This article will explore the ways in which data science is driving change in finance, focusing on risk management, fraud detection, and other innovative applications.

Amidst the ever-evolving landscape of data-driven industries, the battleground against fraud and money laundering remains relentless. However, a ray of hope emerges from the pioneering research of ...

How have AI and machine learning improved fraud detection in the fintech industry? What specific applications does this technology touch, and what mechanisms complement it?

In addition to his work on fraud detection, Sravan Kumar Pala has explored the role of big data analytics in revolutionizing customer experience in banking.

He's now the co-founder and CEO of Sift Science, a growing fraud detection startup grounded in machine learning. Recently, I talked with Tan about how career adversity led him to "embrace the weird," ...

As companies continue to innovate and embrace new technologies, utilizing geolocation data will be key to advancing fraud detection efforts.

Generative AI can produce similar payment sequences, simulating a fraud attack on a card, which augments training data to assist the fraud detection ML tools and help them to perform better.

Opinion: Science Needs Better Fraud Detection—And More Whistleblowers An influential paper on amyloid protein and Alzheimer’s disease potentially fabricated data. Why did it take 16 years to flag?