Effects Of Non-Recoverable And Recoverable Loans On Lending Behaviour Of Banks

Affect of nonrecoverable loans and recoverable loans on banks lending behaviour. the project must contain two or three objectives.

Topic: Affect of non recoverable loans and recoverable loans on banks’ lending behaviour

Lending behaviour of banks along with its interrelations to the financial and macroeconomic variables is a subject which has attracted increased attention recently. The classical economic fluctuations theory downplays the role within the financial markets in accounting for aggressive fluctuations, current recurring financial turbulences and ensuring macroeconomic difficulties (Soumaré and Tafolong 2017). This has facilitated banks along with their lending decisions at the centre of policy discussion. There are interrelations between bank lending, macroeconomic situations as well as financial uncertainty in an emerging economy.

The banks are observed to have a vital role in accounting for aggregate fluctuations hat has motivated several researches based on lending behaviour of banks. The recent literature present in analysing the bank’s situation is centred on two major concerns. The first concern is associated with observing whether there are some borrower categories that rely on bank lending. In this any change in the wiliness of the banks to immediately lend that impacts their spending and investment decisions. Another issue is regarding the fact that whether changes in the monetary policy has a vital role in the process of monetary transmission (Bholat et al. 2016). The fact that some borrowers are relied on banks for the financing stems from the asymmetric information which might facilitate in explaining the credit market imperfections. Information on the bank lending terms might also serve to be useful in differentiating between the “lending view” and “credit rationing” explanations of a bank credit channel. Lending views is a statement regarding the relative magnitude of shifts within the demand and supply of loans in case the recoverable and non-recoverable loan policies is tightened.

Aim:

The aim of this research is to analyse the effect of non-recoverable and recoverable loans on lending behaviour of the banks. The objectives the research is explained below:

Objectives:

To analyse the effect of non-recoverable loans on the lending behaviour of banks

To evaluate the ways in which recoverable loans impact lending behaviour of banks

To analyse the affect of non-performing loans on profitability of banks

Terms of bank lending

Davidson and Simpson (2015) evidenced that evaluation of aggregate ban balance sheets requires being supplemented with detailed information on bank lending behaviour. These researchers also focussed on the fact that the data in balance sheet regarding the value of loans might change for several reasons. For instance, while loans on the balance sheets can decrease due to the effect of restrictive monetary policy, this can also result in increase of non-performing loans or because the banks offers loans to certain financial institutions. Lin, Tai and Xie (2018) stated that information based on the bank lending might also be helpful in setting out the difference between the “lending view” and explanations on “credit rationing”. These researchers also indicated that the lending views within a statement regarding the relative shifts in magnitude regarding the demand and supply for loans in case policy is strict. Based on the lending view, the new loans volume must decline and the loan rates must increase based on market rates in case of strict policy. Such behaviour is observed indicates shifts in loan supply that are relatively more than the loan demand shifts. In contrast, Repousis (2017) stated that most theories focussed on credit rationing indicates that while the new loans volume must decline in case of strict policy, bank loan rates must increase less than market rates.

Objectives

Effect of non-recoverable loans on the lending behaviour of banks

According to Tandon, Chaturvedi and Vidyarthi (2017) the non-performing loans is concerned with one of the vital factors that results in reluctance for the banks to offer credit. In an increased non performing loans situation, the banks tend to make the credit standards tighter that is in response to decrease in credit quality. Moreover, it is also gathered that financial accelerator impacts indicate the affects of non recoverable loans on the lending behaviour of banks. Tandon, Chaturvedi and Vidyarthi (2017) evidenced that this theory is associated with the equity position of the borrowers that impacts their credit access. This explains the lending behaviour of banks along with its relationship with the cyclical fluctuations within the economy. In case the company’s net worth is enhanced, it can decrease the external finance premium for the reason that lenders anticipate lesser risk when lending it to agents of high net worth during business upturns. Lin, Tai and Xie (2018) indicated that increase in borrowers financing cost will discourage teir desires in order to undertake a negative effect on risk-adjusted interest income. This also suggests that growth of loan is a considerable driver of banks riskiness.

Lin, Tai and Xie (2018) examined the relationship between abnormal growths of loan along with risk taking bank behaviour. Their findings revealed that abnormal growth of credit over a prolonged time period might result in increase in riskiness of banks. This is supported by decrease in solvency along with an increase in the non recoverable loans ratio. Research of Tandon, Chaturvedi and Vidyarthi (2017) revealed that previous empirical investigations revealed decrease in the banks credit associated with non recoverable loans. Majority of the existing research is focussed on the effect of non recoverable loans on lending behaviour of banks within an emerging economy. Based on such concept, it can be stated that non recoverable loans blocks the interest income along with enhancing a missed opportunity of investing within the return-earning investing that impacts future profit streams.

Recoverable loans impact on lending behaviour of banks

Tandon, Chaturvedi and Vidyarthi (2017) stated that for normal and watch facilities, only general provisions of 3% and 1% of the performing outstanding loans are needed. A particular provision of 20% is needed for the sub-standard loans and the interest must be suspended. The banks’ lending behaviour is greatly relied on the quality and size of banks loan books. Lin, Tai and Xie (2018) revealed that recoverable loans form a vital component of the balance sheet of banks and any change within its composition affects the overall bank lending structure. Recoverable loans decreases the risk of bank lending that includes decreased risk exposure in consumers do not fail to repay. The decreases the risk of bad debt resulted from lending behaviour of the banks. Tandon, Chaturvedi and Vidyarthi (2017) evidenced that the performing loans results in increased growth of GDP that results in more investment. Performing loans resolves the loans that are not performing through focussing in the short term costs. Performing loans ensure effective administrative capacity along with supportive legal regimes that maintains better lending policies of banks.

Philosophical approach/paradigm

Philosophical approach/paradigm

Research philosophy is the act of identifying the different ways in which data be used, collected and analyzed in the research.  The different assumptions win the study will put forward using the research philosophy. The research philosophy is selected based on the practical implication of the research. Intepretivism, positivism, realism and pragmatism are the different types of philosophies used in academic and business research (Flick 2015). In this current study, positivism is the research philosophy that will be used. The act of deriving knowledge and facts from the observed data is known as positivism. Positivism is limited to data collection and interpretation of the collected data.  

The observations in this philosophy are quantifiable and can be analyzed by using the statistical tools. Therefore, the data in the study have to be observable and discrete. Therefore, positivism is the most appropriate method as it will facilitate in developing relevant findings using this research (Panneerselvam 2014). The study will be using quantitative analysis of data as positivism will be able to provide a better result. The study will use a mono method and according to the nature of the study it can be said this a applied research. A specific problem has been identified and identifying of the findings will help the organization in the industry to implement changes in their organizational policies. This will help in identifying the lending behavior of the banks and the ways it can changed to increase profit maximization of the banks.

There are different research approaches such as deductive, inductive and abductive. The difference between deductive and approach is defined by the significance of the hypothesis in the study.  Abductive approach introduces astonishing facts and the remaining study is used to provide valid reasons for such facts. Deductive approach is proves the theoretical concept discussed in the literature review (Silverman 2016). On the contrary, Inductive approach is used for developing new paradigms and generalizations and descriptive analysis is the basis of evaluation. In this study, as hypothesis has been formulated and the existing theories will be validated so deductive approach is the most appropriate method.  Moreover, the deductive approach will facilitate in improving the scope of observation in this study. As positivism has been chosen in the study, qualitative analysis cannot be conducted as the observations are discrete therefore, deductive approach will have to be used. The study will establish the relationship between the non recoverable and recoverable loans and lending behavior so deduction is the ideal approach.

Method for gaining access to sites, data and or informants

Research method - Qualitative or Quantitative

 The precise methods of data accumulation and analysis are described by the research design. The two different research designs are exploratory research and conclusive research. The exploratory research will explore data based on the research question and descriptive study is conducted (Smith 2015). A descriptive study will uses case study analysis and thematic analysis to analyze the data and form new theories. However, in exploratory study relevant conclusion may not be drawn. On the other hand, conclusive study will draw findings based on the conclusion and will use analytical study. Therefore, quantitative methods are used in conclusive research. In this current study, conclusive research will be used to develop relevant findings based on the research problem. The research findings will be useful in decision making of the banks facing the described issue.  Conclusive research will use statistical tests consisting of analytical techniques that are advanced to derive quantitative analysis of data. In this current study, conclusive research is the appropriate research design and quantitative analysis of data is the research strategy.

Data Collection methods 

Method for gaining access to sites, data and or informants

The study will consist of primary data analysis where data will be collected by randomly selecting respondents. Secondary data will be collected for the literature review where data from peer reviewed journals, articles and web articles will be collected.  The primary data will be collected using a survey which will consist of close ended questions. The close ended question will use likert scale which will facilitate in developing quantitative data.  However, data collected cannot be compared with qualitative data as the research consists of a single design. This is a limitation of the study as opinion of the particular set of respondents will be taken.

Sampling 

Sampling is used to choose sample respondents from the whole population. Sampling is used to reduce the huge sample size so that the complexity of data analysis can be reduced.  Moreover, analyzing large data will result in increase in the cost and time span of the project. Non-probabilistic sampling and probabilistic sampling are the two types of sampling methods. Probabilistic sampling can be divided into systematic sampling, simple random sampling, cluster sampling and stratified sampling (Taylor, Bogdan and DeVault 2015). Systematic sample selects respondents at equal intervals from the population ranging from 1to n.  Cluster sampling is a method where the sample population is developed into a cluster where multi staged sampling methods will be used to choose the sample population. Simple random sampling is the method of randomly selecting the data from the overall sample population. Stratified sampling is the method where the population is divided into groups that do not overlap and sample population is selected form each of the groups.  The different non-probabilistic sampling methods are snowball sampling, extensive sampling, judgement sampling, quota sampling and convenience sampling. Non probabilistic sampling methods are used when the population is known and small or when there is less availability of data. In this currents study, simple random sampling will be used where the sample population will be selected from 200 respondents. Initially, the data was collected from 200 different levels of employees within different banks. Randomization will be used to select 50 samples from the overall sample population in the study.

Data Analysis 

Data analysis is method of collecting raw data and developing into significant information which can be used to analyze a particular problem.  Quantitative analysis will determine the nature and degree of relationship between the independent variable and the dependent variable (Humphries 2017). The data collected will be developed into frequency tables from which graphs and charts will be developed. Regression analysis will be used to prove the developed hypothesis in the study and correlation coefficient will determine the relationship. The study will statistical tools such as Ms excel where the datasheet of the response will be developed so that it can be thoroughly analyzed.  The regression analysis will develop a regression model which will be able to explain the characteristics of the dependent variable. The nature of the relationship will help in identifying the suitable strategies that can be sued to change the perception of the banks and their lending behaviour.

Anticipated Challenges and Limitations  

The research will not be able to cover all the aspects due to the cost and time span of the project so it has some limitations attached to it.

Research Limitations

The study has used a single research design where only quantitative data analysis will be conducted. However, mixed method is a method which can provide a better result as quantitative and qualitative data can be compared to provide a different dimension to the study (Palinkas et al. 2015).  Moreover, the study will collect data from a specific location which means that the result may not hold true for the companies in a different market. The study could have presented better result if the topic was narrowed down to a particular company as would bring forth more specific results.

Ethical and Professional Issues  

Ethical practices are the key pillars of the study and the success of the study will depend on it. In this study, the privacy of the respondents will have to be maintained by keeping their anonymity. Therefore, their personal data will not be disclosed to for privacy reasons. Moreover, the data collected will not be used in other similar studies or articles (St John et al. 2016).  The respondents have been made aware of the purpose of the study so that the research objective can be maintained. Moreover, the respondents have been forced to take part in the survey and they have taken part on their own. In this currents study, the collected data will not be manipulated to obtain the desired result in the study.

Task	Week 1	Week 2	Week 3	Week 4	Week 5	Week 6	Week 7	Week 8	Week 9
Selection of topic and search for justification
Constructing literature
Selecting appropriate methods
Data collection
Data analysis and representation
Reviewing the outcomes
Conclusions and recommendations
Submitting draft of the project
Printing and final submission

 

References

Bholat, D.M., Lastra, R.M., Markose, S.M., Miglionico, A. and Sen, K., 2016. Non-performing loans: regulatory and accounting treatments of assets.

Davidson, T. and Simpson, W.G., 2015. Federal Home Loan Bank Advances and Small Business Lending.

Flick, U., 2015. Introducing research methodology: A beginner's guide to doing a research project. Sage.

Humphries, B., 2017. Re-thinking social research: anti-discriminatory approaches in research methodology. Taylor & Francis.

Lin, C., Tai, M. and Xie, W., 2018. Bank Liquidity, Small Business Lending, and Real Outcomes.

Palinkas, L.A., Horwitz, S.M., Green, C.A., Wisdom, J.P., Duan, N. and Hoagwood, K., 2015. Purposeful sampling for qualitative data collection and analysis in mixed method implementation research. Administration and Policy in Mental Health and Mental Health Services Research, 42(5), pp.533-544.

Panneerselvam, R. (2014). Research methodology. PHI Learning Pvt. Ltd..

Repousis, S., 2017. “Bad Bank” Strategy in Greek Banking Sector and Receivables from Banks under Liquidation. International Research Journal of Finance and Economics, (162).

Silverman, D. (Ed.). (2016). Qualitative research. Sage.

Smith, J.A. ed., 2015. Qualitative psychology: A practical guide to research methods. Sage.

Soumaré, I. and Tafolong, E., 2017. Risk-based capital for credit insurers with business cycles and dynamic leverage. Quantitative Finance, 17(4), pp.597-612.

St John, F., Brockington, D., Bunnefeld, N., Duffy, R., Homewood, K., Jones, J.P., Keane, A., Milner-Gulland, E.J., Nuno, A. and Razafimanahaka, J., 2016. Research ethics: assuring anonymity at the individual level may not be sufficient to protect research participants from harm.

Tandon, D., Chaturvedi, A. and Vidyarthi, H., 2017. Non-performing assets and profitability of Indian banks: an econometric study. International Journal of Business Competition and Growth, 6(1), pp.60-76.

Taylor, S.J., Bogdan, R. and DeVault, M., 2015. Introduction to qualitative research methods: A guidebook and resource. John Wiley & Sons.