Abstract: This study provides a comprehensive assessment of the components and effectiveness of the money supply process in Bangladesh, with a particular focus on its underlying determinants, trends, and policy implications. The primary objective is to evaluate whether the existing money supply mechanism, as implemented by the Bangladesh Bank, is effective in meeting the country’s macroeconomic objectives of price stability, economic growth, and financial stability. The research adopts a mixed-method approach, integrating both descriptive and econometric analyses. Descriptive statistics and trend analysis are used to examine the historical patterns of monetary aggregates namely the monetary base (H), money multiplier (m), narrow money (M1), and broad money (M2) over the past two decades.
The results reveal that the money supply process in Bangladesh exhibits both short-run volatility and long-run stability, with the monetary base and money multiplier jointly influencing the expansion of M2. Co-integration tests confirm the existence of long-term equilibrium relationships among monetary aggregates, while ECM results suggest a moderate speed of adjustment toward equilibrium following shocks. However, structural break analysis indicates that global financial crises, domestic policy shifts, and recent pandemic-related disruptions have caused significant short-term deviations.
The findings highlight that although the Bangladesh Bank’s monetary policy framework has been largely effective in steering the long-run trajectory of the money supply, challenges remain in managing short-run fluctuations and in aligning monetary expansion with real economic growth. The study concludes with policy recommendations aimed at enhancing the effectiveness of the money supply process, including improving forecasting models, strengthening monetary transmission mechanisms, and enhancing coordination between monetary and fiscal policy.
Abstract: Non-Banking Financial Companies (NBFCs) play a crucial role in the Indian financial system by complementing banks in providing credit, promoting financial inclusion, and offering specialised financial services. The present study aims to evaluate the performance of selected NBFCs in India using key financial indicators. This research analyses profitability, liquidity, solvency, and efficiency ratios to assess the overall financial health of these organisations. Secondary data has been collected from annual reports and published financial statements of the selected NBFCs for a specific period. The findings reveal performance variations among NBFCs, highlighting strengths, weaknesses, and areas for improvement. This study conducts a comparative performance appraisal of two major Non-Banking Financial Companies operating in the National Capital Region (NCR) of India: Bajaj Finance Ltd. (Gurgaon) and Tata Capital Financial Services Ltd. (Noida). Using key financial metrics such as Assets Under Management (AUM), profitability ratios (Return on Assets - ROA, Return on Equity - ROE), net interest margin (NIM), asset quality (non-performing assets - NPAs), and capital adequacy, this paper evaluates the financial health, operational efficiency, and performance dynamics of both NBFCs. The findings highlight significant differences arising from their business strategies, asset quality, and scale of operations, providing actionable insights for investors, regulators, and stakeholders.
Abstract: This study examines the differential approach to risk management strategies concerning Non-Performing Assets (NPA) within India's two foremost banks – the Indian Public Sector Bank, State Bank of India (SBI) and the Indian Private Sector Bank, ICICI Bank. While comparing the two banks, using a mixed-method approach, the research combines quantitative analysis of trends in financial indicators (Gross and Net NPA ratios, Provision Coverage Ratio and Return on Assets) and a qualitative analysis of credit appraisal and monitoring and recovery frameworks. Data from 2010-2025 were taken from RBI publications, annual reports and credible academic studies, so there was authenticity and reliability of data.
Findings show that SBI's recovery centered reforms such as better provisioning (PCR increase from 70.88% to 75%), restructuring under Insolvency and Bankruptcy Code (IBC) and improved post-sanction monitoring have led to a reduction in Gross NPAs by 47% and significant improvement in profitability (ROA increased from 0.48% to 1.1%). On the other hand , ICICI Bank's proactive and technology-driven risk model, with AI-driven early warning systems, digitised credit scoring and stringent underwriting, regularly maintained low NPAs (down from 3.05% to 1.67%) and enhanced profitability (ROA doubling to 2.0%). Correlation study reports we see that there is a very strong inverse relationship between NPAs, provisioning, Net NPA ratio and profitability (r approx –0.9) which means as NPAs and provisioning go up Net NPA ratio and profitability goes down. This is proof that what we put in place for credit assessment, early identification and recovery does in fact directly improve banks’ performance. We found out that what made SBI successful was its recovery and restructurizing which made ICICI’s success was in prevention and technology based monitoring. Also brought to light is the fact that what is key in the Indian banking system is the integration between AI, data analysis and good governance which banks use in risk management and in the end in the maintenance of asset quality in a sustainable way.
Abstract: This study examines the differential approach to risk management strategies concerning Non-Performing Assets (NPA) within India's two foremost banks – the Indian Public Sector Bank, State Bank of India (SBI) and the Indian Private Sector Bank, ICICI Bank. While comparing the two banks, using a mixed-method approach, the research combines quantitative analysis of trends in financial indicators (Gross and Net NPA ratios, Provision Coverage Ratio and Return on Assets) and a qualitative analysis of credit appraisal and monitoring and recovery frameworks. Data from 2010-2025 were taken from RBI publications, annual reports and credible academic studies, so there was authenticity and reliability of data.
Findings show that SBI's recovery centered reforms such as better provisioning (PCR increase from 70.88% to 75%), restructuring under Insolvency and Bankruptcy Code (IBC) and improved post-sanction monitoring have led to a reduction in Gross NPAs by 47% and significant improvement in profitability (ROA increased from 0.48% to 1.1%). On the other hand , ICICI Bank's proactive and technology-driven risk model, with AI-driven early warning systems, digitised credit scoring and stringent underwriting, regularly maintained low NPAs (down from 3.05% to 1.67%) and enhanced profitability (ROA doubling to 2.0%). Correlation study reports we see that there is a very strong inverse relationship between NPAs, provisioning, Net NPA ratio and profitability (r approx –0.9) which means as NPAs and provisioning go up Net NPA ratio and profitability goes down. This is proof that what we put in place for credit assessment, early identification and recovery does in fact directly improve banks’ performance. We found out that what made SBI successful was its recovery and restructurizing which made ICICI’s success was in prevention and technology based monitoring. Also brought to light is the fact that what is key in the Indian banking system is the integration between AI, data analysis and good governance which banks use in risk management and in the end in the maintenance of asset quality in a sustainable way.
Abstract: This study empirically investigates the inflation-unemployment trade-off in Bangladesh and assesses its implications for achieving Sustainable Development Goal 1 (SDG 1) of zero poverty. High inflation erodes the real income of the poor, while unemployment directly limits earning capabilities, making the interplay between these variables a central determinant of poverty reduction. Using annual time-series data from 1990 to 2024, we employ an Autoregressive Distributed Lag (ARDL) model to test for the existence and stability of a long-run relationship. Our findings confirm a significant short-run trade-off but reveal that this relationship is unstable and weakens in the long run, suggesting that other structural factors dominate. The results indicate that unanticipated inflationary shocks disproportionately harm the poor, and persistent unemployment remains a formidable barrier to inclusive growth. The study concludes that a singular focus on either price stability or employment generation is insufficient for attaining SDG 1. Instead, Bangladesh requires an integrated policy framework that combines prudent monetary policy to control the inflation rate with targeted fiscal measures, investments in human capital, and productive sector diversification to generate new employment opportunities. This holistic approach is essential to effectively manage the trade-off and accelerate progress towards eliminating poverty.