In 2025, the rapid expansion of digital banking has significantly transformed the financial sector by providing fast, convenient, and accessible financial services. However, this digital transformation has also led to a sharp rise in financial frauds such as phishing, identity theft, credit card fraud, and unauthorized transactions. Traditional rule-based fraud detection systems have proven inadequate in dealing with the increasing complexity and sophistication of cyber threats. Artificial Intelligence (AI) has emerged as an advanced and effective solution for detecting and preventing financial fraud in digital banking. By utilizing machine learning, deep learning, and predictive analytics, AI enables real-time transaction monitoring, anomaly detection, and risk assessment. AI systems can process vast amounts of data, identify hidden patterns, and detect suspicious activities with greater accuracy and speed compared to conventional methods. This study focuses on the role of AI in enhancing fraud detection mechanisms in digital banking. It highlights the key techniques, benefits, and challenges associated with AI implementation. While issues such as data privacy, high costs, and model transparency remain concerns, AI continues to play a crucial role in strengthening banking security and ensuring safer digital financial transactions.
Aditya Dhiman (Mon,) studied this question.