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<title>Exploring the Link between Loan Loss Provisions and Profitability in Bangladesh’s  Private Banking Sector</title>
<link>http://ar.cou.ac.bd:8080/xmlui/handle/123456789/245</link>
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<dc:date>2026-05-28T19:08:06Z</dc:date>
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<title>Exploring the Link between Loan Loss Provisions and Profitability in Bangladesh’s  Private Banking Sector</title>
<link>http://ar.cou.ac.bd:8080/xmlui/handle/123456789/246</link>
<description>Exploring the Link between Loan Loss Provisions and Profitability in Bangladesh’s  Private Banking Sector
Mia, Rubel
This study investigates the relationship between Loan Loss Provisions (LLPs) and the &#13;
profitability of private commercial banks in Bangladesh, considering both internal financial &#13;
metrics and macroeconomic factors. As financial intermediaries, banks play a critical role in &#13;
supporting economic activity, but they also face growing challenges from rising credit risk, &#13;
deteriorating asset quality, and regulatory requirements. In this context, LLPs, which are used &#13;
to cover potential loan defaults, become essential risk management tools. However, their &#13;
impact on profitability remains a key concern for bank executives and policymakers. Using &#13;
panel data from ten Dhaka Stock Exchange (DSE)-listed private banks over the period 2014&#13;
2023, the study examines how LLPs, along with Non-performing Loans (NPL), Capital &#13;
Adequacy Ratio (CAR), Loan Growth Rate (LGR), GDP growth rate, Total Loans to Total &#13;
Assets (TLTA), Total Loans to Total Deposits (TLTD), and Bank Size, influence Return On &#13;
Assets (ROA) and Return On Equity (ROE). The analysis employs panel data regression &#13;
models—Fixed Effects, Random Effects, Pooled OLS, and GLS—supported by robustness &#13;
tests including multicollinearity (VIF), heteroskedasticity (Breusch–Pagan), autocorrelation &#13;
(Wooldridge), and the Hausman specification test. GLS model is best for this study. The results show that LLPs and NPLs negatively affect profitability, while CAR, GDP growth, and bank size positively influence ROA and ROE. TLTD is found to have a negative effect, signaling potential risk from aggressive lending practices. The GLS model emerged as the most appropriate fit for the dataset. These findings highlight the importance of strategic provisioning policies and effective credit risk management. Policymakers and bank managers should focus on improving asset quality, maintaining adequate capital buffers, and aligning risk control measures with macroeconomic conditions to enhance long-term profitability in the banking sector.
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<dc:date>2025-05-26T00:00:00Z</dc:date>
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