Generative AI in Action: Securing E-Commerce payments and safeguarding consumer purchases from fraud

The rapid growth in e-commerce backed by efficient logistics and supply chain infrastructure is reshaping the global marketplace, enabling customers to access goods and services from anywhere easily. Nevertheless, this growth has also resulted in more sophisticated fraud tactics, posing significant risks for businesses and consumers. Fraud detection systems currently struggle to keep pace with evolving cyber threats, emphasizing the necessity for advanced technologies.
Generative Artificial Intelligence (GenAI) is revolutionizing the battle against e-commerce fraud. AI can detect complex fraud patterns, predict potential threats, and address risks in real-time by utilizing advanced techniques like deep learning models, neural networks, and reinforcement learning algorithms.
This study delves into the use of generative AI in e-commerce transactions, focusing on making consumer purchases more secure. It reviews recent research on machine learning (ML)models and fraud detection technologies, showcasing how AI improves security, reduces false positives, and builds user trust. Some of the recent advancements include anomaly detection, combining supervised learning with blockchain, and applying AI to dynamic pricing strategies.
This research also considers the ethical and regulatory challenges of integrating AI into financial systems, highlighting the importance of human oversight and compliance with data privacy laws. A real-world example, such as Alibaba's use of generative AI, is highlighted to demonstrate the impact of GenAI. The study also evaluates the role of AI in protecting payment gateways and preventing online credit card fraud.
An example of a gen AI use case in Alibaba is presented, along with a critical analysis of its impact on payment gateways and the detection of online credit card fraud. Relevant data, visualized using Python, is also included.