The use of Artificial intelligence (ai) to manage cyber fraud incidents in the Nigerian financial sector
| Author | Affiliation |
|---|---|
Ozah, Harrison |
| Date | Volume | Issue |
|---|---|---|
2025 | 12 | 10 |
The increasing number of cyber incidents has highlighted the urgent need for innovative solutions to enhance cybersecurity within Nigeria’s critical infrastructure and financial sector. Artificial intelligence (AI) models have emerged as essential tools in combating cybercrime, particularly as human error continues to expose vulnerabilities and lead to significant losses in these sectors. However, the question remains: can AI models effectively mitigate these risks? This study examines the use of AI models to manage cyber incidents within Nigeria’s critical infrastructure and financial sectors. A quantitative research design was adopted, employing a survey method to collect primary data from a sample of 218 IT specialists working in both the private and public sectors, specifically within Nigeria’s critical infrastructure and financial industries. The survey yielded a 71.7% response rate, with 18.3% of questionnaires left incomplete. Data analysis was conducted using SPSS software, with inferential statistics, including Chi-square tests and standard deviation, to assess the variance and test the hypothesis regarding the effectiveness of AI models in managing cybercrime incidents. The findings suggest that organizations within Nigeria’s critical assets and the financial sector are increasingly adopting AI solutions, such as predictive analytics and behavioural analysis tools and others, to effectively address cybercrime incidents. Respondents expressed positive sentiments, indicating general agreement about the successful implementation and effectiveness of AI technologies within their organizations in quick responding resolutions and protecting of critical assets and the financial sector in cyber incidents. However, this indicates, the need in some areas of AI model limitation that requires human decision due to increase number of false positive flagging.