How AI Can Help Address Contract Challenges During LIBOR Transition

The transition from LIBOR to alternative reference rates presents numerous challenges, particularly when it comes to renegotiating and operationalizing fallback language for both existing and new contracts. Although uncertainty remains among market participants and industry guidance continues to evolve, adopting a “wait-and-see” attitude before amending contracts is not considered wise. Financial institutions should consider acting […]

Improve Threat Intelligence with Data Analytics and Machine Learning

The cybersecurity industry is increasingly producing enormous amounts of raw threat data. The sheer volume of information threat researchers must sift through makes it difficult to collect, analyze, and research that data on time. This in turn limits their ability to understand what data is valid and useful and whether threat artifacts will result in […]

Trust and Understand AI for Successful Transformation with Regulatory Compliance

When considering AI, you may have potential questions or simply want to understand AI better. Trusting and understanding AI is key to a successful AI transformation. This is especially pertinent in industries with stringent regulations, such as financial services, banking, and healthcare. After all, if the AI gets it wrong, people may be adversely affected.

Tackling Clinical Trial Data Overload with Data Lakes and Machine Learning

As clinical trial complexity increases, trial sizes grow, and data variety and volume explode, this problem is only growing worse. For sponsors and CROs who are experiencing this challenge, within and across studies, a clinical data and analytics hub built on big data, data lake architecture offers great promise. This article explores how a data […]