Job seekers need not fear robo advisors, number crunching softwares, and artificial intelligence killing jobs in asset management, experts say. Here are some experts’ views from a recent conference in Singapore. 

Job Creation

“The theory that technology in the asset management industry is going to be a huge job killer is both inconsistent with economic theory and the evidence,” said Eddie Fishman, managing director of The D. E. Shaw Group, who was speaking at the Milken Institute 2018 event held in Singapore.

“Years of labour theory has predicted that years of job destruction has led to job creation. So we see in the data that asset management employment is at an all-time high,” said Fishman, whose firm is involved in global investment and technology development for the industry.

Traditional Barriers Gone

“The amount of capital stock in the form of technology, that complements the human capital in the industry is at an all-time high. People are getting more productive every year, they make more money every year, and the amount of technology support they have is greater every year,” said Fishman.

Technology has enabled asset management firms today to recruit talents globally, which they otherwise could not. One example was WorldQuant, which held an international quantitative competition using a web platform.

Astounding Results

“The results were astounding. There was a team of three young women in France who ended up winning the competition. They competed for six months, from France, and we had 11,000 entrants,” said Michael DeAddio, president of WorldQuant, who was also speaking at the event.

He went on to explain that one of the women in that team could not get to France physically to finish the last round of competition. Hence, they resorted to using WhatsApp video to work on the problem together, even though they are not physically together.

Extending Human Limitations

Other fund managers are using technology as a way to speed up the investment process and aid in overcoming human limitations and biases.

“We’re using it (technology) as a leverage point to speed the investment process because the idea of velocity is becoming so critical these days, so we have a number of tools to speed the pace of integration of data into the investment process,” said Taylor O’Malley, president of Balyasny Asset Management.

Significant Shift

It is the risk-taking process that O’Malley saw the most significant shift. One of the biggest limitations for us is those portfolio managers who don’t scale. One of the primary drivers they don’t scale is mental issues: fear of scale, fear of growing too large, fear of volatility.

When senior fund managers use technology to follow trades made by these portfolio managers, it helped them overcome human fears, O’Malley said.

For us, technology is driving returns and facilitating that. In that same token, technology is driving greater market efficiency. We have quantitative funds using quant tools.

Tech Generates Unique Perspectives

Another positive result of using technology is the narrowing of the focus to generate unique perspectives, which resulted in better returns. Three years ago, an average analyst or portfolio manager may have a coverage of a hundred names, noted O’Malley.

“But in contrast that by today, I get a portfolio manager with a coverage of fifty names by each member of their team and generates twice the alpha, than someone who does who has a hundred names under coverage in their universe,” he said. “What I don’t see as much are the AI fears, the machine learning, all the heuristics of assisted-tech taking over the industry.”

Big Data Overrated

“There are two terms that drive me crazy: Big data – that was the most overused marketing term in 2016 and Quantamental is the other in 2017,” said O’Malley. For example, if someone can get revenue data purely for the iPhone (in isolation), he is pretty sure it can be monetised. However, many data sets are only “incrementally helpful” while others provide “very limited advantage for very short periods of time” without consistent predictive power, he noted.

DeAddio concurred, saying that terms like “Quantamental” and “Big Data” drive him nuts for multiple reasons. “Data is just data. It’s the predictive power and what you do with the data that really matters, so it should be called big prediction or something that is a little more thoughtful,” DeAddio explained.

Think Small Data

“In other cases, even thin alphas or small signals provide tremendous value, as long as one gets good signal quality around it from other sources, like those that a fundamental stock picker would typically find,” said O’Malley.

“So data is integrated into the (investment) process but it’s a much lower value than people perceive it to be. The stuff that people talk most about tends to be the least value. I don’t know if you met someone who is doing big data on healthcare or big data on insurance – that’s the stuff that’s interesting,” he said.

Yield Still Low

While quantitative funds may use tools and machine learning techniques to assess the value of data before purchasing, asset managers have to accept that not every data set is useful. Sometimes, they could trial a thousand data sets but maybe land a yield of 25 per cent, noted DeAddio.

“From a statistics perspective, not every data set has to work, sometimes you buy them and they don’t work out, so you don’t know the value of them until you put your researchers on them for 6 to 9 months and then see if you can actually find value in it,” said DeAddio.

Cost of Doing Business

Hence, the use of data is a multi-step process, starting from the initial assessment, the negotiation, the buying of data, and then finally the research.

“And if you think you’re going to get every single one right, you’re fooling yourself. The world is increasing so quickly the data types you have, you’ll make some mistakes. It’s just the cost of doing business in the data world,” DeAddio noted.


We would like to thank Valerie for her contribution to this article. She has been a sell-side research analyst at HSBC and Macquarie and continues to work in the field of investment. She is a senior mentor at Springboard Talent Management.

Springboard is a platform that nurtures young professionals intending to enter the investment industry. We are in the midst of developing a practical curriculum with veterans in the field of real estate investments, private equity, and fintech. If you wish to get more career advise, please feel free to write to val AT

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