OPTIMIZING BANK MANAGEMENT: A DYNAMIC ANALYSIS OF PROFITABILITY, CREDIT RISK, LIQUIDITY RISK, AND CAPITAL

Abstract

Purpose: For a decade long, we have seen that technological upgradation, macro economical volatility and various regulatory changes have resulted a significant impact on Indian banking industry. Those banks who wants to improve their financial status, it is very important for them to have a deep analysis on the key financial metrics and their interrelations among them. Profitability being an essential component of any businesses need to be looked carefully, that what impacts the present and future profitability of the business. Here, we will see the impact of key financial indicators, credit risk, liquidity risk and capital adequacy on the profitability of 29 banks in the particular year. Panel Vector Autoregression (PVAR) model is used to analyse 29 Indian banks for the time period of 10 years (2015-2024) this will capture both the cross sectional data and time series data respectively, which will help in forming a strong foundation for the research and findings. Design, Methodology and Approach: This research project uses Panel Vector Autoregression (PVAR) model to calculate the interrelation of the financial metrics. This econometric model can calculate both the cause and the effect on the dataset, for the endogeneity of all internal variables. This model can also calculate the impact of exogeneous variables like GDP growth, interest rates and foreign exchange rates on the dependent variable. Data from 2015 to 2024 of 29 Indian banks providing yearly ratios consisted of credit ratio, capital ratio, liquidity ratio and profitability ratio. The lag is introduced to find the impact of past year’s profitability on the current year, the Bayesian Information Criterion (BIC) and the Akaike Information Criterion (AIC) helps to choose the ideal lag for the PVAR model. Secondly, we will further run the Hausman test to find out the suitability of either the fixed effects or random effect for the model. The final result derives from the Wald test which confirms and explains the combined effect of the independent variables on the dependent variable. Findings: This research provides insights into the dynamic relation between credit risk, liquidity risk, capital structure and profitability in Indian banks. The first finding is, banks profitability gets impacted from the rising of the credit risk. The second finding says the with the increase of liquidity we can see there is a rise in the profitability, as it helps the bank to meet their short term obligations and the capital structure with ideal amount of equity shows a positive effect on the profitability as capital acts as an buffer for the banking industry in times of economic unbalances, helping the banks to meet their long term obligations. Lastly, it is found out that the credit risk and liquidity risk have a neutrality, which means there is no compulsion of variation in credit risk will result in variation in liquidity and banks can handle these risks individually. Research Limitations & Implications: The study admits several limitations even though it offers insightful information about the dynamic relationships between important financial indicators in the Indian banking industry. To completely understand the underlying mechanisms, a more coherent theoretical framework is required due to the intricacy of the dynamic interactions among the financial indicators. Future studies may concentrate on creating a framework like this, combining institutional and behavioural elements that affect bank performance. Furthermore, the study only looks at 29 banks during a ten-year period. The findings may be more broadly applicable if the dataset is expanded to cover a larger number of institutions and a longer time period. A more thorough picture of the external factors affecting bank performance may also be obtained by include other macroeconomic variables, such as unemployment and inflation rates.