Mr Wilmot is the founder of London-based WilmotML and former head of macro investment strategies at Credit Suisse. His firm combines machine learning and artificial intelligence techniques with a long-established macro framework to forecast the global economy.

He believes that a new powerful funds management machine will likely emerge from DeepMind, the artificial intelligence company in London bought by Google in 2014. DeepMind was founded by Demis Hassabis, Shane Legg and Mustafa Suleyman in 2010.

"Officially Google and DeepMind are not working on investment," Mr Wilmot said. "I am not sure how many of you believe that. I don't.

"These are the guys that potentially have the highest credibility and the biggest capacity and the deepest pockets to apply machine learning techniques to fund management.

"And they have a lot of cash that they want to manage in this low return world. And they are mean, they don't like paying people fees."

Later, in response to a question from The Australian Financial Review, Mr Wilmot said that companies with exclusive access to proprietary data, such as Google, would have an advantage over others in funds management using machine learning and data science.

"People like Google have enough money to buy all the financial data sets and they have all these other unstructured data sets that they could potentially mine and look at to use these techniques," he said.

"Who has access to the data and what kind of data it is and how relevant it is in the decision-making process is going to be the battlefield rather than having enough cloud computing space."


Biggest barrier

Mr Wilmot said that the biggest barrier to machines disrupting funds management was lack of transparency about what is "under the hood". He said some of the machine learning methods, including deep learning algorithms, were opaque.

"Deep learning is the ultra black box," he said.

This would create issues of trust for investors.

Nevertheless, he predicted that machines would be used to screen and filter information for discretionary managers, to pick stocks, to decide asset allocation and to provide market timing indicators for discretionary managers.

"We have clearly got a whole set of techniques that are potentially incredibly powerful," he said. "This is something the world has never seen before. Asset management is a complex task.

"The thing we know about these machines is that they are beyond human in their ability to process large data sets.

"We also know they don't have the context, the intuition, the judgement that human beings do and they don't have perhaps the adaptability that humans do.

"But we do know that the guys that are at the very edge of the revolution in these techniques basically believe that machines will be able to do it all at some point."

The author travelled to Hong Kong as a guest of Credit Suisse