netwealth - How to better understand clients' risk preferences | Morningstar

Every client is different but they all have one thing in common - they don't like losing. Ryan Murphy, Head of decision science at Morningstar, discusses ways advisers can help their clients focus on the benefits and not the risks involved with financial advice.

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Transcript

Matt Heine: Hi, and welcome to this episode of Between Meetings. I'm your host Matt Heine and I'm delighted to have our guest join us today. He's flown over especially to join us from Chicago. I think he's our first true international guest on the show. And it's going to be really interesting discussion I think. He's an expert on a range of topics including Game Theory and Decision Science. He's been in the faculty of Universities overseas in both Zürich and also America. And really looking forward to understanding where his interest lies, but more importantly how the research he's been doing can impact the work of advisors, and the real value that it can add to an advisor's business. Welcome to the show, Ryan Murphy.

Ryan Murphy: Great, thank you. I'm very happy to be here.

MH: Now your academic background is really interesting and it does cover a huge wide gambit of different areas. Do you want to just talk about some that you're particularly passionate about and how you got into it?

RM: So I started with a background in psychology, I was fundamentally interested in how people made decisions. And so from there I continued to study that, experimental psychology and then got more and more interested in economics. And that took me to experimental economics and from there lots of different experiments and essentially modelling how people think about risk and strategic choices.

MH: What I found recently when I was over in Berkeley, I caught up with, I think it was Shachar, who pioneered the true profile, risk profiling system. I think Berkeley may have been the first university to understand that there was a concept of behavioural economics and they merged a number of the faculties, being statistics, psychology and there's one other. Is that something that you're saying more broadly, over in America, is that something you've been involved in yourself?

RM: So, for me that's really what I'm interested in is this broad [inaudible 00:03:21] called Decision Sciences. So, if you had to explain Decision Sciences you would think of three different questions. So, the first is, how should make people make decisions if they are perfectly rational? And then how do people actually make decisions? And the third is once you've noticed that they're not always perfectly rational, is, how can you help them make better choices?

RM: So that first question draws extensively from economics and finance, and with strong roots in mathematics and statistics. The second question about how real people make choices, is a lot of psychology. And so the third is, how do you bring all of this together in a useful way? How do you engineer systems to help real people make better choices? And there are [inaudible 00:03:59] there are lots of different universities now that are bringing these different fields closer together. And it's that inner disciplinary work that I'm most interested in.

MH: And out of those three disciplines is there one that's stronger than the other? Is it sort of the foundation in psychology or does it depend on the way in which you're approaching the different research?

RM: For me, I would say no there is not one that dominates and that's the value of it. Being able to try and find a deep understanding between... a deep understanding within each of those areas and then try connect them. And so for me, I've drawn extensively on those and as I continue to study this more I start to even draw on other fields that are close by. Statistics, [inaudible 00:04:36], these sorts of areas, and using them as well.

MH: So I touched on before, you've worked in both Zürich and America [crosstalk 00:04:43]

RM: Yes.

MH: And your current role is as the Head of Data, sorry, Decision Science at Morningstar. Can you talk us through how long you've been at Morningstar, but also some of the work you've been doing there?

RM: So, I've been at Morningstar for about two years. And so we've been working on a host of different projects. So one of the projects that I've been most interested in has to do with how you understand people's goals as they make decisions and also starting to think about people's risk preferences within that context. And so trying to bring these two things together. There's a lot of work in the industry about measuring people's preferences for risk and using that as the primary guide in how they make investment choices.

And that's only one piece of the puzzle. It's more complicated and [inaudible 00:05:23] that the people's risk capacity and their risk needs, is part of that as well. And trying to square all those things simultaneously. That's been great fun to work on.

MH: Risk profiling study is something personally, I've spent a lot of time thinking about and talking about, and we might come back to that in a moment. But, you touched on goals based advice. Can you just talk about the explosion of goals based planning in the states. What's driving it and how it's different to traditional advice?

RM: I think it's far more a question of why is a person investing? Why are they delaying the consumption of their resources that they have now for later? And, it's an obvious question you ask people. Why are they doing this? It's because they have some sort of goal in mind. Something much further away, multi-years away. But we look how traditional finance is set up, it has this portfolio structure which is efficiency, which is myopic. Looking at what's the best portfolio now, somewhere on this frontier. But that's not really answering out the whole question. It depends on what a person's goals are. How much risk they should take? Where, they should be on that frontier.

And so I think it's a natural evolution for us to start to think more carefully about, of course portfolio should be efficient but at what risk exposure should they be set at, to help people actually achieve their goals that they want to achieve.

MH: And, I think it's a big divergent to obviously traditional advice, where it was almost a one to one relationship. So you went in, your risk profile was balanced right [inaudible 00:06:42] and you got a single portfolio. Whereas now you're suggesting that it's going to be a range of different outcomes, a range of different goals and therefore a range of different portfolios.

RM: Absolutely. It's a very peculiar way in which that system has emerged. So, you go back, and you look at the original marketers work [inaudible 00:06:57] and there's this parameter in there, which is this risk aversion parameter within this math [inaudible 00:07:01] framework. Which, is very strange given the psychological importance of that one parameter. And we act as if people carry this thing around in their heads, as though it's a stable reliable individual difference, right? And our lives would be much easier if that were true. If people could just walk in the office and tell you their coefficient. But that's just not how people are.

MH: So when thinking about the goals based planning, is there typically a list of sort of 10 to 12 key goals that you've identified through your research?

RM: Absolutely. And that's part of the research we've done recently, I've been talking about here in Australia. One of the things that we've found is that if you ask people off the top of their heads, what are their overarching [inaudible 00:07:40] financial goals, they may not know. It's just not where their attention is. I mean, most people's attention is on the day to day, "Where's my cellphone?". "What should I buy at the market?" These sorts of things. They are not thinking in 30 year time horizons [inaudible 00:07:52]. And so we've found that if you ask people this, straight away, off the top of their head it's an unreliable answer about a quarter of the time. And if you ask them their top three, it's unreliable about 70% of the time.

MH: And presumably changing day to day.

RM: Right. If you're trying to make a long term financial plan that's not a good foundation to build on. So the research we've been talking about uses a sort of a process; there's a starting point, an advisor has a discussion with people, but it's very much in pencil, just very high level, "What are you thinking?" And then we bring exactly what you mentioned, a checklist. A list of pure [inaudible 00:08:25], the major typical financial goals people have. And then a person looks through that, and they mark off what really resonates with them, what they really prioritise, and they scratch off what they don't really... doesn't appeal to them. And then after they've gone through that process, then they start to say, okay here's what my overarching goals are. And it's this multi-step process that helps them remember and remind them why they're an investor in the first place.

MH: And we will get back to risk profiling in a moment. But with the goals, presumably some of them are basic, but it's going to largely [inaudible 00:08:55] also depend on, their financial situation at the time. So for mass affluent America it might be home ownership, retiring with a particular sum, education for the kids.

RM: Yip, exactly.

MH: Do you need to go much deeper than those high level ones?

RM: For most people, most of the time, no. Those are the big ones. Retirement is by and large the big one, than home ownership and education.

MH: Complications arise when you've got a partner, so husband and wife, different aspirations. How are you seeing advisors tackling that scenario where you actually got two partners with very different views on what their future might look like? Or is that actually a healthy part of the conversation that builds the relationship?

RM: I think it's a healthy part of the conversation, a necessary thing to actually bring to light and to discuss over. So, there's a difference set of research we've been looking at, on the amount of happiness people report and what their spending patterns are. And it's exactly this point about well let's start to look at this from a couple's standpoint. And so we would build this map that [inaudible 00:09:55] would show how much money you're spending as a person, and here's how much happiness you report from that. Right? Which gives some insight into where people's joy comes from in the resources they spend.

MH: Retail therapy.

RM: Well, what's interesting is, you take those two figures and you can put them on top of each other and so some couples we found are very highly aligned. In the way they're spending money. There's very clear agreement as to that's where they're both deriving some happiness. But there's other couples we've found where there's a clear, stark difference between the two. And to me, that's a great starting point for discussion. Here's where you guys agree, here's where you guys don't. Let's start to talk about that and surface it.

MH: And given you have so many people who don't actually understand their goals when they first come in. It's probably the first time that a couple identifies the differences in their goals as well.

RM: Absolutely. But their aspirations are what they're trying to achieve. These are things they may not have articulated and this is a chance to start to circle in on that and get a little bit better definition around it.

MH: So, if we now move to risk profiling and I think it's a fascinating area; I think fundamentally it's broken in Australia and yet we keep coming back to the five question risk profile, which is meant to give you the answers to everything. My big issue with it and I'm sure you've done a lot of work on this, is if you ask a client that's never lost 20%. What they would do if the market fell 20%.

RM: True.

MH: They don't have the capability to actually answer that question. So I think we talk about financial literacy but a lot of people forget about financial capability and it doesn't seem any recognition of that within our current system?

RM: A couple of things I'm thinking as you're asking this question. The first is this is there's this great quote from Mike Tyson. So, "Everyone has a plan until they get punched in the mouth." Right?

MH: I love that.

RM: And so I think that's part of what financial planning is, and for people who haven't had the experience of watching their portfolio drop 20%. Asking them how they're going to behave is, it's ludicrous as a question, and people will provide the answer, but I don't think it really tells us the things we're most interested in. So I think that there's this... well out of the research out of behavioural science [inaudible 00:11:50], there's this process called dual process theory, or essentially of two minds. One mind is cooler, calm, collected, closer to rational and one mind is much hotter, much emotive [inaudible 00:12:00]. And when you give people a [inaudible 00:12:02] cue, you're asking the first mind. How you as a calm, collected individual think about risk and trade-offs. But that's not the mind that's going to be in charge when the market starts to become more volatile. It's a different mind, a very different way of perceiving and understanding the world. So I think risk, understanding people's risk preferences is very important. The way in which we go about it now, is exceptionally important.

MH: And do people have the conscious ability to manage their rational and irrational levels?

RM: Yeah, I think different people do to different degrees and part of what financial advisors can do is help bolster, the self discipline that people certainly benefit from. And also I think it's worth highlighting where the attention is. For some people there's more... there's a better alignment between those two minds and for other people they can be starkly different.

MH: And you think the rational, and the irrational is that different to you than inherent biases of individuals? Are they different studies and different outcomes or are they linked?

RM: They're definitely linked. So a part... where we see biases start to emerge, where people rely on heuristics that are simple rules of thumb. Which often work great in the real world and there's lots of places these rules work well, but there are places where they break down and sometimes they can break down in ways that are very expensive to people.

MH: Yeah, certainly I know. Personally, I suffer from Confirmation bias on a regular basis. What are the ones that people should be most aware of if they're going to focus on... Is it the aversion to loss? How does that play out?

RM: Well, Confirmation bias... I'm glad you mentioned that one. That's a great one. I think loss aversion certainly is one and overconfidence is another we use. We need to talk about. And that's related to Confirmation bias. People are looking... sort of hypothesis in the back of their heads and looking for evidence to confirm this.

MH: Which is remarkably easy to do.

RM: Oh absolutely. Right. The world provides us lots of different evidence we can pick out-

MH: Thank God for the Internet.

RM: Yeah. This is interesting as technology starts to increase the availability of information, notice how searches work. People are not searching for dis-confirming evidence. They're searching for, "Here's why I think I'm right." Invariably there'll be someone else out there who agrees with you. So, I think there's this belief somehow, that big data is going to help mitigate this. In some ways it could actually exacerbate it.

MH: Because you can actually programme against biases, if you're aware of them.

RM: Well I think that takes effort. And that's one of the things we can do in firms as we work with each other, start to help each other see our biases more clearly and start to set up protocols where we have to go through checklists and other processes to make sure that we don't fall prey to these biases.

MH: Speaking about the Internet, I think that's one of the big issues facing advice at the moment, is that the access to information is far greater than ever before. And some of the value that advisors used to possess, being the centre of information, has been diluted significantly. So we're having to constantly evolve the value proposition and what we're actually doing for the client. Which then, I think, naturally leads into goals based advice planning but then using proper risk profiling to coach or to help clients stay on track and be aware of those different biases. Is there something... I can't remember the exact term [inaudible 00:15:06] talk is it Advisor Gamma? Is that something you've been looking at?

RM: Right. So this is the idea that quantify what is good advice work to a person. Right? And so this idea of Gamma is, how can we start to measure what that is, and start to quantify what value there is comes out of good advice? And you're right, it's not a shortage of information. The Internet is changing this. Information is becoming faster... Very easy

MH: Not necessarily right, but...

RM: Well, more information right? But I think part of the value then that advisors have is that they can provide the context, and the meaning of what that information is. So they can help investors direct their attention, which is a finite resource and is not being multiplied. Right? Focus their attention where it really matters, that can help them make better decisions.

MH: And how do you create an academic study around that? Because I think you've actually managed to come up with a... call it an algorithm. But a way in actually trying to quantify exactly what that Advisor alpha or Advisor Gamma is?

RM: Well there is... Well the Gamma research comes from David Blanchett, whose one of the pillar researchers at Morningstar. He has several papers on this. So, my research along this area is looking at ways that we can shift people's attention to see if we can make them be less biassed. And so when you look at the original work in prospect theory and where loss-aversion comes from, there's this people have this kind of [inaudible 00:16:24] loss-aversion, that seems to be kind of a stable trait.

MH: Don't you just want to explain loss-aversion

RM: Loss-aversion is the hypersensitivity to losses. Nobody likes losing money but people are really, really sensitive to losing. So for example, if I were to hypothetically give you the following gamble, right? Fifty-fifty chance. I flip a perfectly [inaudible 00:16:42] coin, if it comes up heads, you win a hundred and twenty dollars, if it comes up tails, you lose a hundred. The expected value is positive. And from the narrow Neoclassic economic standpoint you'd say, "Yeah sure, I would do that." But most people don't like this. And it's because that loss just stands out much more.

MH: Yeah, fifty-fifty doesn't sound like the odds are stacked in my favour.

RM: Fifty-fifty, and the game is potentially bigger but that loss just feels bigger and that's loss-aversion. That loss feels much larger. [inaudible 00:17:13] When you do that kind of study, this comes out of experimental economics, you have to get the game value up close to around two hundred and twenty-

MH: Wow.

RM: For the majority of people, in a one shot gamble, find that appealing. And that's a huge discrepancy between what the expected value maximisation would predict and what people really like. And that highlights the sensitivity people have to losses. Losses loom larger than gains. That really stands out in their attention. And that can model, get in the way of making good decisions about finances, of course.

MH: Actually, particularly if you're then talking to a client that might be trying to take a conservative profile, but you know that they need to be closer to a balanced true growth portfolio, to actually achieve their outcome or their goals.

RM: Yes. And so then the question is, "What does that person what to do?" So there's a couple of avenues there. We could put you in a portfolio that suits your feelings, and you'll have a nice smooth ride to disappointment. Right? And that I think is really the kind of risk that we should be more focused on. What are your goals, and what's the probability of not actually reaching that goal? That's the risk I think, that you should start to emphasise more. Not risk as period to period volatility. I think that then you start to show a person one of the trade outs. "You are uncomfortable with potential losses." "You don't like [inaudible 00:18:29] dropouts." Okay. "Here's what you have to do between those two." "So if you don't want to endure these kind of [inaudible 00:18:34] dropouts, then you have to contribute this much more to your savings." "You have to give yourself this much more time."

RM: So I think that what financial planning can do is surface these sorts of trade-offs, there's no [inaudible 00:18:43] free lunch. And help people make choices that fit not only what their goals are but also what their abilities [inaudible 00:18:50].

MH: And there's some tools that you're looking at working with all releasing to help advisors with this. Because this is obviously a lot more science, a lot more academia behind this modern day risk profiling than the five questions I touched on before.

RM: Sure. So we have a couple of tools... research tools at the moment that we're in the process of [inaudible 00:19:09] outing. One of them is a sort of framework that brings all these different variables to the surface at the same time. Have the person put in what their goal is, what their timeline is, their contribution rate and then shows here's how much risk exposure you'd have to take, what kind of returns you should seek, to have a good chance of reaching your goals. And people may be comfortable with that which is a great outcome for planning, or they might find that to be unacceptable. And if so, what do they want to change to still reach their goal?

The second tool, the one I really... this one is fun, is trying to get past just asking people, "What are your preferences about risk?" But put them in the experience of gains and losses. In putting in amounts of money that they're actually going to invest. So if a person has a hundred thousand to invest, and they're in a portfolio that could lose 20% of its value, conceivably, within a year, start to show them that's a loss of $20,000. And then let them experience this. Create a period where they make choices.

MH: Right, in your earlier comment if I was looking to lose potentially lose twenty thousand does that mean the upside needs to be forty thousand, or is that going to change depending on the person?

RM: Of course, they'd want it to be, right? But there's just certain limitations of what we can expect markets to do. I think what you do then is say, "Look, if you are willing to endure this kind of volatility over a 20 year period, with these kinds of contributions, you have a very high probability of reaching your goal." That doesn't mean that year after year you can hit this return bubble. I think one of the things we can do is frame the decision in a time period that can actually help people make better choices.

MH: Yeah, and then actually mapping that out against their goal, [crosstalk 00:20:44]

RM: Right.

MH: Rather than against some Indices, which has little relationship to their outcome.

RM: Absolutely. And I think that's one thing that we were talking about where you direct peoples attention? So if you're developing a feedback mechanism to show a person's portfolio performance. Showing numbers at the top of the screen that are Indices is probably not a good idea, unless you want people to focus on that first and foremost. I think what makes a lot more sense is figure out what their goals are and tell them if they're on track or not.

MH: Is there any science behind the optimum number of times you should remind a client of that? Or that you should meet with a client, is it quarterly, six monthly, annually?

RM: I think this depends on different people. So we do know there is some evidence to show that the more often people check on their portfolios the worse they do. Right? So this idea of having monthly check-ins may actually backfire. But some people need that a little bit more. It's a-

MH: Validation.

RM: I think part of it's the validation. But I think by and large just focusing volatility or focusing on index, neither of those things really helps people focus on what they're trying to accomplish.

MH: Given you're from Chicago, have you got any general commentary on what's happening in the states, from an advice perspective? Any big trends, opportunities, challenges?

RM: So I think there's obviously price pressure, no doubt. And there's an ongoing demand to show what advice is. And so I think this is just an overarching, secular trend moving advisors away from picking stocks and assets to actually focusing on financial planning. And that is, I think where the value is now, [inaudible 00:22:47] value will continue to be. I think that's in many ways not going to be easily replaced by an algorithm. There's a relationship of trust and understanding where people are coming from. But there's a lot of things we can still hold that scale up, for example these frameworks, talking about understanding peoples goals. That could be a universal thing. Different people have different goals, but there's still a close-centric framework,[inaudible 00:23:08] that we start to use and deploy.

MH: Does that mean the skill set [inaudible 00:23:10] of advising moving forward, is going to be one based in psychology as opposed to investment?

RM: I think good financial planners would tell you, that's what they do now. And I think moving forward that will only become more important.

MH: As a formal subject do you think? As part of a Financial Planning degree or aid? Should it be mandatory, I guess is my question.

RM: I don't have strong opinion about that because I think that we're still figuring out some of the basics of the science. So I don't think we're up to a point where we could deploy a very effective curriculum around this. So... [inaudible 00:23:40] I'll have to think. That's a hard one.

MH: Yeah. Because it certainly [inaudible 00:23:50] everything that I've seen today. It's very broad, very interesting and a lot of academia behind it. So therefore to evolve it to that next stage would be interesting to know or understand. Where it's actually heading as a field.

RM: I think what's missing, I don't think we have a full intellectual framework to tie all this time together yet. So when you look at traditional finance and economics you have this modern portfolio theory. This idea of efficient portfolios. But the idea of course centric [inaudible 00:24:17] portfolios is very different. So I think it's encumbant on us to start to articulate, "Well, what is that?" "How's it different and how will that work in the end solution?" And then how would you be able to deploy that and actually get that in front of people? That's a massive undertaking. That's just something that we haven't built for yet.

MH: I think that's actually a combination of, obviously, the [inaudible 00:24:38] bravado. We say this in Australia, that this fantastic front-end tools brain developed, but you can't actually implement it in the back so you need technology and product providers to actually then also get around it and make sure that that implementation is streamlined and a great client experience.

RM: Yeah. This is a difficult problem because as soon you start to take a goal-centric view, lots of things change. It's not as though you can get over this chasm in lots of little jumps. It's going to be a big leap and that's hard to accomplish.

MH: How do you have a view on how long that might take? Is it five years, ten years, longer?

RM: I don't have a view. I'm optimistic but still working hard at it.

MH: Fantastic. I wish you all the best in your trip around Australia. Thank you for spending the time with us. I understand you're extremely busy and look forward to continuing to read your research.

RM: Excellent. Thank you very much.