State Super has appointed a body to oversee the development of its investment data science capability to avoid building in biases during the learning process.
State Super deputy chief investment officer, Charles Wu, said using insights from more complex machine learning based models required a strong governance process to avoid the biases and to challenge the path of future developments.
State Super chief executive, John Livanas, said: “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 ‘Academic Oversight Body’ inaugural members appointed were Dr Michael Kollo as chair, Professor David Michayluk, and Dr Alex Antic.
“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,” Kollo said.
“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.”
Kollo had a PhD in finance from the London School of Economics and had experience in quantitative statistical methods at BlackRock, Fidelity, AXA Rosenberg, and HESTA.
Michayluk was currently head of the finance department at UTS Business School and Antic was currently head of data science at Australian National University.