So what’s more important? The data or the behaviours?

“We could have wonderful behavioural change, but if we haven’t changed in the right direction, then that’s not going to help,” Rew says. “We can have wonderful data, technology, analytics and visualisation. But if we’re not seeing behavioural change, then it’s not going to help. I’m a big believer in both the analytical and human sides, in combination, not in competition.”

“Behaviour versus data, humans versus machines, are part of an ongoing battle that we’re seeing across the industry. But to me this battle isn’t very relevant. Using the buzzwords and phrases - artificial intelligence, machine learning, and how robots and things are going to replace people – just isn’t a helpful or value-creating discussion. What we should be talking about is using data, technology and analytics alongside the power and expertise of people to deliver better collective outcomes. There are areas where technology is better and areas where humans are better. The mix will vary from team to team, strategy to strategy, but we should take advantage of that and build a better overall, integrated team."

“For example, computers are much better at cleansing data and doing large calculations at speed and high frequency. They can free up analysts to analyse output rather than spending hours cleaning the data. However, as we go through this evolution, we need to make sure we don’t disempower or undermine people and keep them engaged, focusing on where they can add their highest value.”

Rew has a PhD in econometrics from the University of Reading in the United Kingdom. His doctorate work involved the theory of random numbers and how they relate to one another. He then applied that to the behaviour of interest rates.

“I was applying certain theoretical tests to euro currency interest rates. I was looking at more data than researchers had previously used and found that much of what people thought didn’t exist, in fact, did exist,” he says. “It demonstrated that you’ve got to make sure you’ve got the right data and that you’re applying the right tools. Otherwise, you’ll conclude the wrong stuff and you’ll make the wrong decisions."

“I’ve always had a scientific approach to solving problems. The idea of using data, which underpins so much of financial markets, along with advances in technology, to do analytics and calculations to help investors make better decisions feels very natural and powerful to me.”

Not everyone in global funds management is a convert to the data analytics cause. And good data analysis takes skills not traditional in many organisations. Rew caused a few raised eyebrows when he hired a game designer and gamer for his team at AMP Capital.

I’ve always had a scientific approach to solving problems. The idea of using data which underpins so much of financial markets, along with advances in technology to do analytics and calculations, means I can help investors make better decisions.”

“I was looking for people who think differently. Game designers and gamers spend their lives interacting with screens. They have a great linkage of analytics to visualisation. Gamers are engaged with technology. We can learn from that."

Rew believes in hiring people unlike himself, and unlike each other.

“We needed somebody who really was passionate around visualisation. Matt (the game designer) has an understanding of how to make things more engaging. He just sees the world differently to other people, and fortunately has the skills and passion to implement his craft.”

This philosophy means he needs to create a workplace that welcomes all types.

“I don’t want anybody coming to work and not being themselves. Sadly, across the industry there’s lots of people who aren’t able to take themselves to work each day and be themselves. Fortunately for us this is an area that AMP Capital is highly focused on and supportive of."

“We look for people who may not realise they have the skills we need. The gamer was an example.”

Unlike many other workplaces, particularly in financial services, Rew does not set people up to compete against each other.

“Humans love competing with each other, but that can undermine a team because they are always trying to get one step ahead. I’ve witnessed highly capable individuals and teams be destroyed by trying to be better and beat their team colleagues, so we hire smart people, who are very good at what they do and we actively try and minimise the skills overlap across each team member to minimise that negative competitive edge."

“The other thing we focus on when hiring is the personality type. We like people who recognise that no matter how good they are, they may not have the entire answer. Maybe 70 per cent or 80 per cent is all we need. We have skills in our team which can get the rest.”

Leveraging the potential of fully integrated portfolio risk management data analytics isn’t easy for the uninitiated. Rew says it involves a number of critical steps.

Risk appetite

“Risk appetite in our lingo is called risk wallet. Exactly how much risk should be taken to generate the targeted return? How do you really define what the risks are and what risks a client should be taking, and what risks they should be avoiding?” he says.

“We link those questions and find an ‘identity’ of an investment team. If a team is collectively very thoughtful and thinks in the long term, and perhaps is collectively a little bit introverted, I would expect them to take longer term risks versus a team who’s more hyper, looking for quick rewards."

“It’s all about an investor’s identity. You need to draw that out within asset classes, and within each individual investment team."

“You need all this to help the investment teams understand how they are going to allocate risk. We try and come up with a numerical value for risk. How much of my risk wallet am I putting into a single security? Are we any good at selecting single securities? Are we any good at timing the market?"

Working with portfolio managers

Rew is clear that there needs to be a delineation between what he does and what portfolio managers do. The portfolio managers work with clients, they think about asset classes and analyse specific securities. They manage the portfolio and are responsible for the risks that they take.

On the other hand Rew is clear on his team’s responsibilities: delivering a cutting edge and aligned data, technology, analytics and visualisation strategy that enhances what the investment teams do.

“For us, the first stage is just measuring what people are doing and finding what they’re good at. From there you start working with the team to refine what they’re doing. We help find somebody’s edge and prove that up and that allows investors to increase risk, and return, over time."

“There is a difference between what people think they’re doing, what they’re actually doing, and what they’re really good at. In some cases there may not be a big void but in other cases it might be. Once you can measure decisions, people move away from guesstimates or feelings and their behaviours can change.”

Rew uses the analogy of going to a gym.

“I decide to go to the gym. I’m trying to get fitter. I think I know what to do to lose weight – what areas to focus on. If I then have a good trainer, everything is measured, I would turn up and be asked what have I done this week? The trainer would look at what I’ve eaten, how I’ve slept, what exercises I’ve done. Then he would reduce what I shouldn’t be doing and increase what I should be doing."

“But it all starts with capturing the data and knowing what you want to achieve. It’s the whole risk wallet piece,” he says.

I was looking for people who think differently. Game designers spend their lives interacting with screens. They have a great linkage of analytics to visualisation. Game designers are engaged with technology, We can learn from that.”

Capturing the right data

“The data bit is incredibly hard. If you have the wrong data and analyse it, I guarantee you will find the right wrong answer,” Rew says.

“You can’t set up the team until you know what questions you want to answer. And once you’ve got the questions and the team, you need to work out how to find the data. And to find this data the first question then becomes, does the available data actually capture and reflect the investment framework, the investment decisions, and the world view of the individual investment teams and managers? Our experience shows that most of the data our strategy and investment teams demand needs to be created by us, as it wasn’t previously available.”

“Tagging” as the name suggests is used on websites to capture data about users and how they interact with content. Similarly, in investment management ‘tagging’ securities is used to define and differentiate between each security they may be invested in. A perennial issue, in both cases, is accurately and appropriately tagging information and data. Rew says part of the problem with tagging is that there is no one way to tag, and the traditional tags, such as sectors, countries, are misleading at best.

“We all tag things based on how we see things. You’re a portfolio manager and you’re looking at a specific security or company. You will see it a certain way, because of your investment style, your investment approach, your risk wallet. You see it differently to how I would see it. So using a one size fits all, standardised tagging approach is just not the way to go. What we have to provide is a platform to see things through the portfolio manager’s lens.”

“And many of the teams tag the same things differently because of their different perspectives. So how do we work with that? How do we pull that into what we do, use those tags, and push back our information, and data and analytics to the portfolio manager in a way that’s useful?”

“The behavioural and analytical challenge we face is that ‘tagging’ has too frequently been used across the industry to simplify the way we describe individual securities, or a total portfolio or investment strategy. But this simplification risks over-simplifying a complex challenge, and focusing investors on the wrong things, especially from a portfolio construction and position sizing perspective, resulting in inferior investment outcomes.”

Visualisation

Visualisation is critical in delivering successful analytics and insights, Rew says. “It is all fine generating loads and loads of numbers, but most people aren’t able to take millions of pieces of data and picture them in their heads. By using visualisation, you can interpret the data and analytics better and get more out of them.

“Let’s say we’re doing some analysis on a portfolio and there are 100,000 data points, I could give you those hundred thousand data points in a spreadsheet, just as a list of numbers. It would be very difficult for you to see what the trends are.

“Put a chart around it and the data starts to get a perspective. Then embellish the chart and let the user change things on it. The user becomes more engaged. Then if they put their mouse over a number, something pops up. Now you’ve got an engaged user. That’s how many apps are designed, to make you engage so you start using them. Visualisation is about interpretation and human engagement, making the interaction between us and the screen more real so that we take more away from the visuals than we otherwise would.”

People

Historically the chain of data, technology and analytics specialists within organisations has not been seamless, often not working together. But it needs to if data analytics are to make a difference.

“For it to work you need to do it end-to-end from data through technology, through the analytical layer, and through visualisations. It’s information, knowledge and coaching development. Through conversations with the investment teams, we want to find something that is actually insightful and actionable,” Rew says.

“Ultimately everything we do is about behavioural change. How do you get people to do more of the stuff they are good at and achieve a better outcome for clients?

So, does data analytics in a global fund manager like AMP Capital have much more to contribute? “It’s limitless,” Rew says.

I decide to go to the gym. I’m trying to get fitter. I think I know what to do to lose weight – what areas to focus on. If I then have a good trainer, everything is measured, I would turn up and be asked what have I done this week?"

“We can continue to expand across the business, getting deeper into different layers of data technology, analytics, visualisation, as well as the discussions with the investment teams. So, you get deeper and broader and you start crossing the entire business."

“Many of the challenges fund managers deal with can use the same building blocks and approaches we’ve created for other areas of the business. For example, how can we partner with our client teams and leverage all we do to enhance client engagement and the client experience? Or, take accounting data on hundreds of spreadsheets. How can we think about that and the analytics that we can perform on all that data to enhance the way we run the business? Whatever it is, we know even small enhancements can have dramatic impacts on outcomes”.

“It’s interesting. The maths that we deal with hasn’t really changed. The data sets are starting to change, with new niche data sets becoming more mainstream. But the real game changers are the computing power we have today, the skill-sets that we are bringing in, and the way we are going about creating end-to-end solutions with our investment teams, and across the business. Breaking down the traditional solutions, linking data to technology, to analytics, leveraging the power of visualisation are all helping to enhance the decisions our investment teams make and the outcomes they are delivering to our clients.”