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Digital transformation and technology in alternative investing – CAIS 2018 preview

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Such has been the pace of technological innovation over the last decade that we have never been more connected with one another. 

The volume of data generated by social media platforms is transforming the way that fund managers analyse the markets – using sentient algorithms to analyse unstructured data sets such as Twitter feeds, GPS data, etc – while the sheer processing power of machines has led to historic milestones, such as AlphaGo beating Lee Sedol, the world’s number one Go player last year.

Heck, even technologies in movies like Total Recall are becoming science fact. Intel has claimed that virtual reality (VR) will remove the need for humans to physically travel the world. Intel CEO Brian Krzanich believes that the merging of digital and physical worlds will change the world of travel. 

Location-based VR is the next big thing – using VR in specific locations such as the shopping mall, the classroom, or the museum to enhance one’s experience. 

“I had an amazing experience today. I led 250 people in wingsuits off the ledge of a helicopter in Moab, Utah. I hiked with them near a huge waterfall in rural Vietnam,” wrote Krzanich in a January blog1. Using headsets like the Oculus Rift, we are now capable of travelling to Mars for a vacation, just as Arnold Schwarzenegger’s character does. 

Combining Intel RealSense” depth sensing technology and volumetric video efforts, Krzanich believes that Intel will be at the centre of unlocking the potential of all this data and offer people a variety of ways to enjoy immersive travel. This is the world we now live in. 

Next February will be the fifth instalment of the Cayman Alternative Investment Summit (CAIS), hosted by Dart Enterprises. The impact of technology on the alternatives industry will be the theme of the three-day event, entitled: Wired: The Rise of Alternative Investments in a Digital Age.

“Each year, we want to create a theme for CAIS that is relevant to the external influences facing the alternative funds industry and ensure that all the associated speakers, panels, and demonstrations that we arrange, are appropriate,” says Chris Duggan, Director of CAIS and VP of Community Development at Dart Enterprises.

There are so many factors influencing the financial industry. If digital technology is not top of that list, “it’s certainly a close second,” says Duggan, in terms of the impact it is having on business processes and the way people evolve their operational models. “I think digital technology in all its forms is the single biggest element that financial firms have to seek to take advantage of. There are threats, which firms will need to mitigate, but more importantly there will be new opportunities to explore.” 

The alternative funds industry does feel like it stands on the cusp of an exciting new era; one that will see increased use of machine learning and AI technology taking over mundane tasks. In turn, this will free up managers to hone their investment strategies and build investment solutions that more closely match investors’ needs.

On 28 June, RBC Global Asset Management (RBC GAM) announced2 the establishment of the RBC GAM Innovation Lab: an in-house technology hub to incubate digital capabilities and drive innovation. 

Leveraging the network of technology and innovation capabilities across RBC, the RBC GAM Innovation Lab will focus on developing and executing next-generation initiatives to enhance the experience and outcomes of investors and advisors.

It is just one of countless technology initiatives underway across the financial industry. 

Is AI just a fad?

Concerns do exist in the industry as to whether artificial intelligence can really add value to the investment process – is it just a marketing fad and a way for managers to access capital by designing strategies that incorporate AI? 

An article in the Financial Times3 highlighted that some quantitative financiers “are sceptical that these tools are any more than a somewhat better mousetrap”. 

“Everyone wants the Holy Grail, something they can invest in and it will make 1 per cent a month forever,” Ewan Kirk, head of Cantab Capital, a Cambridge-based quantitative hedge fund, told the FT. “I don’t want to be cynical, but I am sceptical.”

Still, there are those who view it seriously. Sophisticated institutional investors understand the importance of AI and see it, in some form or another, as a key part of every manager they are dealing with at the larger end of the market. 

“I was speaking to a large manager recently and talked about three main developments that have led to this,” comments Tony Cowell, Partner at KPMG and Editorial Chair at CAIS 2018.

“Firstly, the processing power of computing has increased infinitely. Algorithms can be developed in realistic timeframes. Secondly, technology has become more easily available to organisations, and thirdly, the emergence of cloud computing. 

“When you consider the convergence of these three factors, in that context institutional investors get it. They understand it, and can see the benefits. The biggest excitement for them is lower costs in the future, and the potential for more stable good returns.”

Minority Report… could Hollywood become reality?

In the Tom Cruise film, Minority Report, the central premise is that a futuristic (2054) US police department is able to use psychic technology to arrest murderers before they commit their crimes. In a similar, albeit less dramatic fashion, the financial industry is starting to use equivalent technology.

At Nasdaq, the world’s second largest stock exchange, its Risk & Surveillance business division runs a solution called SMARTS Trade Surveillance. In brief, the solution uses machine learning technology to automate the detection, investigation and analysis of potentially abusive or disorderly trading. 

“Over the long term, we may be able to map different clusters and anomalies to particular behaviours; for example, it could point towards potential insider trading activity, or that a trader or account acts in a manner which is associated with the behaviours that have been associated with an insider, before it becomes an alert,” says Michael O’Brien, Head of Product Development, Risk & Trade Solutions at Nasdaq. 

This ability to use machine intelligence to identify potential market abuse before it happens shows how powerful technology is becoming. It opens up huge potential for data analytics.

In the last decade, we had descriptive analytics (what happened?) and diagnostic analytics (why it happened?). Now, we have moved into the realm of predictive analytics (what will happen?) and prescriptive diagnostics (what will make it happen?).

“These enhancements will provide a very powerful dimension to the traditional investment processes across all the alternative asset classes,” says Amin Rajan, CEO, Create-Research and one of the panel moderators at CAIS 2018. 

The term “Big Data’ is not new. What is new is the volume, variety and velocity of data. Behavioural biases are distinguished from structural anomalies, reason from emotion and signal from noise. As a result, says Rajan, “asset managers are constantly bombarded with new investable information and actionable insights. 

“The role of machine learning is used to constantly appraise the old relationships in the light of new information created every minute.”

Rather than suggest that the machines are going to take over, if and when they exceed human intelligence – a point referred to as the singularity – Rajan is more sanguine in his future outlook.

In his view, machines can become a very powerful decision-making tool. 

This is already happening in the oil and gas exploration industry, where they use artificial intelligence systems on a very large scale to help them interpret seismic data on underwater geological structures. 

“That sums up what it’s all about. AI and machine learning systems can help you overcome your own prejudices by giving you rational analysis,” comments Rajan, which in turn could lead to discovering new insights.

For alternative fund managers, unlocking value from unstructured data could be what distinguishes great managers from merely good ones. How far organisations go to embrace technological change is set to become the next battleground for winning investor capital. 

Cowell is more impassioned in his argument for the future, and remarks: “I genuinely believe that the industry won’t survive unless it moves towards adopting artificial intelligence across the board. We will start to see a barbell effect in what I call the technology continuum. 

“On the one side, you will have smaller boutiques that will still involve some significant human element i.e. trading single name credit and equity instruments. As you move further out, you’ll have the large players using a network of computing power, developing deep learning capabilities where machines will make the majority of trading decisions. 

“The human element in these organisations will focus more around the risk framework and less so the strategy framework.”

Cowell says he cannot envisage a world without artificial intelligence being used in fund management. 

Blockchain technology 

Everywhere one looks, blockchain technologies are sprouting up. Goldman Sachs, for example, has filed patents for various blockchain technologies including SETLcoin. Another example of this is CORDA, a bitcoin variant developed by R3, a consortium of banks that are pooling resources to research the potential of blockchain.

The immutability feature of blockchain is what makes the ability to look at information and perform reconciliations in real-time, for example, really exciting. It has the potential to revolutionise the financial industry by removing reliance on intermediaries to clear and settle accounts and introduce significant cost savings. One survey4 by Bain & Co, estimates that total savings to global financial markets could reach anywhere from USD15 billion to USD35 billion.

Earlier this year, Northern Trust announced it had partnered with IBM Corporation to build a private blockchain ecosystem exclusively for its private equity administration business, bringing what has traditionally been a manually intensive exercise firmly into the digital realm. 

If one looks at the current private equity environment and how it works between all the different participants, it is still very opaque. There are lots of legal agreements and precious little transparency on transactions. 

To construct the blockchain record keeping solution, Northern Trust selected IBM to provide the cloud infrastructure and also worked with Hyperledger to develop the code. The end result is a highly secure private cloud infrastructure within which the blockchain technology operates. 

Harnessing man & machine

There will be a wide variety of debates at CAIS 2018 to consider the impact that AI technology could have on the alternatives industry.

One topic that will likely surface throughout the event is the role of man and machine, as algorithms become increasingly sophisticated. 

AlphaGo surpassed all expectations last year, but there are two points to make: firstly, the system is unrivalled at playing Go but if it was asked to play draughts it would probably lose. Its knowledge is entirely based on one task. Secondly, no matter what the algorithm, it is only as good as the human who writes the code.

Machine learning in asset management has not advanced to the stage where one can combine man and machine easily, outside of some specific strategies.

“I see it as the near-term future, which is about five years away,” says Rajan. “If you take factor investing, machines are a great help; they can help give you some indication of which factors are overvalued, undervalued and so on.”

In that respect, the machines are a good decision-making tool for portfolio managers to road test strategies, validate them and stress test them.

In the alternatives industry, the machines haven’t yet had long enough to learn. 

The AlphaGo machine has crunched so many numbers and played so many games that it is in a situation where the machine is writing its own moves. It is learning by doing in the traditional sense. This is dynamic or `self-supervised’ learning. “In asset management the machines haven’t been doing this for long enough, being a nascent phenomenon,” adds Rajan. 

Centaur managers

One firm at the cutting edge of identifying `centaurs’ – quantitative managers that are running autonomous learning investment strategies (ALIS) – is New York-based MOV37.

“A couple of years ago when I was at a Ted Talk in Vancouver,” recalls Jeffrey Tarrant, CEO and Founder of MOV37 (a division of Protégé Partners, a FoHF manager) “I heard Jeremy Howard speak on the future of Artificial Intelligence and how computers were already on the cusp of surpassing human performance in many tasks. 

“Shortly thereafter, I met a fund that was modelled after Graham and Dodd’s value investing philosophy but was able to analyse every public filing, such as 10Qs and 10Ks since inception. This further confirmed my belief that this was the future of investing.”

In a fascinating white paper – The Intelligent Investor in an Era of Autonomous Learning5 – Tarrant details the rapid arc of AI capabilities. The idea behind ALIS is that the coming together of man, machine and data science is set to create the `third wave’ of investment management. 

The first wave was fundamental discretionary investors, says Tarrant. The second wave was systematic quantitative managers who used hypothesis-driven programming and structured financial data.  

The third wave is ALIS managers who use machine learning, which is typically data (rather than hypothesis) driven using unstructured and non-financial data (rather than structured financial data). 

Cowell says that there are now quantitative strategies moving from static to active or deep learning environments. He thinks over the next two years, the use of cognitive technology will increase and that human reasoning will be done by the machines. 

“If the human can be involved in setting the risk framework and the machine is used for setting the strategic direction as well as trading, we will see a huge move towards customisation, on a scale we’ve never before seen,” suggests Cowell. 

Through self-learning, algorithms are becoming very powerful but they cannot yet explain why they are suggesting a particular BUY for a security. 

“One of the reasons the pace of technological change in asset management has been slow is that we have yet to establish a necessary interface between humans and machines; interface in the sense that if I look at a number that comes out of the machine I am confident it is correct,” suggests Rajan.

In other words, the necessary trust between human and machine has yet to be established.

Digital technology in real asset investing

Much is written about how digital technology is revolutionising passive and active strategies, which one ordinarily characterises as long-only funds, ETFs, and hedge funds. And whilst it might not be as obvious, or indeed urgent, digital technology has huge potential to transform private equity and real estate investing. 

In the real estate space, for example, Dart Enterprises is using 3D printing and virtual software to enhance the way it approaches the design and construction of buildings. The technology in its models is referred to as Building Information Modelling or `BIM’.

“We are creating building information models which allow us to virtually construct the buildings we develop during the design process,” says Rick Aspin, Dart Real Estate. 

The aim, he says, is by having the construction drawings created from views cut through the virtual model “we have a clear blueprint in place. This helps us to figure out all of the issues that, in the past, would have needed to be resolved on-site. 

“If successful, this will allow us to streamline the whole construction process.” 

3D printing: bringing buildings to life

Dart has created a 3D printed version of Camana Bay in the Cayman Islands, which used a 3D model called the Dart Referencing System (DRS). The DRS is a geographical location system that provides a code for every item that Dart Real Estate/Dart Development builds.

The aim of this is to align its whole enterprise to be able to communicate and locate information intuitively.

The model itself opens up huge potential for sharing data via a central cloud based model that can be accessed by all from any location.

“The 3D printed version is good for those who aren’t good at reading drawings and allows for much more in-depth conversation. You can pick the building up and interact with it. You can look at the details of the building, figure out construction sequences and consider how things will come together on-site,” adds Aspin. 

Because everything based on the cloud, anyone involved in the project can access current information. This means any external consultants can see real-time information. “Moreover, it means the costings team can get information on where we are in the process and work out if everything is within budget, which avoids us getting into the mud and having to drag ourselves out,” says Aspin.

More broadly, in considering the benefits of technology to private equity and real estate investing, KPMG’s Cowell believes that the likes of blockchain and smart contracts “could be a game changer given what the speed and timing of deal transactions could become in a blockchain environment”.

Some, like Professor Rajan, think that private equity managers can live without technology for another 10 years. It is, he argues, a skills-oriented, knowledge-based activity, “which requires a huge amount of human instinct”. 

More and more PE and hedge fund houses are, nevertheless, recognising the need to harness the power of machinesºjust on their terms. 

“Don’t just rely on the intrinsic power of technology, harness it to meet your unique needs,” suggests Rajan.

Applying virtual reality to financial services

One exciting area of innovation, which has implications for how financial organisations engage with their end investors, is virtual reality. The technology is being used within academic institutions and innovation labs to understand how people learn, how they communicate, how they make decisions, and the potential for changing people’s perceptions is enormous.

Jeremy Bailenson6, who will be speaking at CAIS 2018, is founding director of Stanford University’s Virtual Human Interaction Lab and Thomas More Storke Professor in the Department of Communication. He is the author of Experience on Demand: What Virtual reality is, How it works, and What it can do, available on Amazon.

Bailenson has been exploring the applications of VR technology on the human experience since 1999 to determine how it could become a commonplace medium.

“The vision my colleagues, and science fiction writers had years ago is starting to come to fruition,” says Bailenson, echoing the early reference to Total Recall.

Bailenson spends time advising companies on VR strategies, from start-ups through to multinationals like Samsung. In addition to his academic work at Stanford, he is the co-founder of STRIVR, which uses VR to train athletes and employees.

When thinking about coaching and overcoming behavioural biases in a fund management context one cannot help think of Wendy Rhoades in Billions, the sharp minded performance coach at Axe Capital. 

Although the applications of VR to portfolio managers are possible, much of the work Bailenson has done to date has focused more on the end investor. 

Two specific case studies are worth referencing to illustrate: one with Fidelity and one with Bank of America Merrill Lynch. One relates to coaching the professional who works in the industry, the other relates to coaching the consumer.

The US faces a huge pension crisis because Millennials are not putting money in the bank. Yet, they are set to have the longest life expectancy of any generation.

“A professor at UCLA wrote his dissertation on how to use VR to motivate people to care about their future,” says Bailenson. “He had subjects come to our lab where we scanned their faces. Then they walked up to a virtual mirror and could watch their mirror image morph into a 70-year old. We then gave them a headset to viscerally see and feel like a 70-year old. When they took the VR headset off, they were given two choices: either they could have some money now, or if they put it in a savings account they could have more later on.” 

In short, the findings of the study found that after experiencing what it felt like to be 70 years old, most people opted to save money. 

“Then we got to work with a number of companies including Bank of America Merrill Lynch where, back in 2012, we helped them to develop a mobile application called Face Retirement. The camera scans your face to produce a 3D model, and overlays a 2D image of your future self, which becomes part of your online banking interface. When you’re making decisions, your future self stares back at you. The more you invest to save, the happier the face becomes,” explains Bailenson. 

The Fidelity7 project was focused more on developing empathy with the investor, and to better understand them, using a mix of artificial intelligence and VR technology.

In short, the Fidelity employee dons a VR headset, which Fidelity Labs built on the Google Daydream headset, where upon they find themselves transported from their office desk to a customer’s home. 

“Suddenly, you are with this person who is injured with a broken leg and has a stack of unopened medical bills. A conversation commences with a customer but instead of responding, we give the Fidelity employee three or four options, some of which are better suited to the situation than others,” adds Bailenson.

The aim is to understand what the customer’s needs and motivations are and, in turn, make better decisions. It’s a clear example of how cutting edge technology has the potential to train employees to overcome biases and make a difference to the end client; this is relevant to the retail funds industry but could equally apply to institutional fund management, going forward. 


This is the most exciting period of technological innovation. Most likely, the future of investment management will lead to significant reductions in head count as a result of technology driving greater automation, efficiency and client service. 

“Positions that we think of today will be very different in the future, just as they will in other industries. Deep learning scientists will become flavour of the day, and some of the more quantitative static-based traders will be replaced. We will see technology being used to collect large and random data sets that humans simply cannot process, and analysed by the machines. This could provide advantages to fund managers as they tweak and design their trading strategies,” concludes Cowell. 



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