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Prediction of Financial Distress of Non-Bank Financial Institutions of
Bangladesh using Altman’s Z Score Model
ArticleinInternational Journal of Business and Management · November 2016
DOI: 10.5539/ijbm.v11n12p261
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Tania Hamid
East West University (Bangladesh)
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East West University (Bangladesh)
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Prediction of Financial Health of Non-Bank Financial Institutions of
Bangladesh using Altman’s Z” Score Model
Abstract:
The non-bank financial institutions (NBFIs) comprise a rapidly growing segment of the financial system in
Bangladesh. They are gaining increased popularity in recent times. They play a vital role in the economy. This study
attempts to predict the financial health of 15 publicly traded NBFIs of Bangladesh over five years ranging from
2011 to 2015 using Altman‟s Z” Score Model (1965). The results show that most of the sampled NBFIs are in
„Distress‟ zone, Some of sample NBFIs are nationally and internationally acclaimed for their outstanding
performances and contributions to the industrial as well as economic development of the country, but they fail to
attain the minimum score. Most of the companies are lying on the bankruptcy level. Hence, the study suggests the
stakeholders, including regulatory authorities and researchers to be more watchful of the operations of NBFIs.
Key Words: Altman Z” score, Financial Distress, Non-bank financial institutions, Stakeholders.
1. INTRODUCTION:
Non-bank financial institutions (NBFIs) are the financial institutions that provide financial services including
banking, though they do not hold a banking license. Non-bank financial institutions in Bangladesh are gaining
increased popularity in recent times. The major business of NBFIs is leasing, but some of them are diversifying into
other lines of businesses, like term lending, real-estate financing, merchant banking, equity financing, venture
capital financing, etc. These institutions are not allowed to take deposits from the public. The emergence of NBFIs
in Bangladesh is complementary to commercial banks. Started in 1981, the size of the nonbanking financial sector
has grown in both absolute and relative terms.
The NBFIs offer wide range of products and services to mitigate the financial intermediation gap and thereby, play
an important complementary role of commercial banks in the society (Shrestha, 2007; Sufian, 2008; Vittas, 1997).
According to Ahmed and Chowdhury (2007), the fundamental limitations existing in the banking sector are, in fact,
initiated the foundation of the accelerated development process of NBFIs. Hossain and Shahiduzzaman (2002)
focused on the importance of non-banking sector as a vehicle for the economic development of the country and
identifies the underlying problems existed within the sector.
Sufian (2007) opines that BFIs and NBFIs enhance the overall growth of the economy with the support of efficient
money and capital market and NBFIs plays important role in providing complementary facilities offered by the
commercial banks. Sufian (2007) also opines that with the development of health of NBFIs, health of capital market
is also increase. He also added that as the key player in the development of capital market, efficient and productive
NBFIs lead the market based economy move forward. Ahmed and Chowdhury (2007) opine that NBFIs intensify the
country‟s financial system, contribute to the economic development of the country through diversified financial
services in the market. The development, growth and the changes over time of this sector as well as its impact on the
economy have been analyzed by many researchers to evaluate the structure of this industry. Various changes in this
industry initiated by the financial reform policy make the analysis even more important to the policy makers.
In the relatively advanced economies, there are different types of non-bank financial institutions, namely, insurance
companies, finance companies, investment banks and others dealing with pension and mutual funds, though
financial innovation is blurring the distinction between different institutions. Usually, financial institutions provide
both banking and non-banking financial service packages to meet the changing requirements of the customers. The
main functions of NBFIs are to give loans and advances for industry, commerce, agriculture, housing and real estate,
carry on underwriting or acquisition business or the investment and re-investment in shares, stocks, bonds,
debentures or debenture stocks or securities issued by the government or any local authority; carry on the business
of hire purchase transactions including leasing of machinery or equipment, and use their capital to invest in
companies (Kiragu, 1993). The financial system of Bangladesh is such that NBFIs are a necessity for the sake of
economy. Though commercial banks are considered the dominants players in the financial system, they have some
structural limitations and rigidity of different regulations, such as not being able to expand their operations in all
expected areas rather being confined to a relatively limited sphere of financial services, asset-liability mismatch to
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meet long term financing with short term resources, which can create pressure on their financial base, not being able
broaden their operational horizon appreciably by offering new and innovative financial products, etc (Carmichael &
Pomcerleano, 2002). That is why NBFIs in Bangladesh emerged for supporting industrialization and economic
growth of the country.
From the very beginning, bank financial institutions (BFIs) plays very significant role in economic and
infrastructure development of Bangladesh. The history of NBFIs is a new one. But with the passage of time NBFIs
have become an integral part of the financial system of Bangladesh. NBFIs alongside the banking sector
contributing prominently in influencing and mobilizing saving for investment (Eidleman, 2007). According to Beck
and Rahman (2006), there is a positive relationship between the development of financial intermediaries and
economic growth. They also added that financial intermediaries help to control the reverse causation of economic
growth. Islam & Osman (2011) examined the long-run relationship between per capital real GDP and the NBFIs
based on Malaysian market. They revealed that there is a long run stable relationship between per capita real GDP
and the NBFIs‟ investment, trade openness, and employment. Pirtea, Iovu & Milos (2008) expressed that with the
development of NBFIs, financial system and domestic capital market also develop, that in turn contribute to the
overall economic development of the country. Vittas (1997) expressed that NBFIs creates long-term financial
resources and provides a strong stimulus to the development of capital market by creating new marketable securities
in the area of leasing, factoring and venture capital.
As the NBFIs deal with peoples‟ money and some are even publicly traded, these NBFIs must be practicing faithful
business practices and the managers of these NBFIs are trying to maximize the stakeholders‟ wealth. In light of
recent events that have taken place in Bangladesh, the importance of knowing the financial health of NBFIs is
imperative to stakeholders. The focus of this study is to check the financial soundness of NBFIs with the use of
Altman‟s Z” Score Bankruptcy Model. From traditional times, the Z score values have been constantly used for
prediction of bankruptcy. Our work is such an investigation that uses Altman Z” Scores and provides an indication
to stakeholders about the financial stability of the organizations under study.
Our work seeks to provide valuable insights into the financial condition of some of the publicly traded NBFIs. On
the ground of recent banking scandals and the uncertainty concerning future frauds, this study may help the
stakeholders to be more careful about any such banking frauds that can take place in future.
2. LITERATURE REVIEW:
The recent emergence of NBFIs as financial intermediaries is noticeable both in developed countries and in
developing countries, but the research on various issues of NBFIs remains substantially scarce (Sufian, 2008); (Kogi
2003). Empirical evidence to evaluate the development and growth of the non-banking sector stays even more
insignificant, particularly in the context of developing countries. With regard to the literature concerning the
nonbanking sector, limited number of studies has been conducted so far in Bangladesh. That is why it is imperative
to measure the financial health of NBFIs in Bangladesh to predict possible financial distress and bankruptcy.
The importance of bankruptcy prediction has become a significant concern for corporate governance, argue many
researchers such as Gilson, (1989); Gilson (1990); Datta & Iskandar-Datta,(1995). Telmoudi , Ghourabi, and
Limam, (2011) put emphasis on prediction of financial condition of firms by pointing out that the identification of
early warning signals in failing firms can deter managers from making poor investment decisions and implementing
preventative actions to offset possible future catastrophes. It is the potential bankruptcy and the consequences
associated with it that have made academic researchers from all over the world to keep developing a gigantic
number of corporate failure prediction models, based on various types of modeling techniques (Aldrich and Nelson,
2007); (Simic, Evic and Simic, 2012).. Ross, Westerfield, Jaffe, and Jordan (2007) defined financial distress as a
“situation where a firm’s operating cash flows are not sufficient to satisfy current obligations and the firm is forced
to take corrective actions.” O‟Leary (2001) argues that prediction of bankruptcy probably is one of the most
important business decision-making problems affecting the entire life span of a business as the failure result in a
high cost from the collaborators (firms and organizations), the society and the country‟s economy.
Jaisheela (2015) researched on 27 Indian leasing companies by Z score formula and revealed that 22% were in grey
zone and 27% had very strong probability to get sick. Vaziri, Bhuyan and Manuel (2012) analyzed on financial
institutions and took 100 banks as samples which are from Europe, USA and Asia. They used several models
including Z score to predict bankruptcy. Their results showed that all the models can forecast bankruptcy correctly
before filing but z-score model could predict it more accurately than the other models.
In Bangladesh, distress analysis has been done on several industries such as; banking, capital market, insurance
companies, ceramic companies (Masum & Johora, 2015), SME (Jahur & Quadir, 2012), pharmaceutical companies
(Islam & Mili, 2012), cement companies (Hossain & Moudud–Ul-Huq, 2014) and some other industries but yet not
done on NBFIs. Ahmed and Alam (2015) analyzed Z-score on 15 commercial banks of Bangladesh and find out that
most of the banks belong to distress zone. They find out that only 7% of the sample banks were in healthy financial
position in 2009 which started declining gradually and after 2011 there was none. They also revealed a transition of
the banks from the distress zone to grey zone. Mostofa, Rezina, & Hasan (2016) investigated the insolvency level
and probability to be bankrupted of the banking industry in Bangladesh. They performed their research work on 25
conventional and non-conventional commercial banks and find out a promising result compare to other research
works. 24 % of the sample banks were in safe zone and 20 % banks were in risky zone was the final findings of their
research Chowdhury and Barua (2009) used Z score model to predict the bankruptcy risk of DSE (Dhaka Stock
Exchange) listed Z category companies and their results indicated that 5 out of 53 companies are out of dangers and
forty one companies were in distress zone due to weaker managerial capacity and poor efficiency in operational
activities. They also discussed regarding the applicability of z-score model in Bangladesh. Hasan and Khanam
(2013) researched on Sadharon Bima Corporation of Bangladesh from 2007 to 2011 and find out that long term
solvency and liquidity were not satisfactory at that time to determine distress level. They also suggested some
techniques to improve the situation like; using modern techniques for asset management, modern marketing policies
etc.
The pioneer in finding the contemporary corporate failure prediction models was William H. Beaver. Beaver (1966)
carried out univariate analysis, comparing the financial ratios of 79 failed firms and 79 non-failing firms. He
examined the predictive power of thirty accounting ratios for five consecutive years leading up to the bankruptcy of
the tested firms. Beaver applied 3 criteria in selecting these ratios; widely used in past literature, good performance
of ratios in past studies and the capability of ratios to be defined as “cash flow” concept, argue Siew Bee &
Abdollahi (2011).
A limitation of Beaver‟s work is that it is based primarily on the univariate nature that only allows for one ratio used
