T–3…2…1… Robo-Advisor Has a Launch!

Since 2008, we have seen a number of Robo-Advisor launches around the world – disrupting the traditional wealth management industry. More Robos are expected to launch in the UK in 2016. Some are home grown, others arriving from continental Europe and the US. Regardless of the numbers, I believe that there is still plenty of room for innovative and differentiating Robo-Platforms in the market.

In this blog, I am discussing the business and technology architecture needed to build and launch a Robo-Advisor/ Digital Wealth Management service; including a distinction between the bare minimum set of features/ functions and considerations of features for the next wave of Robo-Advisors. But first, a reminder of what makes Robo-Advisors different from most traditional wealth managers:

  • Seamless client experience from modelling and simulation to registration to the ongoing relationship management. Design thinking combined with cutting edge visualisation techniques are used to simplify client facing applications and make them intuitive – even for a 60-something who may not be a “digital native”.
  • There is a higher degree of transparency on fees and costs. You can see how much you would pay based on investments and there are no surprises, no exit fees or, transaction costs. There are 3-4 tiers based on the amount you invest and a flat fee per tier.
  • Investors are in control of your investments. Most start small. Also, at any time, investors can change risk preferences and the platform will rebalance the portfolio within a reasonable time at no additional cost to the investor.
  • Robo platforms employ passive or, at best, smart beta investment strategies and products. These are typically less risky than active management where, managers have to employ strategies to beat the market index to beat a target. Also, Robo platforms are discretionary and generally do not offer {regulated} advice.
  • As almost all Robo platforms are created by FinTech start-ups, they have no technology or infrastructure legacy. In fact, most platforms were “born” on off-premise/ cloud based environments, use devOps for continuous delivery and iterative releases. Ultimately enabling the business to be agile.
  • Robo platforms are not well known brands and therefore it takes them longer to acquire a customer and a sudden, uncontrolled market movements to loose many. Most retail investors tend to experiment with a small proportion of their savings. Also, there is no relationship manager to comfort you during rocky market conditions. You are interacting with a website or, a mobile app. Therefore, relative to a high-street retail bank or, a well-known wealth manager, Robo-Advisors take longer to earn the trust of the investor.
  • Traditional wealth managers are able to handle situations of any complexity such as family offices, trusts and handle matters such as tax, legal and investments that can span multiple generations. Currently, Robo-Advisors can handle simple investment scenarios such as Savings and Pensions.
  • It also appears that the founders of Robo-Advisors believe in bringing good social change too. They want an average person with an average job and savings to have the same level of service and quality of investment {advice} as super-rich without high fees and charges. Plus, they want to engage and educate their clients and bring behaviour change.

Before we get into the nuts and bolts of a Robo-Advisor, let’s also look at the key junctions of an investor’s journey. This will become useful later to highlight how different parts of the system come together to enable these interactions:


Here is a brief analysis of the following four key events in an investor’s journey:

Event How does the investor feel? What action would the investor take?
An individual becomes aware of the need to save. Guilty for not starting sooner, wants help to build a plan and start saving towards the plan. Actively searches for saving options, may visit their bank and choose one or more services or products to invest with.
Registration and goal setting. Energised about the goal and savings, feels good about starting to save and may visualise how they might feel upon reaching the goal. Transfers cash to the provider.
The investor may achieve their investment goal. Delighted to have achieved the financial goals. May feel motivated to do this again. May cash out and use money towards the goal – wedding, car, children’s education etc.
The investor decides to leave the service. May be frustrated that the goals have not been met in a specific timeline or, that the returns on investments have been lower than expected or, finds a better product/ provider.


Requests for the account to be closed, portfolio to be divested and cash to be transferred to his/ her bank account.

May look for an alternative products or providers.

All of the interactions happen electronically. The Business and Technical Architecture below underpins the offering:


Front Office Systems primarily include applications and systems used by prospects, clients and client-facing employees. No change there! However, over the last few years, there has been considerable focus on providing excellent client experience. As a result, Design Thinking concepts have been applied whilst designing business processes and front-end systems. Using simplistic and colourful interfaces, prospects can learn about the offering, do modelling and simulations. Investors can see their portfolio, holdings and current valuations, performance over time and the exact amount of fee they have paid. I mentioned social change earlier and these front-end systems use techniques such as goal-setting, what-if analysis, gamification and visualisation techniques to engage investors and encourage behaviour change by demonstrating the impact of their decisions. Education happens by explaining concepts, market movements, risks and opportunities in simple language through blogs, articles and videos commentaries. Collectively, all of this demonstrates openness and that the manager is working for and on behalf of the investor – keeping investors interests above their own.

Investment Strategies and Risk Systems, I believe, are at the heart of any wealth management organisation; especially critical for Robo-Advisor firms. Getting this part of the business wrong could be catastrophic for the organisation and for its clients as well. The organisation must decide and continuously evaluate the following areas:

  1. Risk management process – including operational, investment and compliance risk.
  2. How to assess risk appetite of prospects and clients?
  3. List of investment instruments, evaluation of their risk ratings and the process of asset allocation and portfolio construction.

Once these decisions are made, the next critical decision is what to automate and the level of automation. Higher degree of automation can help achieve scale and control/ contain costs. Tasks such as asset allocation and portfolio construction should be automated based on rules. These rules, however, should be created by human experts. For example, the Chief Investment Officer and his expert team to determine the rules for asset allocation and portfolio construction, when it is necessary to rebalance portfolio, frequency at which portfolios must be valued and compared to their client risk profiles and how the rebalancing should occur.

Components such as portfolio execution, custody, reporting and legal can be outsourced to some extent – even though the liability will still remain with the Robo-Advisor.

Enablers include skills, tools, technologies and systems that are required to build the operating platform for the organisation. The business and IT functions must make these key decisions together that, in traditional organisations, are usually IT centric. For example, the selection of content management platform or, the design of core APIs. The former may allow the business to curate and publish content independent of IT and the latter may play a vital role in integrating and embedding the Robo-Advisor in third party services. These factors can differentiate Robo-Advisors.

As these could be considered non-core to the business, a number of these components can be outsourced. However, for the reasons explained above, the business needs to maintain a degree of control. I’ve illustrated these in the table below with control levels as ‘obsessive’, ‘Mildly obsessive’ and ‘relaxed’. These labels apply whether these are internal to the organisation or provided by third-party/ cloud-based capabilities.

Component Level of control
API Design Obsessive
Talent Management Obsessive
Design Thinking Obsessive
Systems development and integration Mildly Obsessive
Business Process Management Mildly Obsessive
Data Quality and Governance Mildly Obsessive
Third party services Mildly Obsessive
Systems of record Relaxed
Infrastructure and platforms Relaxed
Content Management Obsessive

All components in the architecture need to be secure and must provide hooks into the Big Data and Analytics engines. Whether you are integrating with a custodian outside of your network, a CRM system on the Cloud or, an order management system within your enterprise, I believe that the same level of security should be applied. At the very least, the ‘CAIN’ principle checklist should be on systems and points of integration – Confidentiality, Authentication, Integrity and Non-Repudiation. These principles apply regardless of the actual mechanisms used on the wire.

Big Data and Analytics can support the business in making informed routine and strategic decisions. Here are some examples of Analytics use cases for Robo-Advisors:

Client Related

  • Prospects visiting your website or downloading your app. Their interaction history and activities – clicks, content consumed, duration spent on content can be combined with customer acquisition models to present bespoke offers and content. For example, first 3 months free or, invitation to come to a face-to-face event they may be interested in. A prospect’s history of interaction with the Robo-Advisor can be tied to customer when they register including any goals, savings and targets they might have entered.
  • Better understand your customer demographics and common trends within each segment of your client-base. For example, most 30-35 year olds start saving for their Children’s University Education. This be used to guide/ influence a new 32 year old investor who has just joined the platform.
  • Lifetime value of clients.
  • Predict customer life-events and suggests goals, savings and life-style choices. For example, a 20-something year old is likely to buy car, pay student loans, get married, have children etc. This timeline of events can be applied to the type of interaction, value-add and products Robo-Advisors can offer to this client.
  • Predict when a customer is likely to leave the Robo-Platform, several weeks in advance. Using proven models, it is possible to combine demographics, behaviour, transaction, personality and social data to predict if a customer is planning to leave the Robo platform.
  • Applied to the KYC process and obtain better confidence that risk questions have been understood by the customer.

Social Media Analytics

  • Robo-Advisors take full advantage of social media platforms to build brand reputation and trust. Analytics can be used to compare engagement, influence and reach. Also, how you compare to your peer group and against your internal targets.
  • With permission, Robo-Advisors can see customer/ prospect posts on social media to determine social network strength, influence factor and propensity to recommend.
  • There are some early prototypes that can use social media to determine risk-appetite and profile of a retail investor.

Product and Offering Analytics

  • Customer usability behaviour can be tracked on websites and applications to enhance customer experience. For example, creating heat-maps of how customers are using the application. This could be useful to isolate and identify points of frustration in the customer journey.
  • Product uptake sentiment – investor’s feelings about new products being offered.
  • Big Data can play a critical role in investment research, should the Robo-Advisor choose to perform any market research themselves. Non-traditional data sources such as weather, social, news and events can be combined with traditional economic and financial data to enrich research and create or invest in better/ more robust products.



The first wave of Robo-Advisors have brought disruption in the industry.  And, as it is probably now obvious to most readers, building a Robo-Advisor is complex but not a difficult task. The underpinning technologies have been generally available and used across all sectors and industries for decades. A fantastic front-end, backed with a sound and robust risk management system and processes is key to the long-term success of a Robo-Advisor.

Current functions and capabilities of Robo-Advisors is now the minimum expectation of investors. And, Robo-Advisors could do better. The next few waves of Robo-Advisors should consider and implement the following exciting set of capabilities:

  • Natural language interface that clients can use in a chat window or over voice. Imagine a digital assistant that you can talk to who understands natural language, can pick up conversations where you left them, can send you reminders and updates.
  • Customisable visualisations, complex modelling and peer-group comparisons.
  • Provide investors with more control on the type of investments they are willing to make.
  • With client’s permission, connect to other savings, investments and liabilities an investor may have. Then, use this information to identify savings potential and better management of assets and liabilities. We may see partnerships between Robo and service providers such as legal and tax providers to handle an investor’s specific needs.
  • Ability to handle advice based scenarios of low to medium complexity. As pensions are already a product most Robo-Advisors offer, perhaps start with advice on Pensions.
  • Active investment strategies.


I am looking forward to the developments in the {digital} wealth management space over the next few years. Excitement ahead…

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