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Big Data Analytics’ Involvement in Enhancing the Efficiency Lending and Marketing of Nigerian Lending Firms

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  • Ilemona Abutu

    (Manchester Metropolitan University, Manchester, United Kingdom)

Abstract

This research investigates the impact of big data analytics on efficiency and marketing of lending firms in Nigeria. The study adopts a review method to investigate the key issues facing lending firms in Nigeria. The study further investigates how data analytics help lending firms in overcoming these issues in term of risk management and lending decision making. Case study analysis of lending firms who have adopted data analytics in their business models shows how effective and sustainable their practices has been. Findings shows that firms utilise and invest heavily in big data analytics. Findings also revealed that there is statistically significant positive relationship between big data analytics and risk management, as well as lending decision making. Findings reveals that firms faces challenges such as data quality and government policies. The findings concludes that big data analytics is significant in not just lending firms but all financial institution in the country. The study therefore recommends among others that Nigerian financial lending firms should invest in developing integrated data management systems that consolidate data from multiple sources. By so doing, there will be readily available data for analysis whenever a borrower shows up and submit their bank verification number. An integrated system can provide a comprehensive view of customers, reducing data silos and enhancing insights for lending decisions and marketing strategies

Suggested Citation

  • Ilemona Abutu, 2025. "Big Data Analytics’ Involvement in Enhancing the Efficiency Lending and Marketing of Nigerian Lending Firms," International Journal of Research and Innovation in Social Science, International Journal of Research and Innovation in Social Science (IJRISS), vol. 9(1), pages 1320-1329, January.
  • Handle: RePEc:bcp:journl:v:9:y:2025:i:1:p:1320-1329
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