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machine learning (ML)

How emerging market regulators may be helped by machine learning

IOSCO and Cambridge Judge Business School collaborate on a machine-learning pilot to assist emerging-market regulators. The International Organisation of Securities Commissions (IOSCO) and Cambridge Judge Business School announced today (9 March) a pilot project for the development of a Machine…

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How emerging market regulators may be helped by machine learning.

Regulatory Genome Project announces new participants

The Regulatory Genome Project (RGP) announces four new participants: the Abu Dhabi Global Market Academy, Dow Jones Risk & Compliance, Invesco and Northern Trust.  The Regulatory Genome Project (RGP), a pioneering initiative to reduce fragmentation in how information about regulatory requirements is shared…

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Finextra: Mastercard joins Regulatory Genome Project

The Regulatory Genome Project at the University of Cambridge will collaborate with CMS, Grant Thornton UK LLP, Macfarlanes and Mastercard to address the issue of regulation in digital era. The new initiative will create an inclusive and easily accessible repository…

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Genome’s first industry collaborators

First industry collaborators: CMS, Grant Thornton UK LLP , Macfarlanes, and Mastercard to collaborate with the Regulatory Genome Project. Dr Robert Wardrop Regulation in the digital era is highly complex and globally fragmented, with rules changing at a rapid pace.…

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Steering clear

Artificial intelligence can transform the workplace but managers need to avoid four key "AI dysfunctions" including algorithmic bias, says article co-authored by Dr Stella Pachidi of Cambridge Judge. Dr Stella Pachidi Artificial intelligence holds great potential to transform the workplace,…

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AI and COVID-19

Five important challenges in dealing with the coronavirus crisis can be addressed through machine learning and artificial intelligence, says article co-authored by Professor Stefan Scholtes of Cambridge Judge. Professor Stefan Scholtes Five of the most important challenges in responding to…

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