International Journal of Financial Management

K. S. Rajeev ¹, Suresh Subramoniam ²

Affiliations
1 Kerala Financial Corporation, Trivandrum, Kerala, IN
2 CET School of Management, College of Engineering, Thiruvananthapuram, Kerala, IN

Abstract

According to Reserve Bank of India (RBI) Governor, public sector banks are having stressed accounts equivalent to over Rs. 7 lakh Crores including non-performing assets (NPA) and restructured loans (News Asia, 2016). RBI has also pointed out that gross NPA of public sector banks has risen to 6.03% during June 2015 from 5.20% during March 2015. As banks have growing huge bad debts, steps are being laid down by the RBI and the government to help lending banksclean up their balance sheet by 2017. NPAs impact bank growth/stability and deteriorate profits, increase provisions, reduce reserves, affect capital adequacy, increase market borrowings, drop share values, build negative image about the economy and high interest rates. In order to compensate for the money lost in the form of interest in NPAs, banks have to charge high interest rate from other borrowers. This will have indirect impact on inflation and results in negative impact on development. Overall development of the country will also get affected due to NPA by way of unemployment, business exit due to inability to meet its loan repayment obligations, instability of the banking system, and liquidity crisis. A detailed analysis on the factors which cause NPA has become a high priority research agenda in the present day context. A questionnaire is developed for the purpose to acquire and analyse data to identify factors which cause NPA. Also, an exploratory factor analysis has been carried out to identify factors which contribute to growing NPA in financial institutions.

Purpose:

The purpose of this paper is to identify factors which cause non-performing assets in non-banking financial institutions.

Design/methodology/approach:

A questionnaire has been developed to gather data from 120 professionals who are involved in the process of granting or recovering loans in non-banking financial institutions in India and appropriate statistical techniques have been used to test for statistical significance.

Findings:

As a result of exploratory factor analysis, three components with corresponding factors are identified for the cause of non-performing assets in non-banking financial institutions. These are component 1 which is professional incapability of the borrower in running the firm leading to NPA, component 2 related to borrower nature in wilful default and his/her influential nature on financial institution and government resulting in NPA and, component 3 due to weak internal policy of the firm or external environment which aid non-repayment of loan. Component 1, component 2, and component 3 have nine factors, seven factors, and six factors associated with them, respectively, as explained in the paper.

Research limitations/implications:

The study identified the factors which are to be critically analysed prior to granting loan so that chance of the loan becoming NPA can be minimised. The success of this finding depends on suitably designed electronic credit worthiness evaluation system that evaluate the borrower.

Originality/value:

The identification of various factors which contribute to non-performing assets and to take suitable measures to control them is a high priority agenda for any financial institution and this research is directly oriented towards that direction.

Keywords

NPA, RBI, Exploratory Factor Analysis, Causes.

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Sruthy Santhosh ¹, Suresh Subramoniam ²

Affiliations
1 CET School of Management, College of Engineering, Trivandrum, Kerala, India., IN
2 College of Engineering, Trivandrum, Kerala, India, IN

Abstract

Foreign Direct Investments (FDI) and Foreign Institutional Investors (FII) provide capital for the growing Indian economy, to develop her infrastructure, such as sea ports, railways, roadways, airports, telecommunication, and other services. The present pace of industrialisation in India has also accelerated the need for foreign capital in the Indian context. The Indian stock market is continually responding to the changes in the foreign investment policies from time to time. This research analyses the impact of foreign capital investment inflow on the Indian stock market, with special reference to BSE Sensex and CNX Nifty. Statistical techniques such as correlation and multi-regression are used. The regression method used is Ordinary Least Squares (OLS) method or Auto-Regressive Distributed Lag (ARDL) Cointegration method, depending on whether the data is stationary, at level or not, with further analysis on long-run and short-run relationship among the variables studied. The research finds that there exists a weak negative correlation between FDI and Sensex, whereas a strong positive correlation exists between FDI and Nifty, as well as between FII and Sensex and FII and Nifty. Further, the variable FII shows a significant relationship with Sensex, whereas the relationship between FDI and Sensex is insignificant. FII also showed a significant positive relationship with Nifty, but the relationship between FDI and Nifty is insignificant. In summary, FII only showed a positive relation to stock movements, whereas with FDI, it was insignificant. Based on the empirical fi ndings, FDI shows only long-run relationship towards the Indian Stock markets. It is recommended that the government must attract more FDI for economic growth, through industrial growth, infrastructural developments, technological upgradations, competitive advantages, and more. On the other hand, FII are directly connected to the stock market movements and also help in the growth and development of the country, in short-run as well as the long-run. This indicates that the government must adopt appropriate measures to attract more foreign institutional investors, in order to strengthen the economic development. This research contributes to the decision-making by the government regarding the promotion of FII or FDI in short-run or long-run, for accelerating growth in the economy. This finding is highly relevant in the contemporary context, as this relationship is derived for India based on recent data.

Keywords

India, Time Series, FDI, FII, ARDL, OLS, CNX Nifty, BSE Sensex View PDF

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