Name: From Financial Markets to the Societal Applications of AI and Bias
Start: 2019-11-28T12:00:00+11:00
End: 2019-11-28T13:00:00+11:00
Location: ANU College of Business & Economics

The study of financial markets has attracted some of the brightest mathematicians, statisticians and psychologists over the past decades. Statistical methods to forecast returns, risk and build portfolios have been heavily researched, implemented and used within that industry. Equally, the technical pitfalls of these methods have been shown from identification vs forecasting to causation vs correlation, and transparency vs complexity of models.

I will explore some of the major elements of quant (Data Science) used in finance, and their potential applications and lessons for other industries, specifically industry and government profiling citizens for loans, insurance and potential criminal activity. Focusing specifically on how these models function, their explainability, their tilts (eg ‘bias’ that has been talked about), and how misunderstood they can be in a social-contract context.

Dr Michael G. Kollo

Mike is an investment executive, a writer, a speaker and a self-confessed ‘translator’ for technical topics to wider audiences. Michael gained his PhD in Finance from the London School of Economics (LSE) in the UK, before joining a suite of sophisticated institutional asset managers (Blackrock, Fidelity and Axa) where he led research teams and spoke globally on applying quantitative (data science) techniques in asset management, machine learning and AI in society, the future of work and applications of alternative data. More recently, Michael moved back to Australia, joining the super industry as a leader in quantitative finance, and establishing the quantitative team for HESTA ($50bn fund). Michael continued to keep touch with academia, holding the Chief Examiner for Corporate Finance title at LSE for a decade, and teaching Masters of Finance courses at Imperial College (rated as the top lecturer), and NYU. He is a published author in the application of machine learning to investing, a contributor to WEF AI / Fintech panel, and a highly respected member of the quantitative community in both the UK and Australia. More recently, he started his own consultancy focusing on application of AI in financial services, as well as a global podcast (The Curious Quant) with a focus on the wider implications of AI in society. Michael enjoys good intellectual banter, philosophy, psychology and mixed martial arts.

Come grab some pizza, mingle with the illuminati of the Canberra Data Science community, and hear a fantastic talk!

Alex A.

Canberra R Users Group

Technology

Open Source

Big Data

Data Analytics

R Project for Statistical Computing

Data Visualization

Sarat

Venkat B Rao

Gigi D'Souza

Zulgerel Jenkins

Nick S.

Ramee El

Eugene Dubossarsky

From Financial Markets to the Societal Applications of AI and Bias

ANU College of Business & Economics

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Canberra R Users Group

From Financial Markets to the Societal Applications of AI and Bias

Canberra R Users Group

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