YASIN ALSYSYASIN ALSYS

African Multidisciplinary Journal of Sciences and Artificial IntelligenceAfrican Multidisciplinary Journal of Sciences and Artificial Intelligence

The increasing shift to digital banking in Nigeria has accelerated cyber fraud losses, prompting banks to adopt proactive forensic readiness measures. Recent industry reports show that Nigerian banks lost more than N300 billion ($833 million) in a single quarter of 2023, a 534% increase year-on-year. Digital Forensic Readiness (DFR) is a proactive cybersecurity strategy that ensures digital evidence is preserved and ready for analysis before a breach occurs. This paper reviews leading forensic readiness models, including Locards Exchange Principle, the Diamond Intrusion Model, and the NIST Risk Management Framework, and compares their applicability to Nigerian banking. We integrate these theories into a proposed DFR framework tailored for Nigerias banking sector, drawing on local and global studies. Key components of DFR (such as policies, technology, people, and legal compliance) are discussed with illustrations. Current challenges, notably reactive culture, evidentiary gaps, and regulatory compliance, are highlighted. Finally, best practices and a synthesis framework are presented to guide Nigerian banks toward a more resilient forensic posture.

Cyber fraud poses a severe threat to Nigerian banks profitability and reputation.This paper surveyed major forensic readiness models – Locards Exchange Principle, the Diamond Intrusion Model, and the Risk Management Framework – and analyzed their applicability to the banking sector.The proposed DFR framework is designed to leverage existing strengths while filling gaps in policy and compliance.Overall, a robust DFR posture will help Nigerian banks detect fraud earlier, conduct swifter investigations, and support legal action when needed, thereby strengthening trust in the financial system.

Further research should focus on empirically testing the proposed DFR frameworks effectiveness across Nigerian banks to determine its real-world impact and identify areas for improvement. Additionally, studies could investigate the specific training needs of Nigerian banking personnel regarding digital forensics and evidence handling, leading to the development of targeted training programs. Finally, exploring the integration of artificial intelligence and machine learning techniques into the DFR framework could enhance fraud detection capabilities and automate evidence analysis, ultimately strengthening the resilience of the Nigerian banking sector against evolving cyber threats. These investigations will require collaboration between academic institutions, regulatory bodies, and banking professionals to ensure relevance and practical applicability, contributing to a more secure and trustworthy financial ecosystem for Nigeria.

  1. Comparative Analysis of Theoretical Models for Digital Forensic Readiness (DFR) in Nigerian Banking |... ejournal.yasin-alsys.org/AMJSAI/article/view/8322Comparative Analysis of Theoretical Models for Digital Forensic Readiness DFR in Nigerian Banking ejournal yasin alsys AMJSAI article view 8322
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