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Robo-Advice Explained

Robo-Advice explained:

A comprehensive look at what it is, where it’s at and why it’s here to stay.

// Robo-Advice explained

If you work in the financial planning industry, you would be hard pressed, not to have noticed the increasingly publicised coming of the robo-advisers. I must warn you though that despite the remoteness of our island continent and potential immigration issues, the robo-advisers have found us, they are here and walk among us…alright that’s not entirely accurate, although the topic of robo-advice certainly lends itself to ominous fun, but the reality is it’s here – the change is happening around us now.

Those that can adapt and harness change to their advantage are often the ones to reap the largest rewards and in many instances, influence the direction of that change. Increasingly advisers and financial planning businesses are being told to ignore robo-advice at their own peril (cit) but before we can start to consider harnessing it we need to know what it is and what it can do for clients.

Article contents

1.  What is first-wave robo-advice?
2.  The Australian experience so far
3.  Second wave  (next gen) robo-advice
4.  Who is robo-advice suited to?
5.  The benefit for consumers
6.  Challenge and risks
7.  The end of the financial adviser?
8.  Harnessing robo-advice services for financial planning businesses
9.  Concluding thoughts
10. Financial planning software: robo-advice status

What is first-wave robo-advice?

You may be disappointed to learn that first-wave robo-advice (robo-advice 1.0) doesn’t involve anything as entertaining as Robocop giving advice to your clients, in fact no current or near future robo-advice is along those lines. What we consider as robo-advice at the moment is reasonably straight forward and likely not a stretch from what you expect:

“A robo-advisor is an online wealth management service that provides automated, algorithm-based portfolio management advice without the use human financial planners.”  (cit)

The first point we should take away from this definition is the strong, almost exclusive association with wealth management and this makes sense when we consider the history of the terminology and its implementation. Industry awarded and respected Adviser, Claire Mackay traces its origins back to 2002, when used by Richard J Korento (cit) to discuss the fall out for US planning clients in the wake of Enron. It wasn’t until 2011 that the term became popularised via WealthFront who was the first successful, billion dollar, self-declared, robo-advice business – specialising in portfolio management. 

A variety of other successful robo-advice firms have emerged since, including hybrid approaches such as that taken by Vanguard (cit)) which uses robo-advice to do the portfolio-management but human advisers to confirm details and walk clients through the plan.

…strong almost exclusive association with wealth management

The second element to note are the characteristics of robo-advice; online, automated, algorithm driven and no humans. The benefits generally ascribed to it include:

  • Low cost structure (from flat fees of less than $200 to asset based total fees of 0.15%-0.5%)
  • Portfolios and asset allocations tailored to the client (based on their information and answers)
  • Tax efficient investments
  • Inbuilt and automated rebalancing (autopilot)
  • Greater transparency (perception/potential)
  • 24/7 online availability and convenience to the client

The types of clients using these services or suited for them can include:

  • Those who couldn’t afford a planner; or
  • They don’t have sufficient funds qualifying to see a planner;
  • They don’t see the value in paying for an adviser;
  • They don’t have the time for what is perceived as a long process (in contrast to this, online and available anytime)

In practical application, this stage of robo-advice means:  client completes a basic fact find and risk profile questionnaire online, the algorithm then generates a diversified portfolio aligned to the results and answers given.  They can then implement and conduct transactions, rebalancing and reporting themselves – areas that traditionally an adviser would do.

The Australian experience so far

Australia follows a lot of US based trends – albeit with some lag – contemporarily, the popularity of MDA’s and ETF’s on our shores has been accredited to their success abroad and changes in investor demands (cit).   The tone of discussion around robo-advice locally has significantly shifted to be far more favourable over the past three years (especially in the past 12 months) and in that time we have seen the arrival of local players in the market such as: InvestSMART, Stockspot and Decimal.

Providers here claim these services are a success story, but at this stage, relative to the market, there has been low uptake with clients and minimal penetration amongst advisers. The largest industry movement in this space to date has been via QInvest, announcing a provider partnership with Decimal. Far from bad news though, robo-advice, like technology is about progress. The ‘2015 Automated Investment Advisors Global Market Review’ expects client side demand to increase for these services, especially from those over 60 (cit). Adviser demand is predicted to gain momentum as businesses search for efficiencies to reduce costs and in some cases, start to re-define their value proposition. The need to reach and engage with clients who favour streamlined, online services with more visibility and control will be a key driving force.

Part of the slow up take of these wealth management robo-advisers could also be attributed to the lack of regulatory direction. The compliance regime that exists in the industry and its enforcers that haunt the hallways of licensee headquarters and adviser offices alike, are scarcely known for their kindness or alacrity to change. ASIC has acknowledged the need to address the growing technological divide (in many areas not just robo-advice) but at this stage submissions and committees are as far as progress has been made (cit). It may end up being a wait and see approach before the critical mass of licensees and advisers ever start to embrace these tools – it is also possible new entrants into the market and demand from consumers could compel faster movement in these areas.

Second-wave (next-gen) robo-advice

First-wave robo-advice, which we have characterised as being associated with just wealth management, is still a work in progress here, but that hasn’t stopped Australian fintech companies from innovating in the space to cater towards more localised consumer needs and areas of advice.

Over the next twelve months at least two Australian providers will be coming to our market with robo-advice targeting personal insurance (cit).   Superannuation, retirement optimisation and SMSFs have also been flagged as targets for new robo-advice services.   Leveraging this technology to target key areas of concern and need for the local market, not only has an enormous scope of opportunity, but may be the embracing catalyst for advisers and clients.

This evolution in robo-advice is being driven by incorporating rules engines, big-data and supercomputing such as IBM’ Watson (cit), working in conjunction to deliver an end to end scaled solution to clients. We can see at this point that limiting our discussion and definition to wealth management alone, at least locally, is no longer viable. To discuss robo-advice going forward we need a new more inclusive mindset and revision of the definition:

“Robo-Advice is an online (cloud) service that utilises an assortment of sophisticated algorithms, rules engines and big-data technology to provide clients with and end to end, situation aware, advice recommendation catering to narrow, single need (scaled) advice.”

Unlike the first era of robo-advice which may be as basic as giving self-directed clients an asset allocation derived portfolio (based on the results of a risk profile questionnaire), second-wave robo-advice is an end to end experience from provisions of personal-aware advice right through to implementation. A first-wave robo-advice insurance model would ask a client if they want insurance inside or outside of super? Any or own occupation? Child trauma? Accident benefit? Critical conditions? On and on it might go.  Even though the system may provide information on these areas it’s easy to imagine how if the client doesn’t know what these are, what the trade-offs are or if they even need them, could end up in an outcome poor situation that doesn’t actually meet their needs in the long-run.

Next gen robo-advice incorporates rule engines and supercomputing to consider the clients situation, what they are trying to achieve and conduct comparisons to generate actual advice – in much the same way as an adviser would go about the same task. The big data component provides prediction and modelling in a way that an adviser draws on their experience and knowledge in making recommendations. Clients aren’t prompted to set everything themselves, they actually get recommendations based on their situation and what they are trying to achieve. Just like with regular advice, clients can over-rule the recommendations and with the interactive nature of the systems they can see and understand the trade-offs and consequences of these changes in real time, right on screen.

We have essentially reached a point where, later this year, from the comfort of their lounges clients could start researching basic needs, i.e, insurance or superannuation, end up on your website and robo-advice portal and by the time they are done, actually have an advice document targeting those specific needs with strategies, full product recommendations (targeted comparisons) and the ability to implement them; right from within the same portal – at a click of the button.  

Who is robo-advice suited to?

In broad terms robo-advice has the potential to open up the advantages of narrow or simple advice solutions, to clients that have otherwise been outside of the process. Currently its estimated that only 2 out of every 10 Australians engage in the advice process or put another way, that’s 80% of the population who don’t seek advice. (cit)

There has been a variety of research and articles to suggest that Gen Y and Millennials prefer the self-service or online approach. The results from the 2014 investment trends report showed that 50% of those under age 29 would be open to receiving advice online and that 42% of those total Australians surveyed, considered themselves self-directed clients. The story favours online solutions even more once cost is factored into their choices, leading to more clients opting for scaled advice with non face-to-face delivery models. As mentioned earlier, older clients with low levels of retirement funds are also expected to engage with these services more frequently.

From the above we could describe the expected clients of robo-advice as those who were unlikely to seek advice in the first place because:

  • They have basic needs or low level investments they perceive as not needing comprehensive advice;
  • They are young, technology savvy individuals who prefer self-service approaches;
  • The costs are too high;
  • They don’t understand the value of financial advice;
  • They don’t have the time for the process and it’s not a priority to them.

This expectation is also in line with what the providers of robo-advice are expecting (cit). The potentially biased results from Mid Winter’s adviser survey (cit) reflects that advisers believe Bronze level clients would mostly benefit mostly from these services.

The trends discussed here aren’t anything new. Every adviser knows that a lot of the population doesn’t seek advice and this is mainly thought to be because a) they don’t understand the value of good advice or b) the cost even for an adviser to address single (scaled) advice is perceived, and generally is, too high.

Robo-advice is no substitute for complex, holistic or strategic advice but many needs can be outside of those complete areas or what the client may require at a particular point in time. This technology could yet offer the most practical approach to enabling those outside of the advice market to start improving their financial health and outcomes.

The benefits for consumers

We touched on the benefits of current robo-advice solutions earlier and even though our definition and knowledge of them has expanded, the general benefits of these services remain much the same. The exception to this is derived from the evolution of the system and the ability to provide more specific advice, that doesn’t solely rely on the client driven questions or letting them pick from a menu:

  • Specific advice: A danger for self-directed or DIY approaches is that the research and knowledge a client might have can be incomplete, inaccurate or based on false assumptions. Robo-advice not only provides the client with specific recommendations based on their current situation, goals and quantifiable needs (eg needs analysis assessment for insurance) but using rules engines and supercomputing can actively recommend or alert – interactively – a client to key considerations the same as an adviser might take into account their personal circumstances, legislation, alternatives and predicted needs based on their experiences (for the robo-adviser that’s big-data and modelling).
  • Low cost: The advice provided by this approach cannot be matched by human advisers when you factor in the administration and fixed costs, advisers time, time to prepare the advice, advisers time to present the advice and then further time implement the advice.
  • Real time, always online: The system is available 24/7, all online whenever and wherever it suits the client.
  • All in one end to end solution: From seeking information and research through to getting specific advice and implementation – all within the one platform or portal. All things being equal this can also eliminate admin errors and time lags associated with human based advice.
  • Control and transparency: Using these services the client has greater control if they want it.

Challenges and risks

Using robo-advice is no panacea for the potential risks in any financial planning or money management affairs. Yes, the human error element that can occur with admin and other basic tasks can be eliminated but the core risks still exist.

From a service or technology point of view, the two areas of great concern are:

  1. Know your client and information integrity. Information the client provides about themselves and their current situation is integral to the advice-process and forms the foundation of any advice. This is one area where human-advisers both excel and spend a lot of their time, in getting to know the client. Robo-advice solutions have the possibility of a client not understanding the questions or the rationale for information requested and if the data is not provided or the wrong information given then the outcomes can range from bad to sub-optimal. The technology must have a robust way to deal with the human element in using the service.
  2. Identifying when robo-advice is not suitable. No one expects or is claiming robo-advice is for everything and everyone. The service must, however, have adaptable check points that identify when the clients situation or the advice being requested, in contrast to the data is not suitable. To a large extent this comes down to trust as both users and the advice industry need to be able to trust or verify that this occurs. From a technology point of view it is surprisingly easy to steer users down a path, ignoring the more complex items that a solution may not be able to handle.

Based on the global experience of robo-advice to date the Financial Planning Standards Board has identified a variety of risks that robo providers, planning firms and regulators should consider: (cit)

  • Planning firms classifying robo-advice as execution only or general advice to avoid the regulations associated with standard advice.
  • Ensuring clients are aware of the extent of advice being received (as we discussed first-wave robo-advice can be quite basic not taking into account much more than risk profiles)
  • Conflicts of interest where the robo-advice solution has been set up to favour the firms products or recommendations rather than an advice neutral client first approach customers would expect.
  • Insufficient internal controls and resources to monitor the usage and quality of the service and tools
  • The validity of metrics used including; assumptions, suitability assessments and analysis tools. 

The potential for the client not to understand the advice could be a massive risk to robo-advice more than face-to-face advice. Certainly this is one area where advisers, by virtue of their value, the need and the compliance regime, excel at ensuring clients understand the advice being given. However, due to the simple nature of robo-advice, combined with the interactive and media-rich basis of these systems, we may actually find these tools provide a higher degree of understanding and financial education to clients than the traditional advice models and processes to date.

The end of the financial adviser?

Disruptive technologies and anything that has the potential to change the way we might go about work, has often been met with scepticism and exaggerated headlines of negative scenarios. With all the potential of robo-advice, both as a technology and a means to affect how consumers and clients obtain advice, it’s not surprising the many headlines and publications have tried to capture our attention with the possibility that advisers are meeting their (professional) end.

Whilst the reception towards robo-advice and technology in general has vastly improved (open discussions at the AFA, IFA and new events such as ‘Adviser Innovation 2015’), we do – even this year – still see headlines questioning the end of advisers (cit). It’s not all without base, just last year research predicted that over the next 10-20 years there is a 58% chance of robo-advice and AI replacing the current model flesh based, oxygen breathing human adviser. (cit)

The role and value of the human adviser in providing good advice, remains unchallenged but robo-advice will compete in areas with value poor advice models. Think investment advice, where the business just chases FUM and collects percentages, without adding any much value. These individual businesses may be at risk overtime from this technology however, like  a lot of developments in the industry eg, FOFA, these changes don’t happen overnight. Those paying attention, who may be entrenched in these models, should be considering how to transform their value proposition. 

As the tone towards robo-advice has improved the doomsday predictions have also receded with many now seeing this technology as enhancing the advice and engagement process – producing better outcomes for clients and advisers. (cit) Long into the future this topic may need a revisit, but for now you only need to keep in mind who robo-advice is suitable for and what needs it is actually fulfilling and it should be clear that robo-advice presents less of a threat to financial planners and more of a potential opportunity for planning businesses and clients.

If in doubt remember; peace of mind, value based advice that only humans can provide, is never going to be at risk of competition from robo-advisers. (cit)

Harnessing robo-advice services for financial planning businesses

As the Australian market starts to warm to first-wave robo-advice, hybrid or blended, advice models are being discussed more frequently as a way to fuse the best of both worlds. These models take two different approaches, one is digital tools based; where the advisers move from doing portfolio construction and investment management themselves, to letting the machines handle these tasks. The advice process itself is generally the same, leveraging the tools allows the adviser to reduce costs and focus more on the value-add they, themselves, deliver to the client.

The other is robo-advice itself, where clients use the service through your portal, they enter all their details online, answer questions and the algorithm generates a portfolio. In this model the adviser is involved to present the plan to the client, answer any questions and to be sure it fits their needs – in essence keeping the valuable relationship and guidance aspects. This approach allows clients to engage in self-serve and take advantage of the much lower cost to access advice whilst still keeping the adviser in the process for the aspects they do best.

In both approaches the core idea is the same – moving the adviser away from doing components that the machines can do as well if not better (portfolio management) and getting back to value add.(cit) As Darren Tedesco describes it:

“…investments are nothing more than a means to an end. Understanding the goal of the investments, how to get the client to stay invested, how to structure and protect assets, how to leverage Social Security strategies, how to meet legacy wishes—that’s where the human aspect of planning comes into play and where advisers outshine their computer counterparts. “ (cit)

Pure robo-advice

Even with next-gen robo-advice the blended models above are likely to be the most popular, particularly during the transition phases as robo-advice starts to be incorporated. It isn’t the only approach though, pure models exist where clients could use the robo-advice service for the entire process. In these cases planning businesses can still benefit from the technology by offering it and embracing it.

Imagine, a young professional that needs basic insurance advice today may be well suited to the low cost, convenient approach of robo-advice. Tomorrow though, as their situation and needs become more complex and their goals change, speaking with a human adviser will be of more value to them and the adviser. The first place they are going to go to find that adviser is the web site that they liked originally and that delivered them insurance advice so effortlessly – your website or portal.

Just by offering the robo-advice tool and engaging with the client in the manner that they are requesting – you have a client who you can potentially add significant value for in the future when their circumstances need it. As other financial needs arise, again, yours would likely be the first place they go for advice.

In the best case scenario robo-advice would help filter better clients to advisers; clients that want your help (as opposed to self-service) and who you can actually add significant value to.

This would be done by companion or adviser-centric robo-advice tools that are set up to identify circumstances and scenarios where a human adviser would be more suited to achieving the client’s goals and delivering the best outcomes. In this manner, the robo-advice tool helps those it can and hands over clients whose needs are more complex and would benefit more from engaging in the regular advice process.

This approach would need providers of robo-advice to work with advisers, enabling them to set or identify these points of divergence and build them in automatically. It would also be important to clearly articulate why the client is being handed over or should seek the advice from a financial planner. If the client starts the process, they enter their details, goals, needs and get then are advised to seek a planner you would likely lose the client due to shattered expectations. Setting this expectation and communicating that via the robo-advice tool will be a key to success with this approach.

Overview of benefits

•Hybrid or blended advice models will allow planners to spend more time with clients or on delivering valued based advice and services.
•Both digital tools and hybrid advice models can reduce administration errors, time lags and further automate processing – a key competitive advantage for business.
•Just offering the robo-advice tools gives you the opportunity to capture clients of the future and additional leads.
•Robo-advice that works with advisers can improve the quality of clients for the adviser by helping simple need clients automatically and directing complex or high value clients to the adviser.

Concluding thoughts

Robo-Advice is no small topic and just as the industry feels it is coming to terms with it, the technology is about to evolve further. It is clear that robo-advice has risks and regulatory aspects that will need to be addressed but with its multi-facetted potential to clients, consumers and planners it’s hard to imagine a future where its deep integration in the industry doesn’t occur. Going forward Australia may even find itself leading the way in new evolutions and applications of robo-advice.

For all the technological aspects of this disruption, there is a sense of ‘everything old is new again’ as we see common topics emerging in the discourse such as the value of advice, how to best engage with clients and why clients seek advice. As with other challenges, the answer seems to be that businesses and advisers who understand their clients and the value proposition, have little to fear.  Planners and firms who are ahead of the curve on this already have a competitive advantage and when leveraged in conjunction with technological advances, the improvements may produce the best advice experiences yet for clients and advisers.

Good advice from good human advisers, has a brighter future than ever in the Australian landscape and as we said at the start those who can adapt and harness this change, will reap the most rewards and set the tone of how others may end up using robo-advice going forward.

Financial planning software: robo-advice status

Below are the most standard financial planning tools in Australia and the currently known state of their robo-advice services:

IRESS

Xplan by IRESS

Currently xplan has no first or second wave robo-advice facilities and IRESS has made no announcements about offering such features.

The approach they have taken to address the digital client and leverage online capabilities with Xplan so far has been one of self-service research.  The idea is popular amongst the banks and investment platforms, with the view being, by giving the client access to tools which they can use to see why they should seek advice, they will rationally want seek help from a planner.

Tools to educate clients certainly have value, especially online where the interactive nature of them can enhance the client experience.  Self-service research will still be a part of an advisers toolkit in the future but it doesn’t offer any of the advantages of robo-advice and only addresses a fraction of the reason why so many consumers are outside of the advice process.

The hope on the horizon may be IRESS’ new PRIME solution.  While robo-advice hasn’t been announced as part of this, it is hard to imagine a technology forward company like CBA partnering with a solution that wasn’t going to deliver these services.

MidWinter Logo

AdviceOS by Midwinter

Midwinter appears as if it will be taking the lead on this new technology among the planning software providers.  They have skipped over the first-wave and are instead going for second-wave robo-advice – targeting personal insurance and then a variety of scaled advice areas thereafter.  The personal insurance robo-advice is expected to launch in the coming months.

Based on the details they have announced so far the offering will be close to pure robo-advice (with the exception of the user having to either be a client or prospect) allowing the client to receive recommendations and implement them all through the advisers portal which is connected with the adviceOS platform.  They are also the first to offer adviser centric robo-advice having discussed features such as alerts and triggers which sound like they will filter the client to the human adviser under set conditions – as discussed this is likely one of the core benefits robo-advice can deliver to mature advice practices.

It should be noted that Midwinter reject this as a form of ‘robo-advice’ taking issue with the negative aspects and multitude of meanings the term can entail.  See here for further details

COIN

COIN Software by Rubik

COIN has not announced and currently does not offer any robo-advice services.  At some point along the way Rubik may have acquired robo-advice technology from their many acquisitions in past years, however if it ever gets plugged in or incorporated with their platform is anyone’s guess. 

As of early 2015 the company said its focus would be on scaled advice as the next area of concern for planners. (cit)

AdviserLogic

AdviserLogic

A relatively small player in the financial planning software market but one which has re-energised itself in recent times and is cultivating a following. 

Earlier this year they announced a part robo-advice update to the system which enables basic superannuation rollovers to be automated.  Advisers must still select the recommended platform but the comparisons and model portfolios will be automatically generated based on the clients risk profile.

Even though not a full robo-advice system it is encouraging to see these solutions starting to be offered by smaller providers as well. (cit)

Matthew Townsend
Xplan Consultant and Developer | Wealth Management Technologist at Create Something

Matthew is an experienced and innovative Xplan consultant and developer, having worked on and developed some of the largest advice projects in the industry. Passionate about building great experiences in xplan that enable businesses and clients to get the most out of this powerful software.


Matthew Townsend

Matthew is an experienced and innovative Xplan consultant and developer, having worked on and developed some of the largest advice projects in the industry. Passionate about building great experiences in xplan that enable businesses and clients to get the most out of this powerful software.

This Post Has 14 Comments
  1. I want to to thank you for this excellent read!! I certainly enjoyed every little bit of it. I’ve got you saved as a favorite to look at new things you post…|

  2. Excellent post. I was checking constantly this blog and I’m impressed!
    Extremely helpful info specially the last part 🙂
    Thank you
    and best of luck.

  3. I am so happy to read this. This is the type of detailed information that needs to be given and not the random info that you find elsewhere. Appreciate your sharing this

  4. Thanks for the write up Matthew, a lot of the robo articles these days are just parroting information. Nice to see substance.

    Regards,
    Michael

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