Investors check stock prices at a brokerage office in Beijing, China, January 2, 2020. REUTERS / Jason Lee

Chinese fund managers, grappling with a growing list of publicly traded securities and mountains of data, are rapidly adopting machine learning and other types of artificial intelligence (AI) to increase efficiency and boost yields.

From using computers to analyze news and research reports, to crunching numbers, to robots choosing stocks, the move comes as foreign players expand their footprint in the retail industry. $ 3.4 trillion mutual fund in China.

Although AI has already been widely used in China’s gigantic e-commerce and manufacturing sectors, it is now being embraced by asset managers as Beijing aims to further digitize the economy and close the technology divide. with the western world.

Last week, Zheshang Fund Management Co launched a fund that uses robots to predict market outlook and select stocks. It came after China Asset Management Co (ChinaAMC) announced its partnership with Toronto-based AI firm Boosted.ai.

“I think this is a must. Every major player is actively looking for AI solutions. The competition is really tough,” said Bill Chen, chief data officer of ChinaAMC, which managed $ 246 billion in assets at the end of last year.

Global fund managers such as BlackRock Inc (BLK.N) have used artificial intelligence (AI) to analyze fundamentals, market sentiment and macroeconomic policies over the past two years in order to gain an advantage in investment.

“Companies like BlackRock have very powerful advanced technology. They definitely lead us into AI, by at least several years, ”Chen said. “But I think we understand the Chinese market better.”

The increased use of AI by fund managers in the world’s second-largest economy comes as Beijing steps up its digitization campaign, a trend accelerated by the COVID-19 pandemic and which is increasingly clashing with the West on technology policy.

China’s listing reforms have increased the number of state-owned companies, leading to a data explosion that is also fueling demand for AI, said Zhou Yu, chief product officer of ABC Fintech, an AI firm based on it. in Beijing.

ABC Fintech counts asset managers such as China Universal Asset Management and Hwabao WP Fund Management Co among its clients, and serves as their data factory, Yu said.

REGULATORY CHALLENGES

Growing investments in AI are also fueled by early signs of success.

The Zheshang Fund’s first AI-powered fund, the Zheshang Intelligent Industry Preferred Hybrid Fund, has gained 68.34% since its launch in September 2019, according to its first quarter report, compared to a gain of 21.64% in its benchmark index, which is a combination of equity and bond indices. .

The fund has built an “AI Beehive strategy model” in which robots team up like humans to buy stocks. Over 400 robots compete for the right to make decisions as their models constantly evolve through trial and error.

Peter Shepard, chief executive of MSCI Research, said that instead of providing superhuman intelligence, AI provides a superhuman scale that will open up new sources of information that will lead to new levels of insight and efficiency.

“These new tools alone cannot predict the future better than people, but they are essential in unlocking new, alternative and unstructured data sets that will continue to transform the investment process.”

“Artificial intelligence will be a big advantage,” said Larry Cao, senior director of the CFA Institute, author of several reports on AI-based investments. “The hard truth with AI is that bigger companies can invest a lot more resources.”

Some Chinese industry officials, however, have expressed concerns that using machine learning algorithms to select stocks and better returns could face regulatory challenges.

“From a regulatory standpoint, you have to go through a lot of compliance procedures. You have to write reports on your decision making. Some AI-based models are like black boxes and inexplicable,” Yu said. ‘ABC Fintech.

“This is hardly acceptable to regulators.”

As learning algorithms are increasingly used in trading rooms, local fund managers are working with regulators to try to craft new standards for the industry.

“One of the biggest hurdles we face … is that we are highly regulated,” said Chen of ChinaAMC. “Every decision you make, you have to be responsible for that decision, and you should be able to explain a decision when you’re losing money.”

Our standards: Thomson Reuters Trust Principles.



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