Machine learning’s risk/reward challenge | Top1000Funds

AI will have a huge impact on financial services, particularly investment and risk management, in the next five years, a panel of experts said at the Fiduciary Investors Symposium at Stanford University. Machine learning systems that analyse data to mimic human cognitive behaviour around problem solving and thinking are growing as more data and cheap computer power become available.

Machine learning has the potential to generate alpha and affect business processes. Data is automatically processed, collected and presented by machines, rather than people within organisations, said Kay Giesecke, professor of management science and engineering at Stanford University, who said many more research projects in his department have been focused on AI over the last five years.

Data is king

As data has led to better insights, decisions and outperformance, its accumulation has become key. We will see trillion-dollar companies in the next five years that have grown not through producing widgets but through the mass collection of information, predicted Jagdeep Singh Bachher, chief investment officer University of California Regents. Taking the energy sector as an example, he said data accumulation would grow with the shift from centralised to decentralised sectors and economies.

The explosion in the flow of assets to exchange-traded funds and quant strategies has been driven by the “idea that data creates better alpha” Bachher said. Moreover, it is driving the University of California Regents’ own direct investments in companies. It now invests in Ola, India’s rival to Uber, where data patterns providing insight on behaviour and dynamic pricing are key to the company defining how it charges customers, driving the value of the business. In another example, Bachher cited the tech companies vying for access to healthcare records and data. He told delegates that investment in data and data sources was an area they should feed.

“It could lead to better insights to decision-making,” he said.

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Machine learning’s risk/reward challenge | Top1000Funds.com.