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Increasing investor engagement with personalised behavioural interventions

Oxford Risk’s Greg Davies writes how technology can help advisers adopt a more personal touch with investors

Greg B Davies


In communicating about investing, as with anything else, there’s a world of difference between hearing some information, and something really speaking to you.

Attempts to educate, let alone enthuse, an investor are likely to prove ineffective if they don’t first elicit some emotional engagement. Not least because emotional engagement can pull people in both good and bad directions, and the type many investors will encounter along their own, unguided, paths tends to suck them towards discomfort, anxiety, and even panic.

The typical solution to this circles around variations of ‘make the steps simpler’ or ‘use clearer language’. And there’s undoubtedly still huge room for improvement here. Yet steps can only be made so simple, only so many clicks that can be removed.

The most sensible advice, delivered in the simplest, clearest way, doesn’t influence advice – or how investors feel about receiving it – as much as hopes inspired by exploitative promises, or fears stoked by market turmoil.

If you want investors to not only hear what you’ve got to say, but to feel heard by it – and therefore be more likely to respond appropriately to it – you’ve got to get personal.

Make it personal

The investment industry hasn’t been – and isn’t – very good at this. The standard approach to encouraging greater investment has been to distribute information as if it were a software package to be installed in the broadly identical file directories of broadly identical investors. After a couple of cursory questions about goals and risk, just upload the investing information to the investor and they’ll then largely be able to look after themselves. At least until it’s time to install the add-on ‘retirement’ package.

Sometimes this works. Often, however, it does not. Certainly not reliably, and certainly not at scale.

A better approach is to download information from the investor, and use that to personalise the investing experience in a way that more robustly, reliably and repeatedly hooks them in, and makes them far more receptive to whatever it is they need to receive. Whether that’s implementing a portfolio recommendation, understanding a key investment principle, or generally feeling comfortable with the overall investing experience.

Recent reports from Accenture and Deloitte show investors think the advice they receive is too generic and they expect more tailored, relevant, timely experiences. According to EY research, over half of wealth management clients are willing to pay more for a personalised service.

It’s important to remember here that whether the advice actually is ‘generic’ isn’t as relevant as the fact it feels that way. While ‘social proof’ (doing what everyone else is doing) remains one of the strongest internal influences of behaviour, demands for (and expectations of) external badges of individuality has exploded, for everything from trainers to portfolios. People want to feel they’re special, even while comfortable trotting alongside the herd.

Further research by the Personal Investment Management and Financial Advice Association (Pimfa) shows fully tailored advice is the best way to encourage greater investing, with 51% of non-investors saying they would likely start investing if they could access it. Over a fifth (22%) say even basic tailoring would encourage them to invest.

Not knowing where to start, or what to do when you get there are common hurdles to initiating any endeavour. But overcoming them (with signposts and instruction manuals) will only take so many people so far.

As the Pimfa research also found, these individuals avoid investing because they see the investment world as intimidating (56%), lack exposure to the concept in social circles (77%) and feel emotionally apprehensive or overwhelmed about investing (54%).

These emotional factors are likely to prove far more powerful when it comes to taking action, such as getting invested for the first time, or staying invested at the first sign of trouble.

The investment advice industry is already full of numbers. What is it we should be measuring? Or, perhaps more precisely, how should we be measuring it and what should we be doing with it that we aren’t already?

The role of technology in enabling personalisation at scale

Just as bespoke cloth tailoring measures an array of angles, aspects, and accessories – all relevant, some fundamental – to craft something that fits not only with its wearer’s body, but also their personality, so investor measurements (and subsequent recommendations) should cater for their financial situation (what they own), their financial personality (who they are) and their financial behaviours (what they do, in different contexts).

Doing this effectively at scale requires understanding:

  • what we’re trying to get the investor to do (the use case, eg deploy cash, or ease anxiety);
  • what is likely to get them to do it (the intervention most relevant to their financial personality); and
  • tone and delivery (eg the medium and frequency of communication, or the technicality or assumed knowledge of the language used).

The aim of behavioural interventions is to help individuals take economically optimal actions while also finding ways to replace, rather than simply ignore, the emotional comfort being served by the uneconomic alternatives.

Many good advisers have a keen intuitive understanding of how to do this for a given investor. However, this is almost impossible to do reliably over a large client base. Moreover, not all investors have advisers, and even those that do may be far too early in their relationship to have built such an understanding.

Managing this many moving (and frequently interdependent) parts requires an innovative technological solution. Doing personalisation at scale has usually relied on changing an environment to ‘nudge’ people towards better decisions. Nudges are personal only by statistical accident. They rely on designing interventions that research has suggested will, on average, work with the greatest number of people. This greatest number could still be a minority.

Non-personalised ‘nudges’ to help improve decision-making are of limited effectiveness. They can still make a massive difference when you’re trying to persuade millions of people to file their tax returns on time, but it’s less helpful in improving the investment experience of a bank of individual investors.

Beyond a few obvious basics, like making messaging clear, and not prioritising short-term concerns in the design of a long-term portfolio, there are few, if any, ‘objective’ interventions that can be prescribed in isolation of an understanding of their recipient, and their relationship with their investments.

Moreover, what attracts one investor can repel another. Suitable measures for an anxious investor can be off-puttingly patronising for a confident one. Impulsive investors can benefit from artificially imposed friction which would only annoy their psychological opposites.

However, this doesn’t mean you (or your well-trained digital assistant) need to be prepared for each of the infinite possibilities of personality signatures, in each of the infinite sets of circumstances in which they could be expressed. Personality traits tend to cluster into a more manageable handful of common patterns. Investor personas can play a similar (albeit rather more emotionally resonant) role for personalising how investments are presented as model portfolios do for the investments themselves.

For example, rather than sending a generic message about the benefits of investing to 500 people, a behaviourally conscious engagement-enhancing technology could help you identify groups of say 50 to whom you could tailor such a message for maximum overall impact. Effectiveness can be further enhanced by additional tailoring to account for non-personality-driven elements such as preferences for communication medium, level of assumed technical understanding, and so on.

At Oxford Risk we’ve been working for many years on a suite of tools that do this, and are now deploying them with a number of key financial institutions around the world. Our technology takes a wealth of relevant investor information – psychological, circumstantial, behavioural – extracts the key patterns and prescribes effective personalised prescriptions, that become increasingly refined through tight, automatic, feedback loops.

Where do we go from here?

As these interventions reach more investors, especially in contexts such as digital platforms that can track effectiveness towards a given aim and use AI to identify and amplify things that work, and drop things that don’t, the personalised recommendations delivered by Oxford Risk technology will become increasingly refined: the ones proven to be most effective for a given situation will be propelled to the top of the lists that each investor in that sort of situation sees.

Consider a large-language-model AI that could be trained to ‘rewrite message X for type of investor Y in situation Z’, after learning how thousands of investors with thousands of different financial situations and financial personalities interact with their investments, and the messages they receive about them.

As investment information becomes ever-more accessible, curating it to the needs of each individual in a way that stands out from the noise becomes ever-more challenging. However, with the right behavioural and technological expertise, we already have the tools to meet this challenge.

Greg B Davies, PhD, is head of behavioural finance, Oxford Risk

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