IIARD International Institute of Academic Research and Development

Journal of Accounting and Financial Management (JAFM )

E-ISSN 2504-8856
P-ISSN 2695-2211
VOL. 10 NO. 9 2024
DOI: 10.56201/jafm.v10.no9.2024.pg42.62

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Artificial Intelligence and Fraud Detection of Listed Deposit Money Banks in Nigeria

Hussaini Hannah Ojone, Nuraddeen Usman Miko PhD, Sulaiman Umar Musa PhD

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Abstract

The study examined the impact of artificial intelligence on fraud detection of listed deposit money banks in Nigeria. Fraud detection was used as independent variable while Artificial intelligence was used as the independent variable. The determinants of artificial intelligence in this study will be automated chatbot, deep learning machine, machine learning solutions and natural language processing. The geographical coverage of this study will be in Nigeria. The study will cover 11years spanning from 2012 to 2022; within this period CBN introduced cashless policy into the Nigerian Financial system. More so, a lot of Banks introduced artificial intelligence into their operations within this period. This study employ survey design, Therefore the study employed a survey method of data collection, via a self-administered questionnaire. The data was collected from deposit money banks in Kaduna state. Out of the 14 Listed Deposit money Banks in Nigeria, 10 banks will be selected based on simple random Sampling Technique. The tool will be statistical Package for Statistical sciences (SPSS) version 20. Regression analysis will be used to predict the effect of the independent variable on the dependent variable and also used to either accept or reject null hypothesis. Validity and reliability test will be carried out. The result from Table 4.6 reveals that automated chat boat has a coefficient value of 0.413 and P-value 0.000. This signifies that automated chat boat has a positive and significant influence on deposit money banks. The regression model in Table 4.6 indicated that deep learning machine has a coefficient value 0.212 and P value 0.009. This signified that deep learning machine is positively and significantly impacting fraud detection among deposit money bank. From the Table 4.6 it was observed that machine learning solution has a coefficient value 0.172 and P value 0.069. This shows that machine learning solution is positively b

keywords:

Artificial Intelligence, Fraud Detention, Automated Chatbots, Deep Learning Machine, Machine

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