Sholthana Begum.

Regulatory Genome Project names Technology Group Chair

25 January 2023

The article at a glance

Sholthana Begum of the UK’s Financial Conduct Authority is appointed Chair of the Technology Group of the Regulatory Genome Project at Cambridge Judge Business School.

Sholthana Begum of the UK’s Financial Conduct Authority is appointed Chair of the Technology Group of the Regulatory Genome Project at Cambridge Judge Business School.

Sholthana Begum, Head of Data and Data Strategy at the UK’s Financial Conduct Authority (FCA), has been appointed as Chair of the Regulatory Genome Project’s Technology Group.

Recognised as a thought leader and a pioneer of RegTech and Data, Sholthana was named in the 2021 DataIQ power list of the most influential people in Data. She has held various roles in frontline supervision, central banking and finance, bringing many years of valuable experience to the FCA in its mission to become a digital- and intelligence-led regulator. Her counsel is often sought after by other central banks, regulators and private bodies across the globe.

The purpose of the RGP Technology Group is to support the Cambridge Judge Business School (CJBS) vision to build the Cambridge Regulatory Genome (‘CRG’), an open information structure for organisations and comparative analysis of regulations across jurisdictions. Acting as an ambassador for the RGP, the Technology Group will provide insights on opportunities for collaboration with various institutions in an Academic context. The Group will also be serving as a sounding advisor to the RGP Leadership and to CJBS.

Dr Giovanni Bandi, Executive Director of the Regulatory Genome Project, said: “The RGP Technology Group will help the RGP team by providing insights in Regulatory Technology applications and methods to use CRG in a data-driven regulatory framework. Sholthana Begum is certainly well-positioned to lead the Group in providing inputs, ideas, and introductions on key strategic initiatives to foster the adoption of the CRG as the AI-based comparative standard for Machine Learning.”