E91 - Dr Michael Kollo - Explainable AI’s Place in Investment Fund Management and Superannuation

If someone told you something like;

“If you leave your house tomorrow, something bad will happen.”

What would you do?

You’d probably either be horribly confused, slightly offended, or maybe you’d even laugh, thinking it was all some big joke. Either way, you’re left with no explanation.

So, obviously, you ignore the encounter. Whether or not something bad happens the next day is a whole other story.

Without understanding how this stranger arrived at this conclusion, you have no reason to believe them.

Then, how easily do you believe a machine learning model without knowing how it came to the results that it did? Or do you need an explanation?

Meet Michael Kollo

Michael’s Role as a Data Science Leader at Qurious Analytics

Dr. Michael G. Kollo is the Founder of Qurious Analytics. Qurious Analytics aims to breach the gaps formed from the lack of technical expertise and effective communication skills through research, education and mentoring for both technical and non-technical audiences.

Michael is a seasoned executive and quant from the asset management industry. He has led research teams at Blackrock, Fidelity, Renaissance Asset Management, and more recently in Axa Investment Managers and Hesta, a 60bn asset owner in Australia. As well as leading quantitative research and investment teams in London, San Francisco and now Sydney, he recently joined an AI technology startup as Chief Economist, dealing with the impact of automation technologies on the global workforce and industries. Michael is known in the industry as an AI and quantitative expert, both in the fields of asset management and technology startups. He frequently speaks at conferences, both locally and globally on topics of intelligent systems, forecasting in financial markets, ethical AI, reasoning systems and explainability, and impact of automation in global workforces and economies.

Michael’s Other Work in the AI Industry

Michael obtained his PhD from the London School of Economics, Imperial College and at the University of New South Wales. He was the Chief Examiner for the external finance programme of the London School of Economics, and the Adjunct Professor at Imperial College where he taught Quantitative Finance in the Masters stream. He has also mentored Fintech and CyberTech startups in London through the Barclays Accelerator programme.

On top of that, Michael is a published author in both academic and private sectors, with thought leadership pieces, white papers, and the opening chapter in the best selling "Big data and machine learning in quantitative investment.” Michael writes regularly for industry publications on the topic of AI and alternative data. He is also a regular speaker at global quantitative research and institutional industry events.

Explainable AI, AI adoption, and Quant

In this exclusive analytics podcast episode, Michael shares:

• How human trust is under threat with rise of AI
• Research topics that have stuck with Mike and how quickly the world changes with AI
• His background and work in AI in the Quant field
• How AI adoption is progressing in the background, especially in investment fund management and superannuation
• Main reasons for the lack of adoption of AI in these industries
• How explainable AI plays a part in these industries
• A case study of when explainable AI was critical to success in these industries
• What area he would focus on if he was starting his career today
• What he would tell his 20-year-old self if he could

If you are in the executive management team in the financial industry trying to understand how to improve AI adoption in your organization, this is the episode you do not want to miss out on.