Leveraging Machine Learning and Data Visualiz...

Leveraging Machine Learning and Data Visualization for Real-Time Fraud Detection in FinTech

Author Name : Saugat Nayak

ABSTRACT Self-generated complexity and the growth in the volume of digital operations indicate that fraud remains a significant threat to the FinTech industry, sourcing the need for more effective fraud prevention solutions. The purpose of this paper is to review the utilization of ML and tools for data visualization to improve the timely identification of fraud. Machine-level Algorithms like random forests and LSTM networks are used for better fraud detection in contrast to decisions that traditional rule-based systems could make. These models learn the new fraud patterns with an improved ability to identify the negatives while minimizing the positives. Furthermore, applying heat maps and other interactive dashboards gives the fraud analyst a quick and efficient way of decision-making. Therefore, this paper recommends sloth ML and visualization tools to enhance fraud detection systems and build customer trust