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Study on Application of Artificial Intelligence and Machine Learning in the Banking Sector for Fraud Detection and Prevention
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Author(s): Retheesh P. Pillai (Karunya Institute of Technology and Sciences (Deemed), India)and D. Ponmary Pushpa Latha (Karunya Institute of Technology and Sciences (Deemed), India)
Copyright: 2025
Pages: 24
Source title:
Machine Learning for Environmental Monitoring in Wireless Sensor Networks
Source Author(s)/Editor(s): Parikshit N. Mahalle (Department of Artificial Intelligence and Data Science, Vishwakarma Institute of Technology, Pune, India), Dattatray G. Takale (Vishwakarma Institute of Information Technology, India), Sachin Sakhare (Vishwakarma Institute of Information Technology, India)and Ganesh B. Regulwar (Vardhaman College of Engineering, India)
DOI: 10.4018/979-8-3693-3940-4.ch017
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Abstract
Cyberbanking fraud is a growing concern in the digital age, posing risks to financial institutions and consumers. Malicious actors exploit advanced technologies to steal money from banks and users. Traditional methods like rule-based analysis have limitations, especially against digital fraud schemes. This paper highlights the need for constant improvement in fraud prevention strategies. Financial institutions can use AI and ML, particularly deep learning, to enhance their defenses. These technologies enable real-time analysis of large data, detecting unusual patterns and improving fraud identification accuracy. Proactively adopting technological advancements is crucial to combat the ever-changing threat of cyberbanking fraud.
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