Asian Journal of Economics, Business and Accounting
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The Impact of Taxation on Economic Growth and Development
No full textSince Nigeria is an open economy that engage in international trade the importance of identification of revenue source that would help the country improve its economic growth and development is very sacrosanct. The identification of tax revenue is very relevant in enhancing the country growth and development. This study examines into the effect of tax revenue on economic growth and development. The study employed the time series data sourced from the CBN Statistical Bulletin from 1992 to 2024. The dependent variable is the gross domestic product while the independent variables includes value added tax, company income tax, inflation rate and interest rate. The multiple regression revealed that company income tax has positive significant effect on gross domestic product while interest rate has negative significant effect on gross domestic product. The government should adopt policies that balance revenue generation with economic growth. Given the negative and significant effect of value-added tax (VAT) on GDP, policymakers should consider reducing VAT rates on essential goods and services to minimize the burden on consumers and businesses. Additionally, broadening the tax base and improving tax compliance could generate revenue without hampering economic activity
Optimal Portfolio Selection During the Health Crisis of Covid-19: Examining Risk-Based Allocation Methods
No full textThe minimum variance portfolio weights, the ERC (Equally-weighted Risk Contribution) portfolio, the MDP (Most Diversified Portfolio), the IVP (Inverse Volatility Portfolio), and the MDECP (Maximum Decorrelation Portfolio) are all direct functions of the estimated covariance matrix. We conduct a study of two econometric models, the EWMA historical simulation model and the DCC-GARCH model, to first assess the impact of a specification error in the covariance matrix on these risk-based portfolios over daily, weekly forecast horizons, and to study the performance of these portfolio allocation strategies during the Covid-19 health crisis.
In this article We will try to evaluate to what extent the application of portfolio optimization models based on the sole risk criterion would make it possible to develop portfolios capable of remedying the failure of the mean-variance model, particularly in times of the Covid-19 health crisis while addressing the sensitivity of portfolio weightings based on the risk of covariance forecasting.
The empirical study is based on four risky assets: two stock indices, namely: S&P 500 and IEF (Exchange Traded Fund), and two commodities, namely: XAU (the PHLX Gold/Silver Sector Index) and USO (the United States Oil Fund), over a four-year period (2018-2022). Our results show that using dynamic conditional correlation (DCC) or exponentially weighted moving average (EWMA) provides similar covariance forecasts. Indeed, risk-based indexing strategies allow for the minimization of specific risk rather than market risk because these aforementioned portfolio optimization models seek to eliminate diversifiable risk and do not offer protection against systematic risk. The best results are obtained with rebalancing every five trading days but with small magnitude deviations
Financial Technology and Financial Performance: Experience from Nigeria Deposit Money Banks
No full textThis study examines the impact of Financial Technology (FinTech) on the financial performance of deposit money banks in Nigeria. A survey research design was used to collect data from 150 respondents randomly selected across six banking institutions operating in Nigeria, chosen using a homogeneous purposive sampling technique, with each bank providing a sample of 25 questionnaires. Out of the 150 questionnaires distributed, 132 were retrieved and found useful, representing 88% of the total questionnaires administered. The collected data were summarized and analyzed using descriptive statistics, such as tables, frequency, and percentage analysis, while multiple regression analysis was employed to test the hypotheses. The findings reveal a significant positive relationship between digital banking adoption and banks\u27 Return on Assets (ROA), with a coefficient of determination (R²) of 0.743, indicating that 74% of the variation in bank performance is explained by the adoption of digital banking. The study shows that digital banking practices, including ATM transaction volume and internet banking usage, significantly overall profitability of the sampled banks. the study concluded that components of financial technology, such as digital banking penetration, ATM transaction volume, and internet banking usage, are key drivers of banking performance and significantly enhance profitability in Nigeria\u27s deposit money banks. The study recommends that banks invest in advanced digital infrastructure, enhance ATM service reliability, and prioritize cybersecurity measures. These steps will not only increase long-term profitability but also foster greater customer trust in the digital banking space
The Influence of Financial Literacy, Financial Self-efficacy and Financial Strain on Financial Independence of Employees of Pasakha Industrial Estate, Bhutan
No full textFinancial independence refers to the ability of individuals to manage personal finances without financial support from others. Financial independence has become crucial a concern for individuals, households, societies, and countries in recent years, yet research on the subject is done by few only. Thus, current research aims to understand the influence of financial literacy, financial self-efficacy, and financial strain on the financial independence of employees. A two-stage sampling method (Stratified and convenience sampling) was employed to draw a representative sample from the employees of Pasakha Industrial Estate and 356 responses were collected through questionnaire. Descriptive, correlation, and regression analysis were used to analyze the data collected. As revealed by correlation and regression analysis all the relationship were significant and only financial strain have negative relation with financial independence. Moreover, the study reveal that financial self-efficacy has significant influence as compared to other variables. Therefore, the study provides actionable insights to the concerned authorities to uplift the financial independence of employees
Automating Financial Decision-Making in Renewable Energy: Leveraging AI and Credit Risk Models for Sustainable Investment
No full textAim: This study investigates the impact of financial automation, artificial intelligence (AI) credit risk models, and predictive analytics on renewable energy investment choice in the United States. It investigates how automation optimizes capital allocation, mitigates investment risk, and enhances financing structures for clean energy projects.
Study Design: A systematic peer review of the literature from 2019-2025 on the application of AI in financial decision-making, credit risk modeling, and renewable energy investments, including blockchain technology. Case studies from financial institutions and renewable energy firms using AI-driven risk assessments are included.
Methodology: The research gathers articles from academic databases such as Google Scholar, Scopus, SSRN, and Business Source Complete. Some of the selected articles focus on AI in financial automation, credit risk evaluation in renewable energy, and investment patterns in clean energy ventures.
Results: The review references various studies demonstrating how financial automation using AI enhances risk evaluation, reduces rates of project failure, and enhances access to sustainable capital for investment. AI-based credit risk models ease the distribution of capital, allowing small and medium-sized businesses (SMEs) to access financing for clean energy initiatives. Predictive analytics in financial decision-making considerably enhances risk evaluation and portfolio diversification. Blockchain application further strengthens transactional transparency and reduces fraud risks in renewable energy financing.
Conclusions: AI and financial automation present transformative opportunities for sustainable energy financing through improved investment efficiency and diminished credit risks. However, data reliability and algorithmic biases are challenges that must be addressed to realize their maximum potential. Future research should examine regulatory frameworks and ethical considerations to ensure responsible implementation of AI-driven financial automation
Digital Financial Transformation and Financial Well-being in India: An Empirical Study
No full textIn the era of the technology world, we have witnessed the revolution of digital transactions, not only in financial institutions but also in other industries. In the era of digital banking, Digital Financial Services like Unified Payment Interface (UPI), AePS, Fastag, IMPS, NEFT, RTGS, QR, Debit, Credit card payments, and so on. Among this, the UPI transaction has become well known among all sections of the people in the country. This study is descriptive in nature. Based on Secondary data collected from RBI, National Payment Corporation of India (NPCI), and other government-authenticated sources. It was found that, from just 1 Million transactions in 2016, UPI has since crossed the landmark 10 Billion transactions. The UPI recorded the highest-ever volume of transactions, 45 per cent year-on-year increase in volume, reaching 14.44 billion in July 2024. The value of these transactions grew by 35% year-on-year, totaling Rs 20.64 lakh crore as of August 1, 2024. Further, it is predicted that, daily transactions on the UPI platform will touch 1 Billion by 2025. So, it is clearly witnessed that digital transformation has been taking place in urban as well as in rural India which will establish the financial well-being among the people
Adoption of Futuristic Strategies by the Community Banks to Combat Competitive Challenges in USA
No full textThe goal of this study is to investigate methods that can strengthen community banks\u27 resilience in light of these difficulties, guaranteeing their long-term viability and ongoing support of regional economies. Community banks are vital to local economies, particularly in underserved and rural areas, as they give small businesses and individuals access to loans and other necessary financial services. The long-term survival of these organizations has been questioned, nevertheless, due to the growing trend of financial consolidation, regulatory changes, technology disruptions, and economic uncertainties. With an emphasis on digital transformation, regulatory compliance, strategic alliances, and important risk mitigation techniques, this study looks at ways to improve the resilience of community banks in the US. The impact of developing financial technologies, such as blockchain, digital banking, and artificial intelligence (AI), on the sustainability and operational efficiency of community banks is highlighted by this study through an analysis of case studies and current literature. While technological advancements present opportunities for cost reduction and service enhancement, they also introduce cybersecurity threats and regulatory complexities that must be managed effectively. The study further evaluates the effectiveness of resilience strategies such as capital adequacy measures, enterprise risk management (ERM), and diversified revenue models in mitigating financial risks. Case studies of successful community banks demonstrate how institutions leveraging technology and sound financial practices have sustained operations despite industry challenges. The findings emphasize the need for continuous adaptation to technological and economic shifts, proactive regulatory compliance, and strong financial governance to ensure the long-term stability of community banks. Ultimately, strengthening community banks\u27 resilience is not only vital for their survival but also for the broader financial stability and economic inclusion of local communities in the United States
Micro-credit in Bangladesh: A Comprehensive Review of its Evolution, Impact, and Challenges Using Quantitative and Qualitative Evidences
No full textBangladesh\u27s micro-credit model is widely regarded as the birthplace of contemporary microfinance as it is acknowledged to significantly contribute to poverty alleviation and incorporate financial inclusion in pursuing decent results for the sustainable development goals, including SDG 1 and SDG 5 (No Poverty and Gender Equality) in its implementation. This article tracks the trajectory of microcredit in Bangladesh, showing how it has grown from a small, grassroots enterprise to an essential part of the financial inclusion and rural development agenda. In Bangladesh, microcredit has revolutionized financial practices through its unique, non-collateral group financing, conceived by Grameen Bank and BRAC in the late 1970s, to help millions of poor, primarily female, communities. The industry has grown considerably from pilot projects to a large-scale structure supported by stronger legislation, government involvement, and international donor financing. Such progress has decreased poverty tremendously and has been critical to meeting urgent Sustainable Development Goals, particularly SDG 1 (No Poverty) and SDG 5 (Gender Equality). This review critically evaluates the effectiveness and limitations of micro-credit in promoting financial inclusion, poverty alleviation, and rural development through synthesizing existing literature, empirical studies, and policy reports. This study employed various types of secondary data to obtain a critical perspective of microcredit\u27s social and economic impacts. These include assessments from microfinance agencies, government data, and peer-reviewed studies. Some analyzed key outcomes include improvements in household income, employment, access to education and healthcare services, and increased women\u27s empowerment and expansion of rural entrepreneurship activities. The study highlights some remaining problems, including the risk of debt traps, high loan interest rates, spatial inequalities in access, and a growing complexity in how digital microcredit functions. At the same time, there is a notable digital divide. The study blends empirical research with policy studies to point out significant problems in how microcredit is presently provided and to indicate applicable policy shifts to improve regulatory frameworks, enhance financial literacy, and address digital inequality. The study provides valuable insights for policymakers, financiers, and development practitioners who wish to achieve successful microfinance sustainability in promoting equitable economic development in Bangladesh. Microcredit continues to be an essential, if flawed, tool in Bangladesh\u27s development strategy. As Bangladesh navigates this evolving terrain, microcredit must adapt to developing obstacles while remaining committed to its core mission: elevating the downtrodden through dignity, opportunity, and financial justice
Artificial Intelligence in Content Creation: A Comprehensive Analysis of Creative, Ethical, and Economic Impacts
No full textThe primary objective of this study is to examine the impact of Artificial Intelligence (AI) on content creation across various creative industries, including writing, visual arts, and music composition. The research aims to analyze how AI technologies are transforming traditional creative processes, while also addressing the associated ethical, legal, and economic implications. Data were collected through a structured survey conducted between January and March 2024 among 250 professionals working in journalism, marketing, visual arts, and music production. A stratified random sampling technique was employed to ensure sectoral representation. The study utilized descriptive statistics and independent sample t-tests to evaluate AI\u27s influence on creativity and related concerns. Data analysis was performed using SPSS software. The results revealed statistically significant impacts of AI on creative processes, with t-values of 5.50 (writing), 4.72 (visual arts), and 4.10 (music composition), all with p-values < 0.001, confirming the rejection of the null hypothesis. The findings highlight AI’s capability to enhance efficiency and innovation in content creation, while also raising critical ethical issues, such as authorship (mean score = 3.95), bias (mean = 4.05), and intellectual property rights. Economically, the study found evidence of AI contributing to job displacement and evolving employment patterns within creative sectors. This research underscores the dual nature of AI as both a transformative force and a source of emerging challenges, emphasizing the urgent need for robust ethical and legal frameworks to govern its use in content creation
Bank Employees\u27 Attitudes towards Financial Inclusion: A Study on the Role of Banking Staff in Promoting Financial Literacy and Accessibility
No full textThis study investigates the attitudes of bank employees towards financial inclusion in Cameroon. The survey of 25 bank employees and a comprehensive analysis using multiple linear regression yielded significant findings. The results reveal a positive association between Attitudes Towards Financial Inclusion (ATFI) and attitudes towards underserved groups (ATUG), perceived importance of financial literacy (PIHL), and financial inclusion training (FIT). However, a negative correlation was observed between ATFI and bank policies and procedures (BPP) and Cameroon\u27s Anglophone Regions Employees\u27 Perception (CR). The model effectively explains 91.9% of the variance in ATF. These findings have important implications for the banking sector, suggesting that enhancing bank employees\u27 attitudes towards financial inclusion through targeted training programs and strategic adjustments to bank policies and procedures can lead to improved financial inclusion practices