65th ISI World Statistics Congress

65th ISI World Statistics Congress

IPS 1028 - Financial Data Science: Opportunity and Risks

Category: IPS
Wednesday 8 October 2 p.m. - 3:40 p.m. (Europe/Amsterdam) (Ended) Room - Onyx

View proposal detail

Participants

FR
Fernando Alberto Rocha (Chair)
PG
Paolo Giudici (Presenter/Speaker)
DR
Dale Rosenthal (Presenter/Speaker)
T
Bruno Tissot (Presenter/Speaker)
C
Elisabetta Carfagna (Organiser)

Category: International Society for Business and Industrial Statistics (ISBIS)

Organiser: Elisabetta Carfagna

Chair: Fernando Alberto G Sampaio C Rocha, Head of Statistics at the Central Bank of Brazil and IFC Executive member
Speakers:

1.      Paolo Giudici, University of Pavia, Italy “Safe Artificial Intelligence in Finance”

2.      Dale Rosenthal, Head Partner, Q36 Chicago, USA, “Data Science and finance”

3.      Bruno Tissot, Head of Statistics and Research Support at the BIS and Head of the Secretariat of the Irving Fisher Committee on Central Bank Statistics (IFC) “AI in finance: learning from central banks” 

The growth of Artificial Intelligence applications, boosted by financial data science, requires developing risk assessment and management models that can balance opportunities with risks. The proposed session aims to contribute to the on-going debate on regulations and industry standards for AI risk management models, by discussing proposals of statistical models, statistical indicators and software codes that can be employed to measure the risks of AI.

The session will include research contributions from different regions and professional roles, to reflect diversity and to achieve a shared view. Academics will present their proposed risk management models and codes; financial regulators will talk about supervisory technology models (SupTech) for the regulation of AI in the financial sectors; financial professionals will illustrate how institutions can extend their risk management models to include the risks of AI.

This IPS is proposed by the ISBIS and the ISI Special Interest Group on Data Science.


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