13th Students’ Research Symposium 2023/2024

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    The Impact of Green Banking Practices on Bank Financial Performance, Study Based on Commercial Banks of Sri Lanka
    (Department of Finance, Faculty of Commerce and Management Studies, University of Kelaniya, Sri Lanka., 2025) Amarasiri, G. D. M. N.; Fernando, J. M. R.
    Introduction: This study focused on the Impact of Green Banking Practices on Bank Financial Performance Study Based on Commercial Banks of Sri Lanka. Local or foreign researchers have not done any research considering the recent effect of green banking practices by evaluating the quantitative data on financial performance. Methodology: To address the three objectives; impact of green costs on the bank’s financial performance, the impact of corporate governance and its moderate relationship between green banking practices and banks’ financial performances, the effect of country regulation, and moderate the relationship between green banking practices and the financial performance of 10 licensed commercial banks in Sri Lanka under registration in the Colombo Stock Exchange, this study uses six variables including one dependent variable, one independent variable, two moderate variables, and two control variables. The study used secondary data from banks' annual reports and worldwide Governance Indicators from 2015 to 2023 and used panel regression to analyze the data. Findings: The study found green costs are negatively significant with ROA, demonstrating that short-term costs related to green initiatives could have a negative impact on short-term financial performance. While country regulatory, and corporate governance showed a significant positive relationship with ROA. Conclusion: This research suggests that bank financial performance is significantly impacted by green cost, green governance, and green country. Strong corporate governance procedures are crucial for promoting sustainable growth.
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    Impact of Risk Management on Firms’ Financial Performance: Evidence from Licensed Commercial Banks in Sri Lanka
    (Department of Finance, Faculty of Commerce and Management Studies, University of Kelaniya, Sri Lanka., 2025) Sandeepani, W. R. N.; Piyananda, S. D. P.
    Introduction: This study investigates how methods for risk management affect Sri Lankan commercial banks with permissions and their financial results. Effective risk management is now essential to maintaining the profitability and security of banks in a financial environment that is becoming more and more uncertain. The research focuses on key risk factors: nonperforming loans (NPL), loans and advance (LA), loan loss provision (LLP), liquidity ratio (LR), and return on equity (ROA). The study investigates financial statements from seven commercial banks out of the twenty-four commercial banks that are listed on the Colombo Stock Exchange. They are selected under the sufficient of data category and other banks excluded due to the insufficient of data. Methodology: All the data collected as secondary data from annual report from 2019 to 2023 of each bank and the data analyzed by using regression analysis. The data set was analyzed using EVIEWS software. Furthermore, the firm’s performance measured by Return on Asset and risk management measured by loan loss provision, loans and advances, non-performing loans and capital adequacy ratio. Findings: Loans and advances (LA) represent a critical role in improving financial performance, as the analysis shows that they have a statistically significant and positive impact on ROA. On the other hand, ROA is not significantly correlated with Loan Loss Provisions (LLP), Non-Performing Loans (NPL), Liquidity (LIQ), or the Capital Adequacy Ratio (CAR). While the model explains a moderate proportion of the variation in ROA, the adjusted R-squared suggests room for improvement in predictive accuracy. The overall model is statistically significant, with no evidence of autocorrelation in the residuals. Conclusion: In conclusion, these findings highlight the urgent need for more empirical and theoretical research to strengthen the model's explanatory power, improve its predictive stability, and provide a more comprehensive, complex understanding of risk management's multiple influence on bank performance, operational efficiency, and financial stability.