Z-Score analysis. Journal of Business Administration and Management Sciences Research, 4(1).
http://www.apexjournal.org
Kiragu, I. M. (1991). The prediction of corporate failure using price adjusted accounting data (Doctoral dissertation, University of Nairobi).
Kogi, S. K. (2003). An analysis of the discriminant corporate failure prediction model based on stability of financial ratios (Doctoral dissertation, University of Nairobi).
Mostofa, M., Rezina, S., & Hasan, M. (2016). Predicting the financial distress in the banking industry of Bangladesh: A case study on private commercial banks. Australian Academy of Accounting and Finance Review, 2(1), 189-203.
Mustofa, S., & Fahad Noor, M. (2020). Predicting solvency of non-banking financial institutions in Bangladesh by using Springate Fulmer model. Turk Turizm Arastirmalari Dergisi, 2(1), 51–69.
https://doi.org/10.26677/tr1010.2020.427
Shrestha, M. B. (2007). Role of Non-Bank Financial Intermediation: Challenges for Central Banks in the SEACEN Countries, Research Studies, South East Asian Central Banks (SEACEN) Research and Training Centre, number rp67.
Osuala, A. E., & Odunze, C. O. (2014). Do non-bank financial institutions’ loans and advances influence economic growth? A bounds test investigation. In European Journal of Business and Management www.iiste.org ISSN (Vol. 6, Issue 27).
Online. www.iiste.org
Sakyi, P. A., Ofoeda, I., Coleman, A. K., & Abor, J. Y. (2014). Risk and performance of non-bank financial institutions. International Journal of Financial Services Management, 7(1), 19.
https://doi.org/10.1504/ijfsm.2014.062289
Samkin, G. (2012). The use of Z-scores to predict finance company collapses : A research note. 10(2), 69–83.
Siddiqui, S. A. (2012). Business bankruptcy prediction models: A significant study of the Altman’s Z-Score model. SSRN Electronic Journal, 3(1), 212–219.
https://doi.org/10.2139/ssrn.2128475
Sufian, F. (2008). Revenue shifts and non-bank financial institutions’ productivity: Empirical evidence from Malaysia. Studies in Economics and Finance, 25(2), 76–92.
https://doi.org/10.1108/10867370810879410
Uddin, S. S., & Gupta, A. D. (2012). Concentration and competition in the non-banking sector: Evidence from Bangladesh. Global Journal of Management and Business Research, 12(8), 81-88.
Vittas, D. (1997). The role of non-bank financial intermediaries in Egypt and other MENA countries. Development Research Group, World Bank.
Yim, J., & Mitchell, H. (2007). Predicting financial distress in the Australian financial service industry. Australian Economic Papers, 46(4), 375-388.
