INTEGRATING MULTIDIMENSIONAL DATA ANALYSIS, DATA WAREHOUSING, AND DATA MINING FOR ENHANCED DECISION SUPPORT SYSTEMS: MONIEPOINT MICROFINANCE BANK SCENARIO IN NIGERIA; A REVIEW.

Abstract

This review examined how Moniepoint Microfinance Bank, a Nigerian fintech institution, could use a 
Decision Support System (DSS) to improve its operations. The study explored how integrating 
multidimensional data analysis, data warehousing, and data mining enhanced decision-making. Key 
applications of this technology included fraud detection, customer segmentation, credit risk assessment, and 
regulatory compliance. The paper identified both opportunities and challenges for Moniepoint. The 
opportunities included optimizing operations by improving transaction monitoring, automating loan 
underwriting, and delivering personalized services to SMEs. However, the study also highlighted significant 
obstacles, such as data quality issues, infrastructural constraints, privacy risks, and algorithmic bias. Ethical 
considerations regarding fairness, transparency, and compliance with Nigerian data protection laws were also 
discussed. The review concluded that Moniepoint and similar institutions should invest in robust data 
governance, infrastructure, and analytics to fully utilize DSS capabilities. The paper proposed future research, 
including empirical DSS evaluations and the development of Africa-centred AI ethics frameworks. The report 
provided a strategic roadmap for integrating advanced analytics into the decision-making architecture of 
microfinance institutions in Africa.