No investor should ever be surprised by the ups and downs of their portfolio. After paying for financial advice, investors are entitled to “sleep tight”. They should never lie awake worrying about changes in the value of their investments.

Regrettably, sleepless nights will be the norm for many investors. Their mistake? They trusted a robo-advisor – an automated advice process that made an investment recommendation. Unfortunately, many of these automated advisors are badly built and recommend investments that are not suitable for the customer.

So, what is wrong with most robo brains? And why do they recommend unsuitable investments? A key problem is that many robos are simply replicating the poor examples set for them by the human advice process!

The investment industry happily “talks the talk” about making recommendations that are suitable for their customers when it helps win clients while avoiding regulatory intent, but it has a very poor record when it comes to “walking the walk” down the path of investment suitability – the matching of investment products to investors, using tools including risk profiling.

Today, it is the investor’s unrevealed problem. However, after the next major market correction, this will spread the pain. First, it will be the robo’s problem. Soon afterwards, it will become the problem of the sales and marketing departments of the robo, followed by the robo’s lawyer. And then the robo’s parent firm’s professional negligence insurer’s problem. And then the jury’s problem. Soon, there will be no “sleep tight” for anyone.

When investment suitability is done poorly, everyone is a loser. The client is exposed to assets and asset mixes they are not emotionally prepared to own. So they often sell and buy at the worst possible moments. The robo is exposed to all the risks of an unhappy, complaining client, including reputational damage, eventually leading to fines and class-action settlements.

Conversely, “sleep tight” is a two-way street. Investors/clients sleep tight when they have investments that suit their personality and needs. Owners and operators of robos sleep tight when they have a proper and defensible process for recommending investments to ensure they are suitable. When investment suitability is done well, everybody comes out a winner.

Investment suitability needs to be a process that accurately and scientifically takes into account an investor’s financial and psychological needs, but commonly this process is kidnapped by sales opportunism. Instead of rigour and science, there is a race to make a quick sale. “Suitability” might, at best, be cursory or superficial – at worst, it could be an outright lie.

Usually, these suitability mismatches go unnoticed, unrecognized or simply are not considered cause for concern. But then, a sharp drop in asset prices occurs, such as in 2008. In an instant, those mismatches can transform into unhappy clients seeking support, more advice and finally redress. In the current (opposing) practice and regulatory settings, they will win both retribution and compensation.

We have been warned – suitability is the major area of consumer complaints in many countries, pressuring governments and regulators to react. Courts have a history of severely punishing investment professionals who exploit their less-knowledgeable clients by foisting upon them unsuitable financial products. Regulation, however, is struggling to keep up. Prescriptive regulation – where rules must be followed and boxes must be ticked – proved to be a failure. It was simply too hard and costly to enforce, but the new standards-based regulation is just as big a failure. It says “here is a desirable outcome – now meet it however you see fit”. But without guidance or rules to be enforced, just about anything can be argued to be meeting the “standard”.

Now, robo-advice has arrived into a market where there has been little growth in funds under management for almost a decade, and packs of competitors fight like piranhas over every investable dollar.

Public trust and confidence in financial advice has never fully recovered from the horror and dismay of 2008. A significant portion of the blame is at the industry’s feet, because it has not displayed the integrity and consistency of customer experience necessary to earn – or regain – client trust.

However, there is a simple pathway to restoring that lost trust – be trustworthy! That means acting with integrity by putting the needs of the client first and delivering consistent client experiences.

The foundation of trust is to prove that investments are suitable.

First, advice givers must meet five “proofs” of suitability:

• Know and understand the investor. To truly understand their client, the advisor must consider three distinct factors which many advisors and advice processes fail to recognize individually:
  • Risk tolerance. The investor’s psychological disposition and ability to comfortably deal with rises and falls in the value of their investments.
  • Risk capacity. The investor’s ability to realize their goals in the event of a substantial fall in the value of investments.
  • Risk required. The amount of investment risk needed to achieve the returns necessary in order to satisfy the investor’s goals.
• Identify mismatches and examine alternative strategies. Financial products are not “one-size-fits-all”. The system should identify people who have a mismatch between their risk tolerances and the risks they may want, or need, to take on and consider alternative ways that might achieve their goals.
• Know the products. Can you explain what is “in” the product, how it works and how it will behave in a downturn? Are investors’ needs mapped and framed to portfolios consistent with the person’s risk tolerance, needs and goals?
• Explain the risks. This step is vital but commonly overlooked, or done poorly. It is, to be fair, a complex and difficult task. It brings together what is known about the investor’s risk tolerance and the risk of the recommended products. This allows for all risks to be fully disclosed in ways that the client will be able to understand and comprehend.
• Obtain informed consent. A client who understands the details and risks of a financial proposal and how it relates to their individual risk tolerance can give “informed consent”. Borrowed from medicine, this term means that the person has had all risks and possible outcomes explained to them and agrees to proceed.

Meeting these proofs requires a complex, multi-dimensional process that uses a wide range of factors to determine an investor’s risk profile – that is, the most appropriate level of risk for that person. Risk tolerance is balanced with the “risk required” to achieve the goals given current resources and the “risk capacity” – the ability to still achieve goals even if the investments fail to grow as expected.

Robos that are “direct-to-public” have, for the most part, failed to earn their keep.

The robos making it in the market are, with just a few exceptions, attached to larger financial organizations. Often the robo is augmented by the involvement of a human advisor in a “cyborg” process that is part person and part machine.

Robos pose particular risks to their enterprise owners, because what the robo is doing must integrate with their existing investment advice ecosystem. The first reason is reputational – a brand does not want to diminish itself through a lesser service. The second reason is logistical. Over a lifetime, a client may move through many of the brand’s different business arms and the same approach needs to be standardized and practised across all of these different potential contact points.

Financial enterprises who are parents and keepers of robos require four critical consistencies across all arms of their business:

1. Risk profiling methodology. The robo, retail bank and private client department must all measure and apply the risk profile consistently.
2. Mapping of risk tolerance to portfolios. Mapping is a nuanced process that takes into account any mismatches between risk required, risk capacity and risk tolerance.
3. Consistent language of risk. When FinaMetrica published a global book on risk terminology,¹ we found more than 25 terms that describe risk in the setting of financial planning and investments – not one has an agreed definition in the wider world! But within an enterprise, all terms about risk must mean the same thing in every advice channel.
4. Explanations of risk. As people absorb and process information in different ways, the explanations of risk must be presented in different formats such as words, visually and numerically. Like language, explanations must also be consistent across all channels.

Robos are proliferating. Most banks, major investment houses, large pension funds and life offices have at least one, while some have a range of robos – each aimed at a different target market.

Many of these robos are not getting investment suitability right. They are getting the risk profiling wrong, which makes it impossible to accurately map the investor to a portfolio and to frame the expectations around that portfolio.

Regrettably, regulators have not mandated that a psychometric risk tolerance assessment should be the first step of the investment suitability process. But regulators have fallen behind, and enterprises that want to stay ahead in a competitive marketplace are doing more than just the “minimum possible requirement” as a point of differentiation.

In our experience, a growing number of enterprises are turning to “best of breed” components, so that they can integrate their chosen tools into their own offerings to clients. We see an increasing trend towards specialist businesses using open architecture APIs, which allow outsiders to access the inner engines of other people’s software – for example, using Facebook logins for another company’s website.

These enterprises are seeking out “best of breed” providers of algorithms and intellectual property to help them stay ahead of the competition, which grows by the day. By properly risk profiling and understanding clients, they are building a protection against being stomped on by a new entrant like Facebook, Apple or Google, who have an incredibly detailed knowledge of their billions of users.