The Role of Data Analytics in Enhancing Financial Inclusion in Emerging Economies (Published)
Financial inclusion, defined as the availability and equality of opportunities to access financial services, is a critical factor in the economic development of emerging economies. However, various barriers such as geographical, socioeconomic, technological, and regulatory constraints hinder its widespread adoption. Data analytics emerges as a powerful tool to overcome these barriers and enhance financial inclusion. This review explores how data analytics can identify and understand unbanked and underbanked populations, improve credit scoring and risk assessment through alternative data sources, personalize financial products and services, enhance financial literacy, and facilitate digital payments and transactions. Case studies from diverse emerging economies illustrate the practical applications and success stories, such as Kenya’s mobile money platform M-Pesa, India’s digital lending initiatives leveraging Aadhaar and UPI, and blockchain-based financial inclusion efforts in Africa. These examples highlight the transformative impact of data-driven solutions in bridging the financial inclusion gap. Despite the promising potential, challenges such as data privacy and security concerns, infrastructure limitations, regulatory hurdles, and the risk of bias must be addressed to ensure equitable benefits. Policy recommendations include fostering public-private partnerships, promoting open data initiatives, implementing supportive regulatory frameworks, and investing in digital infrastructure and literacy. Emerging technologies and trends, including advancements in AI, the expansion of blockchain technology, and the integration of the Internet of Things (IoT) in financial services, offer new avenues for enhancing financial inclusion. By leveraging these innovations, emerging economies can achieve sustainable development goals, drive economic growth, and significantly reduce poverty levels. This review underscores the pivotal role of data analytics in creating an inclusive financial ecosystem and outlines a strategic path forward for policymakers and financial institutions.
Keywords: Economic, Financial Inclusion, data analytics
Impact of Monetary Policy on Economic Growth in Nigeria (1990-2017) (Published)
The study examined the impact of monetary policy on economic growth in Nigeria; for the period 1990-2017. Secondary data were collected from the Central Bank of Nigeria Statistical Bulletin. The study used Gross Domestic Product as proxy for economic growth and employed as the dependent variable; whereas, monetary policy rate, liquidity rate and Treasury Bills respectively were used as the explanatory variables to measure monetary policy. Hypotheses formulated were tested using Ordinary Least Square (OLS) techniques. The study revealed a significant impact of Treasury Bills on Gross Domestic Product in Nigeria. Liquidity ratio had a significant impact on Gross Domestic Product in Nigeria. Monetary policy rate had a significant impact on Gross Domestic Product in Nigeria. The coefficient of determination indicated that about 62% of the variations in private sector of the economy can be explained by changes in monetary policy variables. The study concluded that monetary policy had impacted significantly on private sector growth in Nigeria. The study recommended that policy makers should strong economic policies that will maintain and stabilize the economy. CBN should lay down strict prudential guidelines to stabilize and strengthen the economy. The CBN should review the Monetary Policy Rate downwards so as to reduce the cost of credit and increase the flow of investible funds to the economy.