Because of its firm reliance on oil exports, Nigeria, a major oil-producing nation, has seen considerable economic volatility. The exchange rates and the volatility of oil prices significantly impact the country’s macroeconomic stability, growth, and development. Nigeria’s economy mainly depends on oil exports, which provide 70% of government revenue and more than 90% of foreign exchange revenues. On the other hand, because of shifts in monetary policy, capital flows, and oil prices, the Nigerian Naira (NGN) has seen considerable volatility against major currencies, especially the US Dollar (USD). As a result, the GDP grew at erratic rates, impacted by changes in the price of oil, ranging from -1.6% in 2016 to 3.1% in 2022 (CBN, 2023). The main subject of this study is the relationship between Nigeria’s GDP growth, exchange rates, and oil price volatility. In particular, the contribution of currency rate and oil price volatility to the engineering and maintenance of Nigeria’s economic growth was investigated. The study also looks at how the exchange rate affects Nigeria’s economic development and how the volatility of the oil price affects that growth. The period of 40 years (1984–2023) was chosen for empirical investigation. The information was gathered from the Nigeria Bureau of Statistics (NBS; 2023), journals, the Central Bank of Nigeria Statistical Bulletin (CBN; 2023), and World Bank statistics. These data sources are thought to be highly trustworthy and dependable.
The potential of fraud is one of the typical governance concerns faced by monetary institutions, such as rural banks, regardless of size, location, or operational complexity. Having robust internal control systems and establishing a risk management program is critical in combating fraud. This study explores the implementation of Internal Control Systems of the firm RB concerning the principles prescribed by the COSO framework. The research method used in the study was quantitative. The participants of the study comprised55 stakeholders of the institution selected based on purposive sampling. Findings show that the business has internal control systems in place which are generally implemented to a great extent as prevention and detection controls. The recommendation includes that the company should consider studying and investing in fraud prevention software and designs, integrating its best practices and existing regulatory standards with technological advancements to combat new probable fraud schemes.
This study examined the adoption of predictive analytics for marketing decision making and its implications for business growth. Specifically, the study examined the nexus between adoption of sales trend forecasting and customer retention in SMEs. Survey descriptive research design was used in the study. The population of the study consist of 1,902 registered SMEs in Awka South Local Government Area, Anambra State, with sample size of 330 respondents obtained using Taro Yamane (1967) formula. Data (Primary) were collected using structured questionnaire. Mean and frequency distribution were used to conduct descriptive analysis on the data. Hypothesis was tested using multiple regression analysis, at a 5% level of significance. The result indicted that a very high positive correlation exists between the variables analyzed, with an R coefficient of 0.8849, while the R² value of 0.7831 means that about 78.31% of the variation in the dependent variable is explained by the model. The study, therefore, concluded that Sales Trend Forecasting significantly and positively influence overall Business Growth of SMEs through customer retention. Sequel to this, among others, it was recommended that small business should learn to leverage data analytics, and by extension, sales trend forecasting, so as to be able to predict customer behavior and track it, in order to follow-up and ensure repeat purchase, and build loyalty among customers.
This study sought to assess the extent of compliance management of the manufacturing company using ISO 9001:2015 model in San Pablo City, Laguna, through descriptive analysis. This study was carried out using a quantitative approach. The respondents involved in this study were selected employees of the manufacturing company; 67.4% of the respondents were female, and 32.6% were male, for a total population of 46. The respondents were given a modified survey questionnaire based on the ISO 9001:2015 checklist requirements. Purposive sampling technique was applied to select respondents. The respondents were purposively selected based on their knowledge and understanding of ISO 9001:2015. The findings of the study revealed that the manufacturing company demonstrates a high level of compliance with ISO 9001:2015 standards. Based on the findings, it was observed that the manufacturing company successfully implemented and maintained a QMS that conforms to international standards. The successful implementation of ISO 9001:2015 suggests the company’s commitment to quality, continuous improvement, and customer satisfaction. Through compliance with ISO 9001:2015, the manufacturing company can improve its overall performance and gain a competitive advantage. The findings may not be to all manufacturing companies, as they differ in the industry, company size, and geographic location may affect the implementation and outcomes of ISO 9001:2015 compliance management.
Artificial intelligence (AI) has emerged as a disruptive force in the accounting and financial industries internationally, enabling substantial breakthroughs in automation, data processing, and decision-making processes. Despite its promise, the adoption of AI in Bangladesh’s accounting and finance business remains embryonic, distinguished by specific difficulties and possibilities. This article explores the opportunities and obstacles of AI adoption within this industry, attempting to give a full grasp of its present condition and future potential. The report reveals major gaps in AI integration, including technical, legislative, and organizational constraints that limit mainstream implementation. Key goals include studying the potential advantages of AI, such as enhanced efficiency and accuracy in financial operations, and analyzing the hurdles encountered by organizations, including resistance to change and talent shortages. A mixed-methods approach was adopted, combining quantitative surveys of 240 professionals from different financial institutions with qualitative, semi-structured interviews of 20 industry experts. Quantitative data was evaluated using descriptive and inferential statistical approaches, while qualitative data was submitted to theme analysis to elicit subtle insights. Findings demonstrate that although there is a rising interest and favorable view towards AI, important hurdles remain, such as insufficient infrastructure and limited knowledge. The report indicates that solving these obstacles via focused strategies and regulations is vital for utilizing AI’s full potential in Bangladesh’s accounting and finance industry. The analysis underlines the need for increasing investment in technology and training to support effective AI deployment.
