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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.

How emerging market regulators may be helped by machine learning.

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 Assisted Capacity Building for Standards Implementation (‘MASI’). At Cambridge Judge, the project will be handled by the Regulatory Genome Project, a collaboration to develop and support the adoption of an Artificial Intelligence-based open information structure to enable the organisation and comparative analysis of financial regulations across jurisdictions.

MASI aims to provide a capacity building tool for emerging markets jurisdictions to assist self-assessments against the IOSCO core principles and to facilitate comparisons with other regulatory frameworks from more developed jurisdictions.

Madrid-based IOSCO is the leading international policy forum for securities regulators and is recognised as the global standard setter for securities regulation. The organisation’s membership regulates more than 95% of the world’s securities markets in some 130 jurisdictions.

IOSCO aims through its permanent structures

  • To co-operate in developing, implementing and promoting internationally recognised and consistent standards of regulation, oversight and enforcement to protect investors, maintain fair, efficient and transparent markets, and seek to address systemic risks.
  • To enhance investor protection and promote investor confidence in the integrity of securities markets, through strengthened information exchange and co-operation in enforcement against misconduct and in supervision of markets and market intermediaries.
  • To exchange information at both global and regional levels on their respective experiences to assist the development of markets, strengthen market infrastructure and implement appropriate regulation.