By Peter Rushton  |  20 February 2017

Peter Rushton is a Senior Consultant to Essentia Analytics. Previously, he was a Partner and Portfolio Manager at Cheyne Capital Management.

In a world where pressure on investment management margins is unrelenting, the obvious place to seek savings is in people costs. Automation and outsourcing of back and middle office functions offers some relief. But the fact is, passive funds are able to offer much lower pricing because they have far lower front office costs to contend with. As the portfolio managers of the 90’s and 00’s reach retirement age, savvy investment firms have an opportunity to use technology to embrace the “juniorization” of fund management: the employment of more junior, less expensive people, in more front office roles.

Conventional wisdom dictates that seasoned portfolio managers are to be preferred over junior investors. Asset allocators want to see grey-haired, battle-scarred fund managers, who have weathered multiple market cycles, and who can explain how the firm is managing client money. Surely, experienced investors are an important part of the investment management value proposition.

But does the acquisition of that experience need to be as linear as it has been, historically? Could technology be used to help younger investors get up the learning curve faster? And at the same time, could technology teach these more junior investors to articulate and prove a cohesive, consistent investment process – something that firms with large senior portfolio manager teams have actually struggled to do, to date? We believe it can.

“Does the acquisition of that experience need to be as linear as it has been, historically?”

“Juniorization” took hold on the sell-side during the financial crisis, with more and more responsibility being handed over to younger employees at investment banks, which faced similar challenges of high people costs and soft demand for their products.

It can be argued that the sell-side is a young person’s game, with its unrelenting hours and aggressive tempo – more so than the buy side, at any rate. But juniorization has already begun on the execution trading desks of the buy-side, where long-standing relationships with the Street have been replaced in importance by quantitative research and programming skills.

The fact remains that if active fund managers are going to reduce their cost bases and bring performance net of fees back ahead of index funds, they will be forced to figure out how to use less expensive investors without jeopardising performance and investor confidence. The question is how?

As author and Carnegie Mellon professor Randy Pausch pithily put it: “Experience is what you get when you didn’t get what you wanted.” In other words, we value our prior experience because we have learned from our mistakes and misfortunes. The fact that we have seen which practices succeeded, as well as which failed, is what makes us better in our chosen fields over time. Therefore “experience” is typically seen as the benefit of the accumulation of good and bad lessons over time.

Perhaps not much can be done to speed the passage of time – some important lessons can only be learned by “being there”. But technology can now accelerate the amount of learning any one of us can gain per unit of time worked. Acquiring experience as an investor need not be left entirely to time, reading and osmosis, as it has in generations past.

“Technology can now accelerate the amount of learning any one of us can gain per unit of time worked.”

First off, data analytics can be used to derive the actual investment process best practices from a given firm’s most skilled investors. That’s a useful exercise in itself, if only to ensure that the investment process being used is consistent with what the firm is selling to investors. But the next step is to use technology to train newer investors to follow that process, and to show them, on an ongoing basis, what they are doing that’s working and what isn’t.

Technology can also supercharge the learning process is by automating the collection of data about the contexts in which each investment decision – whether it’s a decision to trade or not to trade – is made. In other words, recording a rich and accurate “game tape” on each position, which can be watched back later.

Finally, technology can be used to automatically prompt investors, regardless of their tenure, to avoid making the same mistakes repeatedly, by notifying them when a detrimental (or beneficial) pattern may be reappearing.

Technology need not replace the investor as a fundamental decision-maker – indeed, artificial intelligence is not yet at the stage where it is able to do this – but it can be used to empower the decision-maker by enabling accurate and structured reflection, in the same way that athletes use game tapes and data analytics to continuously improve their performance.

The investment management industry is historically poor at reflection, thus the sole reliance on time as a teacher. It uses investment performance – a very noisy and imperfect measure of skill, which provides very little information about what to do differently in future – as its feedback loop. As a result, portfolio managers tend to reflect only for the sake of client reporting, and not in a concerted effort to improve. Yet academic research shows that people who build reflection into their processes learn faster than those who use that time to just “do more”.  

The happy byproduct of using technology to guide, facilitate and measure an investment process is the ability to prove that the process itself is followed, and that it works. In light of the active management industry’s weak performance, clients are less and less persuaded by vague investment processes that rely upon a traditional “star” culture. Investors want to see a clear, repeatable decision-making process that is the subject of constant incremental improvement, with consistent, comparable data across individuals, teams and time.

“Investors want to see a clear, repeatable decision-making process that is the subject of constant incremental improvement…”.

To be fair, behavioral analytics services like Essentia Analytics, which make it easy to separate signal from noise when reflecting on our past investment behavior, have only become available recently. But there’s no longer any reason to rely upon our own biased memories to understand the lessons of our experiences. By implementing a technology-powered data-driven feedback loop, anyone – even a junior fund manager – can derive the lessons of experience quicker, more clearly and more accurately.

In our view, this is the future of the investment management industry.  Aided by technology, junior employees will have the opportunity to learn the same lessons of experience faster and more consciously than their older colleagues did. That doesn’t mean that the industry won’t need “seasoned” investors – it will just need fewer of them.

The same technology is also relevant to attracting and retaining the best next-generation employees. Recent graduates expect data to be collected, analysed and put to good use to solve problems. The best among them expect their employers to be provide rigorous and ongoing training to help them nurture their skills. The ability to learn is a major motivator for them in choosing a job.

It is clear that the active investment management industry needs to evolve, both to offer better products to its clients and to find business models that can profitably supply those products.

We believe that technology that enables cheaper, younger human capital to learn at an exponentially faster rate, and that makes it possible to articulate and prove a cohesive, disciplined investment process, will ultimately be what separates the survivors from the also-rans.