ARTIFICIAL INTELLIGENCE AND FRAUD DETECTION OF DEPOSIT MONEY BANKS IN AWKA-SOUTH ANAMBRA STATE, NIGERIA
Published 2023-09-18
Keywords
- Transaction Monitoring,
- Facial Recognition Artificial Intelligence,
- Chatbot Artificial Intelligence
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Copyright (c) 2023 Global Journal of Artificial Intelligence and Technology Development
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
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Abstract
This study ascertained the effect of artificial intelligence on fraud detection of deposit money banks in Awka-South Local Government Area, Anambra State, Nigeria. Notwithstanding the tangible and monetary benefits, artificial intelligence has various shortfall and problems which inhibits its large scale adoption. With automation, nefarious acts such as phishing, delivery of viruses to software might be difficult to uncover. Although technology has helped make it possible to detect fraud, numerous challenges still face businesses. Ironically, advances in technology also enable fraudsters to craft new ways to dodge detection. This study adopted field survey research design. The population was six hundred and fifty one (651) staff of the sampled fourteen deposit money banks. Taro Yamane formula was employed to determine the sample size of 248. Of the 248 copies of administered questionnaire, 174 copies were collected. Validity and reliability of the instrument were tested and achieved. Descriptive statistics was employed, while inferential statistics using Cronbach Alpha, Spearman’s Correlation and Paired Sample T-Test were employed to test the hypotheses with the aid of SPSS version 23. The specific findings revealed that Facial recognition artificial intelligence has a significant and positive effect on transaction monitoring (t-statistic = 6.9622; p-value = 0.000); Chatbot artificial intelligence has a significant and positive effect on transaction monitoring (t-statistic = 4.909; p-value = 0.000); Digital assistant artificial intelligence has a significant and positive effect on transaction monitoring (t-statistic = 6.5659; p-value = 0.000) of deposit money banks in Awka-South Anambra State, Nigeria at 5% level of significance respectively. This study recommended inter alia that firms should employ the artificial intelligence tools to provide better security and surveillance opportunities, which would also let human identification be fully automated hence enhancing productivity while also raising the rate of accuracy and the detection of fraud.