The bibliometric analysis identified four major thematic clusters: machine learning for fraud detection, artificial ...

As fraud attempts continue to rise, data and advanced analytics are at the center of efforts by banks to prioritize faster detection. The increased digitalization of commerce has made it easier for ...

DoD promised to deliver an anti-fraud strategy by the end of July and make data analytics a top priority within that plan.

Banks can forecast the possibility of client churn using ... The post Data Science Expert’s Breakthrough Research in Fraud Detection, Anti-Money Laundering, and Marketing Analytics first ...

When using using generative AI to enhance data analytics ... Integrating GenAI and predictive analytics into fraud detection strategies guarantees ongoing progress and strong resistance against ...

By using AI to automate fraud detection ... Its corporate audit committee identified the need for improved data and analytics to support fraud detection and investigation at scale. Unfortunately, ...

Conclusion: Integrating geolocation data into fraud detection is a major leap forward in data analytics. With effective data engineering, organizations can quickly collect, process, and analyze ...

The integration of AI, machine learning, and big data analytics has significantly improved the speed and accuracy of fraud detection, while the shift toward digital healthcare, including ...

March 26, 2025 /PRNewswire/ -- A new report from Conning, 2025 Workers' Comp Study: Using Data & AI ... integration of AI and advanced data analytics into fraud detection processes is a game ...