Will data mining kick more goals?

As it becomes increasingly necessary for planners to provide goals-based strategic advice, Malavika Santhebennur asks if big data can help them customise advice.

Conversations around online digital advice, robo-advice, and the use of technology to bolster efficiency are growing louder in both the wealth management industry and the media. 

In the last couple of years, both wealth management arms of institutions and superannuation funds have introduced online digital advice or robo-advice tools, through which they aspire to reach the 80 per cent of Australians who do not seek professional financial advice.

In the retail space Macquarie ventured into the realm of robo-advice in 2015 with the launch of OwnersAdvisory, while National Australia Bank (NAB) also launched its digital advice offering, NAB Prosper, in 2015.

Financial services veteran, Barry Lambert signalled his support for robo-advice last year when he backed Ignition Wealth by investing $1 million into the firm.

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Superannuation funds have also jumped on the bandwagon, with REST Industry Super announcing in December last year that it had partnered with Midwinter to provide ‘mobile first’ access to personalised financial advice with the launch of the REST Advice Online Platform. In 2015, Equip Super partnered with Melbourne-based financial technology start-up firm, Clover, to provide goals-based digital advice and portfolio construction.

Decimal has partnered with various funds including Energy Super and State Wide to provide robo-advice services.

It is indisputable that the industry is attempting to embrace financial technology and online advice to engage with a wider range of clients and members across different demographics.

Conversations around the value of goals-based advice are also gaining increasing traction. As IOOF group general manager, wealth management, Renato Mota wrote in a blog April 2016, goals-based investing is not a new concept in itself but concentrating on meeting the liability of the future instead of increasing asset value could determine a client’s retirement lifestyle.

The firm’s 2014 whitepaper, ‘The expectation of advice’, revealed 76 per cent of clients surveyed valued achieving core goals and lifestyle objectives over other goals, while 14 per cent valued better than average investment performance.

Technological capabilities, particularly the ability to gather, analyse and utilise data, could play a crucial role in providing optimal goals-based advice to financial planning clients, but advice firms and institutions are not there yet.

The SMSF Academy managing director, Aaron Dunn, said there was currently capacity to utilise some of the data to gain some insights into, for example, where a client’s balance stood against the $1.6 million cap. 

Businesses could form a helicopter view around what their client base looked like based on age, financial circumstances and other filters.

“A lot more of that predictive stuff I think will evolve into the future once there’s a stronger understanding in the sector of what the needs of trustees are and some of the behaviours that start to get measured against those,” Dunn said.

“This first iteration is really once people have got data in the cloud, well then let’s start to understand what is there and the power of what you can do with it once it is readily available,” he said.

Cloud-based technology and automation would allow advisers to manage multiple client files simultaneously, in turn boosting efficiencies. Dunn said self-managed superannuation fund (SMSF) cloud-based technologies had driven efficiencies up by 40 per cent.

“If you’re in the process of building that efficiency, is that capacity going to allow us to do additional services? So you’ll move into licensed advice as an accountant that may not have done that before, are you going to be maybe focusing more on niching down on just trying to build a greater number of funds in your practice without actually increasing headcount?” Dunn asked.

WHAT’S HOLDING INDUSTRY BACK?

Rubik general manager of wealth solutions, Cameron O’Sullivan said the Big Four banks and large institutions were increasingly attempting to transfer client data on to the cloud, but noted they found it challenging.

“At the moment, most of the big banks still prefer that client data remains on site in their own data feeds, and that makes the opening up of integration to big data quite difficult,” O’Sullivan said.

Banks remained resistant to the notion of making data as open as possible to transfer information around and they were concerned private information could be captured fraudulently. Banks were also reluctant to attach personally identifiable information to data on the cloud.

“No one wants to be the banks in the papers tomorrow because the data’s been hacked, and obviously the more external places you allow the data to have control over, you might be the unlucky victim of that,” O’Sullivan said.

A 2013 paper by PricewaterhouseCoopers (PwC) about how the financial services industry could unlock the value in big data said that while financial institutions historically collected ample amounts of data, they lacked the ability to use that data to produce meaningful information in a timely fashion, which consequently provided fragmented business insights.

“Because they were unable to develop big data analytics and process the data in real time, they had difficulty predicting and responding to changing business needs and rising opportunities,” the paper said. 

“As a result, business opportunities and related growth were tied to a much slower roadmap. This value chain is at the foundation of big data.”

The paper also said advances in technology in the areas of processing power, data warehouse storage, and software were now enabling firms to organise structured data quickly while also enabling access to large amounts of unstructured data such as blogs and social media to be indexed and made searchable in short periods of time.

‘In addition, the emergence of sophisticated analytics software tools is enabling organisations to analyse vast stores of big data more easily and quickly, using fewer resources in the process,” the paper said.

Financial services software firm, knowIT Group chief executive, Wayne Wilson agreed that the financial planning industry was not utilising big data to its full potential and envisaged it would take at least another decade for the advice industry to embrace it to evolve their practices and service proposition.

He said advisers had not yet understood the potential of big data and how they could utilise it. Furthermore, principals in financial planning businesses were predominantly occupied with working in their business rather than on their business, due to which investing in technology for their business took a back seat.

“The digital provider comes along and says ‘if you use this it’s going to reduce your workload by 20, 30, or 50 per cent’ or whatever it might be ‘but before you do that you need to do the following so that we can implement it’. Well it’s doing the following which is the roadblock,” Wilson said.

“Anytime you try to put a new system in or change the way you do work, your business tends to grind to a halt, your revenue creation seems to slow down and stop and your expenses seem to go up.”

In order to convince advisers to implement new technologies, digital services providers must demonstrate the benefits to them through others who have implemented it. Only then would they be persuaded to pursue the path themselves, Wilson added.

CLIENT FOCUS TO DRIVE DATA USE

The role of financial planners have traditionally included creating a risk profile with a client, constructing asset allocations and selecting products, which they then put in a portfolio and monitor over the long-term. However, this role could increasingly diminish for planners with the advent of robo investment tools, which has the ability to manage a risk profile remotely.

In the new environment where advisers needed to provide client-centric systems, they would be required to take clients on a multimedia journey that explored their goals, built strategies to meet those goals, and created overarching strategic plans that would specifically address each of those goals in terms of their importance to clients. This would require a combination of technology and behavioural guidance.

Wilson said big data functioned at a macro level as well as at a financial planning practice level. He observed that banks and supermarkets had been collecting big data for many years to form a global view, and tracking trends to inform them on how they should evolve their services. 

“To a degree I would expect institutions and providers of services and products into this space begin to either sell or as a matter of service provide freely the trends that big data that can be collected today that are indicating how people are absorbing and valuing services and engaging digitally,” Wilson said.

Financial practices could use this big data to inform them on how to modify their businesses to engage more effectively with their target markets.

For example, if the practice wanted to target the Generation Y cohort, they would need to modify their services to suit the needs of this demographic, which may be saving for a house deposit, earning low to moderate incomes which would increase over time, and would have low risk coverage needs but high aspirations.

“Big data will basically explain to me as a practice, what’s the right way to engage that group of people? Do they want to do it digitally at a distance; is it a dance that requires a number of steps? What kind of control do they want to keep in the processes as opposed to the advice provider?”

GOALS-BASED INVESTING

Robo-advice provider, Ignition Wealth announced in February it would offer goals-based investing, and said it had appointed new research and investment house, SiResearch, to provide adaptive asset allocation built around goals with specific objectives and timeframes.

SiResearch founder, Rebecca Jacques, said robo-advice technology currently replicated the traditional financial planning model, where it would begin with a risk-profiling tool, map the risk depending on how the client answers the questionnaire, and it would then match a static portfolio to that client’s risk profile.

While goals-based investing still used risk profiling as a measure of assisting with portfolio construction from a psychometric behavioural understanding, it would add two more dimensions.

“You might have ‘x’ risk profiles, let’s just say balanced because 80 per cent of people are balanced. But what we then start doing is drilling down to say what is your goal, right? So your goal could be something as, you know, ‘I want a comfortable retirement and I’ll be retiring in 20 years’,” Jacques said. 

“And what goals-based advice does then is that it looks at your risk profile and it looks at your goal and says, essentially, can you achieve it?”

If a client cannot achieve it, the goals-based advice mechanism would seek to either alter the client’s risk profile to be slightly more aggressive in the investment strategy in order to achieve the goal or it would alter the client’s timeframe.

“So instead of say, retire in 20 years, you’re now going to retire in 25 years for instance, and/or you may have to put further contributions in,” Jacques said.

Jacques said robo-advice and other traditional financial planning tools used historical data to provide advice using a static asset allocation framework. She said SiResearch was going to add a third dimension by looking at a client’s objective and link it not just to the risk profile but also their timeframe.

They would then underpin it with forecasts rather than just historical data.

“And it’s not forecasting in the sense of let’s time markets: it’s not a TAA [tactical asset allocation] model or a timing issue,” Jacques said. 

“It’s about saying we know that we, an 80 per cent degree of certainty that there’s low interests rates, low inflationary environment that we’re currently in, is going to persist for the next likely period of five to 10 years. So we don’t see that changing anytime soon. Therefore let’s adjust those long-run averages to reflect the environment that we really are in.”

Jacques said research houses were meeting the demands of their clients because 60 to 70 per cent or so of the marketplace was still delivering standard advice based on historical data.

“There are new entrants emerging in the whole research space but the majority of them at this stage work on a consultancy arrangement and that’s purely just because to really build goals-based advice there is quite a lot of customisation required,” she said.

“That’s why everybody’s looking at the newer entrants in the technology space to say, if you’re not encumbered by all these legacy issues and we’ll tell you the framework that you really need and you go away and start building the technology to facilitate that framework.”

WHAT ARE SUPER FUNDS DOING?

The holy grail of online financial advice capabilities is integration. While online advice tools in a superannuation fund and other institutions are valuable, they create little value if super funds do not integrate the capabilities with the services that a human financial adviser can offer.

Link Advice CEO, Ross Bowden noted that many industry super funds and some retail funds tended to provide financial advice over the phone, which, while it was an older form of technology, was still convenient and effective for members to access. Super funds with online advice facilities should provide members with the option of clicking to talk to a person immediately, perhaps through online chat or through the option of calling into an advice centre.

The online advice capability would enable super funds to collect data on members, including their financial circumstances, investment decisions and capacity, age, and financial goals.  

“If members didn’t do that at that time (call into an advice centre), the phone team should absolutely be looking at this data and making outbounds. If they don’t, then, they’re making a mistake,” Bowden said.

While super funds have launched online financial advice services for their members, they had not yet integrated this with their human financial advice services, which meant they were not utilising data to its full potential to engage in in-depth predictive analytics.

“Some funds who have put in online advice capability over the last few years, it is so standalone, it is not integrated, and if a person goes on and does three or four pieces of advice and modelling, no one ever calls them,” Bowden said.

“It never goes anywhere. It just ends. The holy grail is to integrate it but that would then send a message to say that so-and-so has done xyz, you should give her a call. There’s not a lot of point in having data if you don’t use it.”

While industry funds have begun collecting member data for predictive analysis, the retail funds were ahead in the game due to the vast amounts of resources and high numbers of financial planners they have at their disposal. 

Keeping pace with reforms such as MySuper and new Australian Prudential Regulation Authority (APRA) standards have also meant super funds have not been able to devote the time and resources required to procure and analyse data, which can be an expensive exercise. However, industry funds would increasingly embrace it over time, Bowden said.

Super funds would need to initiate the conversations with members rather than waiting for them to contact the funds, and they must use different channels available to them such as e-mails and SMS. However, sending generic e-mail blasts to all members could have the unintended consequence of disengaging members.

“For example, with all the superannuation changes on 1 July this year, you can’t just e-mail someone and say ‘these are the changes’.  You actually have to go through a process and you can do this with data and storing of information,” Bowden said.

“You can say, ‘how many people set up a transition to retirement pension (TTR) in the last five years but they did that without seeking advice?. I actually need to send something that’s tailored out to those people’.”

“Being able to go in like on an Empirics system and say ‘who has entered into a TTR in the last five years and who doesn’t have an adviser?’ bang, I can get that in two minutes,” he said, adding crafting a customised message would require more effort but it was what clients were demanding.