Digital fraud is a major problem that influences the financial sector and the Indian economy. There has been an increase in financial losses in recent years due to various kinds of smart frauds like unauthorized access, stolen cards, and phishing activities. Hence, finding fraudulent behavior is critical for both individuals and financial institutions effectively. The popularity of Quantum theory with Machine Learning (QML) applications has expanded to larger audience. In this paper, Quantum Machine Learning (QML) is proposed for fraud identification in digital transactional payments. This paper presents an in-depth survey of the difference between classical neural networks and quantum neural networks on various smart digital transaction fraud detection. This paper serves as a pathway for various researchers to understand the advancements in this domain.