We are enhancing the governance process of our ground-breaking investment data science program with the appointment of an independent Academic Oversight Body
State Super’s investment data science program
State Super has led the pension fund market in Australia over the last four years in developing and implementing machine learning models to manage the massive amount of data available for financial market decision making.
Prior to State Super’s development, machine learning had limited application within the Australian pension fund market, but a decision to think differently, combined with a strong, responsive investment governance framework has allowed State Super to be innovative in its application of data science.
Charles Wu, Deputy CIO has been at the forefront of the development of this program, which was first announced at the i3 Investment Strategy Forum in 2017. State Super is now at a level of maturity with the data science program, that we have proactively shared our own learning with other pension funds.
Academic Oversight Body will help identify opportunities
Charles Wu stated that there are some issues to consider when using insights from more complex machine learning based models and it requires a mature governance process. He went on to say,
“State Super understands the potential value that the data science program will bring, and a robust governance framework has been developed to ensure the insights are carefully integrated with our investment process and governance framework”.
As a result, State Super has appointed an independent Academic Oversight Body (AOB) to assist with the strategic development of the investment data science capability. Dr Kollo, Professor David Michayluk and Dr Alex Antic are appointed as the inaugural members of the AOB.
This will help the investment team to identify emerging opportunities and risks with greater confidence and take appropriate action for members. CEO John Livanas explains,
“The challenges faced by our funds, of minimising downside risk while pursuing strong returns, in a liquidity constrained manner, are well known. Charles and his team have developed machine learning algorithms that have been helping us to effectively assess financial conditions and assist our decision-making processes. This has led State Super to maintain superior returns, with significantly lowered risk.
The Academic Oversight Body will assist State Super’s governance of our machine learning models and grow our investment data science capabilities, at a time when the speed of change in markets, and development of machine learning and artificial intelligence research increases.”
The AOB will assess and report on the use of data science and machine learning to the State Super Management Investment Committee, while assisting the investment team to further develop their capabilities in investment data science.
Dr Michael Kollo leads the Academic Oversight Body
Dr Michael Kollo, has been appointed as inaugural chair of the Academic Oversight Body. Dr Kollo gained his PhD in Finance from the London School of Economics, and has extensive industry experience in the application of quantitative statistical methods at Blackrock, Fidelity, Axa Rosenberg and HESTA. Michael said that:
“The increasing scale and sophistication of capital markets drives asset owners toward using more types of data and new technologies, including AI, to help in their decision making. Having an appropriate governance framework and technical resources to oversee and guide their development not only helps members get a better outcome, it is a way for State Super to tap into the best Australian academic talent.”
The other members include: Professor David Michayluk who is Head of the Finance Department at UTS Business School and earned a PhD in Finance at Louisiana State University, and Dr Alex Antic who is Head of Data Science at Australian National University.
Follow State Super’s investment data science program developments, and other news on our LinkedIn page https://www.linkedin.com/company/state-super-sas-trustee-corporation/
AOB members
Dr Michael Kollo
CEO, Qurious Analytics
Dr Michael G. Kollo is a senior investment professional with extensive academic and private sector experience globally, more recently speaking on the application of machine learning and AI in the financial services sector.
Dr Kollo gained his PhD in Finance from the London School of Economics, and has lectured at the London School of Economics, Imperial College and at the University of New South Wales. He was Chief Examiner for the externals finance programme for London School of Economics, and Adjunct Professor at Imperial College where he taught Quantitative Finance in the Masters stream. He has mentored Fintech and CybertTech start-ups in London, through the Barclays Accelerator programme, helping young organisations distil complexity to simpler, intuitive and impactful messages.
Dr Kollo's industry experience is in the application of quantitative statistical methods to improving investment outcomes in a variety of different mandates and organisations. He has led experienced global research teams at Blackrock, Fidelity, Axa Rosenberg to more recently, at HESTA a $50bn superannuation industry fund in Australia. In each of these roles he led a team of quantitative investment teams, working to create the models, and crafting the messaging and communication to global clients. He has worked extensively across the business value chain, from sourcing, mentoring and creating innovative solutions, to team management, and senior leadership communication. He is a strong thought leader who has worked closely with sales teams to transform research insights into marketable service and products. Michael brings with him a technical and articulate skill set, with a high academic pedigree and proven global experience.
He is a published author in both academic and private sector areas, with extensive 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, including Investment Magazine, World Economic Forum, and WSJ, and is a regular speaker at global quantitative research and institutional industry events.
https://www.quriousanalytics.com/about
Professor David Michayluk
Head of Finance Department, UTS Business School
Professor David Michayluk earned a PhD in Finance at Louisiana State University after completing a Chartered Accounting and Certified Public Accounting designation in Canada. He is active in the entrepreneurship community assisting and mentoring start-ups and has completed the Australian Institute of Company Directors course. He was Director of the Financial Research Network (FIRN) from 2016-2018.
He has held faculty positions at UNSW, the University of Rhode Island and he has been at UTS for 15 years, the last 4 of which were as Head of the Finance department in the UTS Business School. He has supervised more than 10 PhD students and numerous Honours students and cofounded the International Journal of Managerial Finance in 2005. His core research areas began in market microstructure and corporate finance and his interests now have expanded to include liquidity, real estate, behavioural finance, entrepreneurship, financial literacy, risk communications and retirement planning.
https://www.linkedin.com/in/michayluk/
Dr Alex Antic
Head of Data Science, Australian National University
Alex has over 17 years' experience developed across a number of industries and domains, including Federal and State government, Insurance, Asset Management, Banking (Investment and Retail), Consulting and Academia. He has expertise in leveraging Data Science/AI to deliver impact and change, by developing and managing high-performance teams, and via strategic advisory and technical expertise. Alex has recently been recognised as one of the Top 10 Analytics Leaders in Australia by the Institute of Analytics Professionals of Australia (IAPA).
https://www.linkedin.com/in/alexantic/
Twitter: @DrAlexAntic