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DATA-DRIVEN STRATEGIES FOR EARLY DETECTION OF FINANCIAL FRAUD IN MOBILE MONEY SYSTEMS: A CASE STUDY OF NIGERIA'S MOBILE MONEY ECOSYSTEM
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The rapid expansion of mobile money services in Sub-Saharan Africa (SSA) has revolutionized financial inclusion, but it has also created new vulnerabilities for financial fraud. This study examines data-driven strategies for early detection of financial fraud in mobile money systems, with a specific focus on Nigeria's mobile money ecosystem, including MTN MoMo, Airtel Money, PalmPay, and OPay. Through a comprehensive analysis of current fraud detection methodologies, machine learning approaches, and regulatory frameworks, this research identifies key strategies for enhancing fraud prevention in mobile financial services. The findings reveal that integrated approaches combining behavioral analytics, transaction pattern recognition, and real-time monitoring systems are most effective in combating mobile money fraud. The study recommends the adoption of collaborative fraud detection frameworks among mobile money operators and strengthened regulatory oversight to protect Nigeria's growing mobile money user base.
Mediterranean Publications and Research International
Title: DATA-DRIVEN STRATEGIES FOR EARLY DETECTION OF FINANCIAL FRAUD IN MOBILE MONEY SYSTEMS: A CASE STUDY OF NIGERIA'S MOBILE MONEY ECOSYSTEM
Description:
The rapid expansion of mobile money services in Sub-Saharan Africa (SSA) has revolutionized financial inclusion, but it has also created new vulnerabilities for financial fraud.
This study examines data-driven strategies for early detection of financial fraud in mobile money systems, with a specific focus on Nigeria's mobile money ecosystem, including MTN MoMo, Airtel Money, PalmPay, and OPay.
Through a comprehensive analysis of current fraud detection methodologies, machine learning approaches, and regulatory frameworks, this research identifies key strategies for enhancing fraud prevention in mobile financial services.
The findings reveal that integrated approaches combining behavioral analytics, transaction pattern recognition, and real-time monitoring systems are most effective in combating mobile money fraud.
The study recommends the adoption of collaborative fraud detection frameworks among mobile money operators and strengthened regulatory oversight to protect Nigeria's growing mobile money user base.
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