Global fraud prevention leveraging artificial and machine learning technologies

Priya, G. Jaculine and Saradha, S. (2023) Global fraud prevention leveraging artificial and machine learning technologies. In: 11TH ANNUAL INTERNATIONAL CONFERENCE (AIC) 2021: On Sciences and Engineering, 29–30 September 2021, Banda Aceh, Indonesia.

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Global fraud prevention leveraging artificial and machine learning technologies _ AIP Conference Proceedings _ AIP Publishing.pdf

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Abstract

Digitization has enabled the world to move forward at a faster pace, however, on the flip side it has opened up another huge problem-“fraud attacks”. Everyday industry is faced with a new type of fraud, which is a huge threat to the IT Industry. Organizations will have to focus on continuous security process improvement and build multiple layers of security controls to safeguard customer assets and its brand value. Though, Fraud is thought to be predominant in the financial sector, it also applies to E-Commerce, health care, payment gate ways and for that matter any digitized business process where customers are exchanging their credentials, locations, credit card and other sensitive details online. To identify and stop these frauds attacks, the industry is desperately looking for accurate and new ways to detect fraud in real time. Organizations should focus on real time fraud detection to prevent fraud through a multitude of factors and stay ahead of the fraudsters. In order to achieve that organizations should come together to exchange fraudulent activity/information amongst themselves and be more transparent to each other. The need of the hour is to create a platform which enables transparent & secure exchange of information, alert organizations of fraudulent activities, real time, there by learning from each other and adapting quickly.

Item Type: Conference or Workshop Item (Paper)
Subjects: Computer Science > Software Engineering
Divisions: Computer Science
Depositing User: Mr IR Admin
Date Deposited: 20 Sep 2024 05:45
Last Modified: 20 Sep 2024 05:45
URI: https://ir.vistas.ac.in/id/eprint/6615

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