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Artificial Intelligence in E-Commerce Fraud Detection: A Paradigm Shift in Digital Security

Authors:

Dr.Swapna Pavan G,

Assistant Professor,

CS MCA department Davangere University Davangere.

Ms.Anu V B,

Assistant Professor,

GM University Davangere.

Mr.Manjunatha K V,

Assistant Professor,

GM University Davangere

Abstract: The rise of e-commerce has made shopping more convenient and accessible, but it has also led to an increase in online fraud. Fraudsters are using advanced techniques to carry out activities such as fake payments, account takeovers, and return fraud. These threats cause financial losses and damage the trust between businesses and their customers. Traditional fraud detection systems, which rely on fixed rules, are often too slow and outdated to keep up with these fast-changing threats. Artificial Intelligence (AI) offers a smarter, faster, and more adaptive approach to fraud detection and prevention. By analyzing large volumes of data in real time, AI can identify unusual patterns and behaviors that may indicate fraud. Machine learning algorithms can learn from past data to detect both known and new types of fraud, while also reducing false positives. Techniques like behavioral analysis, anomaly detection, and predictive modelling help e-commerce platforms respond to threats more effectively. As digital transactions continue to grow, using AI for fraud prevention has become essential. It helps businesses protect their customers, reduce losses, and maintain a secure and trustworthy online shopping environment.

Keyword: Artificial Intelligence (AI), E-Commerce, Fraud Detection, Machine Learning, AI in Fraud Prevention.