International Journal of Social Science Exceptional Research  |  ISSN: 2583-8261  |  Double-Blind Peer Review  |  Open Access  |  CC BY 4.0

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International Journal of Social Science Exceptional Research

ISSN: (Print) | 2583-8261 (Online) | Impact Factor: 8.41 | Open Access

Optimizing SME Banking with Data Analytics for Economic Growth and Job Creation

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Abstract

Small and Medium Enterprises (SMEs) are pivotal to economic growth and job creation, contributing significantly to global GDP and employment. However, many SMEs face barriers to accessing tailored banking solutions, which impedes their growth potential. Data analytics presents a transformative opportunity to optimize SME banking by offering personalized financial products, improving credit risk assessment, and enhancing overall customer experience. This paper explores the integration of advanced data analytics into SME banking, emphasizing its role in fostering economic development and job creation. Through predictive modeling and machine learning, data analytics enables banks to analyze SME financial behaviors, segment their diverse needs, and design customized solutions. Enhanced credit risk modeling, powered by real-time data, reduces loan defaults while increasing access to finance for underserved SMEs. Additionally, analytics-driven decision-making allows banks to identify growth sectors, supporting SMEs in emerging industries and fostering innovation. The paper also examines the economic implications of optimizing SME banking with data analytics. By bridging the financing gap, banks can empower SMEs to scale operations, invest in technology, and create jobs. Moreover, improved access to working capital enhances productivity, ensuring long-term business sustainability. The use of data analytics further strengthens regulatory compliance, reducing financial fraud and fostering trust within the banking ecosystem. Case studies from emerging and developed economies highlight successful implementations of data-driven SME banking, showcasing significant growth in SME loan portfolios and improved job creation metrics. Challenges such as data privacy concerns, integration costs, and the digital readiness of SMEs are also addressed, with recommendations for adopting ethical and scalable data analytics frameworks. This study concludes that the strategic application of data analytics in SME banking is a catalyst for economic growth, innovation, and employment generation. Policymakers, financial institutions, and technology providers must collaborate to harness its potential, ensuring inclusive financial growth.

How to Cite This Article

Oluwasola Emmanuel Adesemoye, Ezinne C Chukwuma-Eke, Comfort Iyabode Lawal, Ngozi Joan Isibor, Abiola Oyeronke Akintobi, Florence Sophia Ezeh (2023). Optimizing SME Banking with Data Analytics for Economic Growth and Job Creation . International Journal of Social Science Exceptional Research (IJSSER), 2(1), 262-276. DOI: https://doi.org/10.54660/IJSSER.2023.2.1.262-276

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