Ascent RegTech

Recorded Webinar: The ROI of Data Trust: Quantifying the Business Value of Data Observability

Data is the fuel that keeps modern financial institutions’ motors running but if that data can’t be trusted then the decisions made based upon it, or the uses to which its put, will be compromised. That’s especially important for data that’s fed into artificial intelligence models. If the data isn’t clean, accurate and complete, then...

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Testing an Assumption: Do AI Signals Really Decay?

Alpha decay is one of the foundational assumptions in quantitative finance. The empirical literature, beginning with McLean and Pontiff’s 2016 study of 97 anomalies and replicated and refined across multiple subsequent studies, has repeatedly found that returns degrade out-of-sample and degrade further once published. The assumption sits inside almost every institutional model risk framework as...

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AI in Data Management Summit New York City

Following the success of the 15th Data Management Summit NYC, A-Team Group are excited to announce our new event: AI in Data Management Summit NYC!

Regulatory Data Handbook 2026 – Fourteenth Edition

Welcome to the fourteenth edition of A-Team Group’s Regulatory Data Handbook. Supervisors increasingly expect firms to demonstrate which rules apply, which data supports each obligation, who owns the control and how exceptions are identified and resolved. Policies and implementation programmes must now be supported by records that can withstand regulatory scrutiny. This edition examines material...