In conversation with Jamie Stevenson

By Prue Roberts

Managing Director, Global Product Head - Data and Analytics at RBC Investor & Treasury Services​, Jamie Stevenson, recently visited Australia from the UK to discuss the organisation's data and analytics platform, investment performance and risk, compliance monitoring, fund sales intelligence and an emerging suite of advanced analytics for asset managers and asset owners with several local entities.

As part of his visit, Jamie participated in the FSC's Technology Workshop Series event on Open Banking and Open Data in November. And at the end of his trip, we asked Jamie to tell us a little more about what he had learned about Australia's data and analytics landscape. 

During your visit, what are some of the things you’ve noticed in terms of Australia’s attitude towards data strategies that differs from other countries around the world?

Most asset managers globally are aware that data can be transformational. My observation of Australia isn’t that different from other countries. It’s the status quo, everyone knows it’s important and they can see lots of value – and nobody disagrees that this is an important topic. But there’s a lot of people scratching their heads and wondering how they get started.

Given that Australia has such a mature market in terms of the superannuation model and the asset managers that serve them, there’s a richness to the type of use cases that are being discussed around the data conversation. There’s more breadth and ambition here in terms of where data can bring value to the end consumer and investor, as well as the manager themselves. My observation is that there’s a status quo waiting to be disrupted.

What are the three things financial institutions in Australia should be continually prioritising with their data practices?

Number one would be data governance and the careful capturing and management of the data. There’s little in the way of maturity in the market currently – but everybody is having a conversation around the value of having a good governance approach.

The second thing is the importance of new talent being introduced into the organisation to build and develop insights from that data. And it’s an acknowledgement that requires careful consideration, and by that, I mean up-and-coming data scientists and engineers are being seen as a new employee type that requires an environment and career path that may not be typical for a traditional asset manager or institutional investor.

The third thing is having an ability to aggregate all of the organisation’s data into one solution, from which insights can then be developed. Data is often being managed in a number of different places and not having one central platform to bring all of that data together is problematic. Companies need to find a way to connect all this data and make it available across the entire organisation enabling more informed and insight driven decision making across/between business units. 

Industry-wide, there appears to be a lot of people looking at each other – which is fairly normal in the sector. But my message to everyone is don’t wait three years to start a program, it’s in three years’ time that you’ll be further behind. I think organisations need to start looking to invest in data technology now.

What is trending internationally on an analytics front, and what should Australian financial institutions be paying attention to?

If you look at the UK market, there are some portfolio managers who are launching funds that use machine-learning. There is a trend in the use of data to create more AI-based products as well.

One of the common challenges for an asset manager is connecting to direct retail clients. So, we are seeing robo-adviser practices popping up internationally, particularly around Europe.

Once managers have organised their data, the challenge is then the application of that data. Is it to build an improved client experience, or new types of products that leverage powerful algorithms to provide new portfolio construction techniques?

How is the ownership of data changing the business landscape?

I’ve had some interesting conversations about who 'owns’ the data. As a business, you need to ask - am I clear on what is 'my’ data, and am I clear on the ethics of what personal data I’m looking at? Particularly the GDPR-type (General Data Protection Regulation) of regulatory change that has opened people’s minds up to the ethics of holding personal data and being responsible with that data.

You need to be clear on the ownership rights, particularly if yours is an organisation using data from many data suppliers. Having someone in your organisation to help clarify and govern and map the ownership rights to data is important.

Data governance is not new, but data governance connected to a commercial management of data is a new form of governance. It’s not just about having practices and policies but having a commercialisation element to that. Maybe for asset managers it’s been a topic they’ve been reading about, but not doing too much with, and they definitely need to start thinking about that given asset managers are information businesses.

What does the future of data look like five years from now? What possibilities are we beginning to unlock that could mean a vastly different world in the coming years?

Volumes are going to explode. Data that’s being generated by machines, data that’s being generated by processes that are benefiting from robotics – it’s huge. And the asset manager community that considers a data warehouse and other traditional forms of data management as an option will be lost. The scale of data to come will be so vast, it simply won’t be able to be processed like it is now.  

Therefore, the opportunity to gain new insights is equally rich, the ability to use unstructured data is going to provide new opportunities and the ability to innovate. So, part one will be the explosion of data, but there arguably could be an explosion of innovation from using that data to create new portfolio products.

I also hope that there is data that connects the entire customer lifecycle. For example, having a view on future outcomes – that connectivity and the openness of data and APIs to bring micro-services around individuals to build a better end outcome that’s more apparent is key.

There will be the ability to leverage data and build for the individual, as opposed to today where the consumer has to find the end product or a bunch of products that don’t necessarily speak to the end outcome.

I think we will also then see the emergence of personalised investment products, as the proximity to the products and the clients will become much closer. There will be many different products assembled uniquely to a person’s investment and spending patterns – a personalisation investment choice that instils confidence in outcomes.

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