Leveraging data science in investing
Global Investment Insights
with Dr. Alex Antic
Head of Data Science, Software Innovation Institute, Australian National University (ANU)
Member, Academic Oversight Body, State Super (SAS Trustee Corporation)
Alex is currently the Head of Data Science at the Australian National University (ANU), and a senior executive of ANU’s new flagship initiative – the Software Innovation Institute (SII). He has recently been appointed as a member of State Super’s inaugural Academic Oversight Body, tasked with enhancing the governance process of their ground-breaking investment data science program (Read more here).
Currently, the overall focus of his work centres around promoting and advancing the use of data science and AI to support evidence-based decision making, particularly in the areas of health, government and financial services. His specific remit spans three pillars, namely:
Educating and training the next generation of data scientists and industry professionals,
Leveraging translational research in emerging areas of data science and AI to help organisations deliver impact and change, and
Providing strategic advisory and technical expertise to help organisations meet their strategic goals.
Apart from sharing his expertise via LinkedIn and his website, Alex provides mentorship in data science, presenting regularly and running workshops at international conferences and industry events.
Alex spoke with GII and shared some of his insights in this exclusive profile interview.
What emerging trends, innovations and thematics excite you about the future of investing?
It has been exciting to see the uptake of data science, AI and evidence-based decision making, as drivers of investing. This has allowed the investment community unparalleled opportunities to make the most of the incredible amounts and diversity of data available and greater agility to respond to rapidly pivoting markets.
It is also positive to see the increasing use of unstructured data in the investment analysis process, by leveraging such data as text, social media, sentiment, audio and video imagery, including the use of machine learning at scale.
CleanTech (ie sustainability) and automation are of particular interest to me and I think that demand for them will continue to grow as innovation in, and application of, AI continues to soar.
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The future of investment lies in the intersection of
human and machine decision making.
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I believe that ultimately the future of investment lies in the intersection of human and machine decision making, leveraging emerging tech and its ability to derive insights from vast troves of complex and varied data, coupled with the expertise of portfolio managers and human insights.
What do you see as the biggest challenge facing the institutional investor community currently and what changes would you advocate be implemented in pursuit of better investment outcomes?
I think it is imperative for the investment community to increase its data literacy, especially at senior levels, when operating in a data-driven, evidence-based, decision-making paradigm. It not only helps senior management question, understand and advance insights and decisions made, but also helps them better understand realistic expectations amidst the proliferation of misunderstanding and hype surrounding AI.
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It is imperative for the investment community to increase
its data literacy, especially at senior levels.
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There is growing demand and appetite for the incorporation of AI ethics principles within the entire investment process, and especially in the use of AI. The notion of responsible AI will become even more important as the investment community learns how to mitigate bias and risk, and how to ensure fairness and ethical use of AI, when making investment decisions on behalf of their investors. As such, I think that the adoption of government and industry ethics frameworks and governance processes - if not regulation - will become more common in the near term.
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The notion of responsible AI will become even
more important…when making investment decisions.
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Beyond this, I think sustainable investing will grow from a niche to a norm.
Where do you see greatest investment opportunities over the near term (three years)?
COVID has caused one of those major structural changes that has had a monumental global impact, resulting in an obvious slowdown in economies. However, I think it will also accelerate a number of trends. I believe that the sudden surge and interest in healthcare, disease prevention and HealthTech will not abate anytime soon, with increasing opportunities in broader healthcare and AI innovators in this space.
Further, COVID related opportunities include e-learning and remote work (think telecommunications and cloud).
The subsequent shift away from globalisation to local supply chains, for instance, may see an increase in demand for broader automation capabilities, and subsequently, the AI innovation and infrastructure that enables it.
In regard to e-everything and e-anything, I see continual demand in streaming services, online advertising-based business models, cybersecurity and data-enabled agriculture, and not just AgTech and the growing broad use of Internet of Things (IoT) technology, but also in relation to the whole food-based sustainability movement.
Can you share a personal or career specific story that has had a significant impact on you, which can serve as practical advice to others?
During one of my earlier roles, I was fortunate to work for a fund-of-hedge-funds when hedge funds were all the rage. This afforded me the opportunity to meet some amazing and influential internationally recognised people in the investment space, and two in particular stand out.
The first is Nassim Nicholas Taleb, who I was lucky to meet early in my new role. We had a fantastic discussion around all things investment and risk, and talked about his incredible book ‘Fooled by Randomness’.
I walked away from that conversation learning one important lesson, you cannot remove the human element from analytics and this has served me well throughout my career.
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You cannot remove the human element from analytics.
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The other person who taught me a valuable lesson was Myron Scholes. Beyond discussing the famous Black-Scholes model, I took away from that conversation the incredibly valuable lesson that analytics is difficult to sell. This is something that has been reinforced many times during my career, and has helped me learn how to garner trust in people when it comes to helping them use analytics for decision making.
Disclaimer
All information contained within this publication is general advice only, as the knowledge levels and needs of all individual and corporate investors vary greatly this publication should not be used solely as a decision-making tool, further opinions and information should be sought before making an investment decision. It is the recommendation of Global Investment Institute (GII) that you seek the opinions of a fee-for-service, independent investment adviser before making any investment decision.
The authors, directors or guest writers may have a financial interest as investors, trustees or directors in investments discussed or recommended in this document. It has been assessed by the editors that these financial interests have not had an impact on the material contained here within.
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