How to get Richer Client Insights for Better Advice: Revealed Preferences #1 – Transcript

Dean Holmes
Welcome to Episode One of revealed preferences, the key to deeper client understanding and better advice. Today we’re going to talk about Revealed Preference methods and how to use them to really get to know your clients and make better, more informed decisions with them. These methods are relatively new to the advice space, there are a novel tool for understanding your clients. So today, I’m joined by Simon Cammiss, of Wealth Advisors, and Dr. Shachar Kariv, professor of economics at the University of California, Berkeley, Chicago is going to get into the economics and research that sit behind these methods. And Simon, we’ll get into how to use these methods with clients. Simon, over to you to get us started with an introduction to yourself, your business and what you’re excited about today.

Simon Cammiss
Hi, guys, I’m Simon Cammiss. I run my own little firm wealthier out of Geelong and Melbourne and I have quite an anti capital preferences recently. And I’m really excited to, I suppose be an advocate and explain to you guys at a call face level how this tool is really revolutionising my client experience.

Dean Holmes
Excellent. Thank you. And, and Shachar, tell us a little bit about yourself, your journey, your accents, and then most importantly, how dolphins can make its way into this podcast. I’m really excited about that.

Shachar Kariv
All right, so I’m Shachar. And don’t try to pronounce my name covertly Even I cannot pronounce my name correctly anymore. And I am, I am an economics professor at UC Berkeley. And I’ve been at Berkeley for 20 years time flies when you’re having fun. And I’m a decision theorist and again, theorists by training. And you know, let me tell you, what economics is all about. So economics is all about improving people’s well being.

Dean Holmes
Okay, interesting. Take economics is all about improving people’s well being. That’s not how I think most people usually think about it. It’s more interest rates, investments, and so on. Can you explain that a little bit more Shachar,

Shachar Kariv
economics is not about setting the interest rates, you know, it’s bigger than this. You think, to yourself, that if the central bank is setting the interest rates correctly, then you can improve the wellbeing of many, many people. Now, you know, when I’m saying well being, this is not something precisely defined, because your well being depends on many, many things, it depends on your mental well being, it depends on your physical well being. But also, in the Oval the yields increasingly so it actually depends on your financial well being. We have a lot of research to show that financial well beings takes in larger and larger ProPILOT of overall well being. And the reason is actually simple. Take a 200 human perspective, suppose that you will be the richest person on earth 200 years ago, and you hit the problem in your tooth was the they don’t, they pulled it out, because money could not buy dental care. And today, so many problems can be solved by throwing money at them, sometimes even little money. So I actually see Simon and your fellow financial advisors who is the boots on the ground for improving people’s well being. And I say in a minute, that my financial advisor is more important for my well being than my physician, but together with this state, and actually comes a lot of responsibility, because I’m holding you guys to the same standards that are actually holding physicians and other providers of medical care. You are date important. And because you are very important, the purpose of capital, two references and you know, the purpose of my entire research in some sense, they apply the purpose of it was to provide you guys tool, diagnostic tools that you can do your very, very important job better, right so we can dive in what are the diagnostic tools and part of this explanation is going to be the famous dolphin explanation. But let me take another minute. Before I get to the to the famous dolphin story. Everyone loved dolphins, of course.

Dean Holmes
Okay, Chicago, so we’ve explored how financial advisors and physicians are similar, but there must be a limit to that metaphor, or a difference. So how are the two different How are financial advisors and physicians different?

Shachar Kariv
Alright, so there is a big difference between a financial advisor and a physician What’s the difference? The difference is medicine is that hard science in economics with all my love and respect to my profession is not a hard science. You know, we don’t have microscopes we don’t have how do we have software. So when you come to your physician, it is pretty clear what the physician needs to do in order to know the patient, you know, give me the patient age, gender, medical history, what the physician needs to do is pretty clear. And then the physician can say, I know this patient, and by the way, you go to different physicians, they will do exactly the same, right? They will take a blood test send pills, they will check your cholesterol, and so on and so forth. But everything that they do, look, the physician will ask you, how do you feel today, but this is just to be nice. You know, my grandmother, I took her to confrontation every day, every time she told him, I’m going to die. Eventually she was right. But in all the years, so it’s hard to to rely on what people are saying the physicians have literally they believe what they get from the microscope from the blood sample from the X ray, because they they’ve held windows. In economics, we don’t have hardware, we only have software. So for us, we first need to a you define what does it mean for an advisor to know the client, you know, if one thing that you learn in academia, you don’t learn many things in academia, but one thing that you learn, you really don’t click on many things. You learn some things very well. But you don’t learn many things. There is a difference here. But the things that you learn very well, is that the most difficult part of actually answering the question is making the question will be fine. Because if the question is, well, not well defined, there is no way of actually answering the question. So the question that I basically pose here is, what do we mean? What the financial advisor actually need to know? Then we would say he knows the client? And by what means can the financial advisor actually get this information? Given that, you know, we don’t have an x ray into the client financial personality? You know, this is impossible. Alright, so I’m signed on sclient. I’m coming to Simon. And I’ll tell Simon Saigon helped me. But in order to help me he needs to know know me, well, does it mean even knowing me? So now we can actually start and get to the dolphins example. Because the standout pick technique for financial advisor to know the client is what we economists call stated references, I basically asked the client questions and the client and gives me answer. This is why we call it stated preferences because the client is telling us so this is done using surveys or questionnaires. And let me say that economist in principle, we are very averse to questionnaires, you might actually be able to ask objective information, like how old you have. I’ve already in the age that I might lie, or I might actually forget. But you know, you might actually ask for objective information. But subjective information is very valid. So let me give you an example of subjective information. So I’m going to ask you the million dollar question. That will be how much do you like dolphins from one to 10? This is a very standard very easy survey question. What I hate dolphins. Hey, I love dolphins more than anything else. So I asked this question and many, many, many people, and no person ever told me shuffle I’m sorry, I cannot answer this question is not well defined. What do you mean like a dolphin? It’s not something? Can you be more specific? No one is actually answering like this. Everyone is giving me a number six, seven, sometimes eight. Sometimes even more, then I’m asking the second question on the same scale. How much do you like sharks? So you’ll see immediately that is an order effect and out of the hundreds of people that I asked I think only Phil told me that they like sharks more than dolphins. So you will get the typical answer for dolphins is eight for sharks in six, four or even less. It’s interesting what Australians feel about sharks but you know let’s let’s we can do another podcast maybe on this. But of course you’ve seen now that there are all that affects you defend the past and fails don’t dolphins and then loan sharks but no matter what the answers are, then my next question is always okay. So I understand that you like don’t face and you virtually also like shots but less than dolphins. The person says yes, that’s correct. And then I say, You know what? Let’s suppose that they add information to your tax statements or your credit cards. How much money have you ever invested in dolphins week? They’re not are a variety of charities that all the money goes to dolphins, how much money you invested in this? And the typical answer is zero. And how much money you ever invested in sharks, the typical answer is also zero. So your stated preferences is that you really like dolphins and you also like shouts, but you will reveal preferences from your actions is that you could not care less about dolphins and equally, you cannot care less about sharks. There is basically a complete disconnect between the stated preferences that we say in Celebes, to debrief the references that we see in the real world. All right. This is about dolphins and sharks. That’s easy. But when I asked you your stated preference is about your risk attitudes, which is something much more abstract than dolphins and sharks. The differences can even be bigger paydays. Oh, this is where these are where the journey begins.

Dean Holmes
Simon, have you ever surveyed anyone about dolphins in any anything like that?

Simon Cammiss
No, but I must have been I’ve invested a fair bit of in flight, which is eaten fish and chip shops near near where I live. So Well, that’ll be dark, isn’t it writing Island?

Dean Holmes
I in shock, national calm? Can you go into the survey a little bit here. Because I know it’s quite common for financial advisors to use surveys with their clients to understand their risk tolerance.

Shachar Kariv
You know, we have to understand that the main problem with surveys is that, you know, there are people that have experience with surveys, however, where surveys, there is no mathematical theory to buy to sell the. So for example, if the three of us now wants to write a survey, we can debate format, which questions to ask how many answers there should be to every question, what’s the order of these questions? Now, maybe based on experience, some of us will have how to do it right. But there is never a theory. This is the right Sylvain. When we move to the village preferences, there are yields of yields the founding fathers of micro economics that own the law, it showed there was a stand, they can tell us when we move to reveal preferences, they can tell us what data we need. And whether we have enough data to measure preferences with enough precision, or right now, you know, there are two types of data on revealed preferences. One type of data, which we always prefer, is called naturally occurring data. This is data that comes from transactions that you actually do in your everyday life, the power of Amazon, the power of Amazon is good naturally occurring data. Why? Because on Amazon, you buy consumption goods, and you do it very frequently. So look, Amazon just by looking at my past behavior, Amazon knows that it allows for maybe I have many, many small ones. Because I’m buying enough dog food. Now Amazon using machine learning already knows that people that have loud stalls, they also like the outdoors because otherwise, who takes allowed stock unit unit to take with the land on a slope outside, like maybe take a chihuahua if you don’t want to go outside. But don’t take a lounge dog. So Amazon can forget about my preferences for consumption goods just based on my best behavior because they had very frequent data. But for us, it’s exactly the opposite. We actually tell clients, you have to stick to a portfolio. So you actually do it you buy and sale financial good. Not that often. So we don’t have naturally occurring data. So when we don’t have naturally occurring data, what are we using? We are using what we call experimental data. This is not a sale vein, I’m not going to ask you a question. I’m going to give you a gamified environment. In this gamified environment, you’re going to solve trade offs. And from these trade offs. I will use economic theory to uncover your preferences that are the three performances that have been pulled in for investing.

Dean Holmes
So we’ve got some we’ve got this first elements of the context for what we’re going to go through today, which is this difference between stated preferences. I like dolphins and then revealed preference Is is in my past performance, I’ve done something or nothing towards my love of dolphins. And so in your research and what happens next we we’ve learned about or we know about these three categories of trade offs. Can you tell us a little bit about the three categories of trade offs and how that’s starting to work towards our revealed preferences?

Shachar Kariv
The first one is rich, Blitzer insists, of course, they put my money in bonds or stocks that we know. The second one is time preferences, today versus to mobile, should I buy this Tesla? Or the safe nor before my retirement? Oh, should I eat this cheesecake or eat the salad? It’s exactly the same time preferences? Do I do something that is better for me today? Or something that will be better for me in the future? Do I go to the gym after we finish the podcast? Or do I watch another reality show? That’s also time preferences. And finally, there is what we call social preferences. It’s the preferences between my own well being and the well being of other people. How much money do I want to leave to my kids? Do I want to set my kids to college? How do I allocate my money among my kids? So these are the three types of preferences, risk, nine, social end, because we don’t tell them, you don’t buy and sell your portfolios every time, we need to have an alternative data to be Vimeo preferences. And these are the games that actually capital preferences based on my research is offering for financial advisors,

Dean Holmes
and the game the games are a series of quick series of questionnaires, but not in the context of of, would you like to grow your wealth? It’s the trade off gain. Exactly. And so Simon, tell us a little bit about how you’ve done these profiling in the past. So just what was what was the history of how bad was it in terms of you doing a profile on a client? Like what’s the worst possible adventure? And then how are you positioning it today in terms of the conversations that you can have with a client as a result of using using this revealed preferences process instead of stated preferences?

Simon Cammiss
Yeah, well, I think most people listening to this podcast will be familiar with the licensee risk profile that has maybe 12 questions, maybe more. And the jargon that’s learned through these questionnaires, you couldn’t possibly send it to a client cold and expect them to have you know, a reasonable good goal and understand what’s going on. So there would often be a lot of coaching around it. And I guess, thinking back, the problem with that is you’re nudging potentially clients based on your own biases. And often the questions just weren’t really tangible. So we would end up with a number which would equate to a risk profile, clients would go to a nice little box, and we’d move on, and possibly we do that year after year, and it would feel like a chore because clients would get to this point of the room review meeting go, oh, we have to do that again. So having changed licensees recently, kind of getting a chance to reset the tools being used. Habit preferences came along. And what I loved about it was, I don’t think you could design a simpler tool for a client to use so the way I’m prefacing it is it’s a preferences exercise, I don’t really kind of use the word risk, because in my view, it’s it’s kind of more than risk, its capacity, and its other elements come into as well like timeframes. And it’s worked best for me, I think we’re, I’ve done it with the client, because they might turn to me and go, What does this mean? I’d say it’s just asking you, in a short and binary a short period of time where the you would risk X amount to potentially make why? And yeah, after we get through the first question, and the next five, that they’re speeding up, they’re, they’re really enjoying it. And like you said, I think it’s almost fun for someone and by the end, in fact, it is. So that’s kind of our founder engagement has been really good across all sort of generations that are better with

Dean Holmes
and I think it also allows for a better conversation between couples as well Simon, just in terms of the the potentially the sophistication of each other and the and the the natural bias towards I’ll have what she’s having kind of exercise is that then you’re able to get two versions of the of the actual revealed preferences which could be different to one another and most likely should be different to one another.

Simon Cammiss
So more often than not, it’s surprisingly so yeah, it’s an it’s great then just deepens the conversation, like you said, because we start to get to the root of what’s really important about money to these people as we delve into these so she’s great. Absolutely.

Dean Holmes
So she got I liked the concept that you’re talking about about the experimental data that you that Amazon obviously gets real data in terms of your preferences towards your, your dog choice. The other thing that we know, we know and get data on as financial advisors is we see the buying and selling activities on the stock market, in and around falls. So we see these flows of money coming in and out of the best performing share fund gets most of the money late after the best performance, the stock market falls, all retail investors sell out at that point in time. So not that they’ve done their own questionnaire, all of these people. But what can we learn from that that actual real evidence? Is that part of what has driven your research? Yes, absolutely.

Shachar Kariv
So you know, selling when markets go down, it’s a sign of a sign, or it’s a sign of what we call loss aversion. And, you know, I always say that the most challenging client is a client that actually has a high levels of risk tolerance, but he’s averse to losses. So this client, when he comes to you and say, Yes, give me the aggressive portfolio, I can digest it. But when markets go down, his loss aversion kicks in. And then he says, By the way, that it’s exactly like me with cheesecakes, you know, I eat the mundane i. So what our method can actually do, I can really identify the clients on a spectrum of risk tolerance and loss aversion in a way that is very efficient and very quick in them. For example, let’s suppose markets are volatile and going down, I can provide Simon with a list called these people fails, because you know, someone who is, for example, is risk averse to begin with, is not going to be in an aggressive portfolio. Yes. So we will have less of a down here is exact This is an example, that our method not only helps you to actually make two references or people to pull ducts, which I want to say and actually something else that Simon following on what Simon said, we can also help the advisor with the hand holding, because in advisor job is not just sending, sending the client to a portfolio is also holding this portfolio when you need to. So there is a lot of hand holding, you know that my physician always tells me Chaka you need to exercise. But you need to follow up with me that I exercise that I actually exercise. Yeah. All right. So I’m following up on what on the on the great point that Simon put forward our mapping form a risk level of a questionnaire to a product, there is no mathematical mapping like this, there is just there is no way you did this in a questionnaire then you need the moderate portfolio based on what when you do our experiment, we are actually estimating what is called the utility function, there is a real mathematical parameter there. And this mathematical parameter is basically saying how you weigh expected return and volatility because the efficient frontier is exactly this, right? higher expected return, but my volatility, so based on these mathematical parameters, I can map you mechanically linearly, mathematically to a point on the efficient frontier. Now, what happens if there is a couple, we are not going into marriage counseling, but you know, part of being a financial it’s, it’s actually map. So we are going to do the marriage counseling under the hood, meaning one, one person in the household and another person in the household will play the game. And underneath our game theory, we’ll actually find a compromise. And we’ll explain here is a compromise between your different let’s say risk attitude, risk tolerance, risk capacity. And why why this is actually the mapping. Let me say that we currently use it with advisors who is actually two household members. But you can actually think about the Family Fund that actually there are even more than two people that are controlling the funds. Sometimes the kids are involved. Sometimes it can be money that was inherited, and then there is multiple households still, so we can exactly find this compromise. And the compromise is going to be a mathematical compromise between the risk attitudes of everyone, you know, sometimes I must say, I compare financial advisors to pilots in the 1950s, you know, in the 1950s, on airline, and there were two pilots in Navigator and a flight engineer. Why? Because there was no equipment. So you will need to sit like this and all in fly the plane go up, go down fine. What we do, we are trying to equip the cockpit of the financial advisor, who is the most advanced tools in game theory in decision theory, it doesn’t mean at all, that the financial advisor can be replaced by the automatic pilot, it cannot. However, it can make the life of the financial advisor much easier, much simpler and more efficient such that the human being in the mind will be invested on what the human being and the mind should be invested in northern flying the plane, ladies and the Golden Gate.

Dean Holmes
So the different things that so you’ve got this data set, and obviously we’re testing this over time, but our clients are getting older as well. And they’re having different responses to the external world as well. So the amount of financial information that’s available now versus the 50s, has exposed has exploded, we’re obviously getting older, we could say generally were wealthier and better educated. And that obviously changes over time as well. Did these things have an impact on my preferences over time?

Shachar Kariv
So first, you know, decisions decisions, actually, based on three things, they based on your preferences, but they also based on your constraints, and they also based on your goals, and all of these things are changing over time. By the way, let’s start with preferences. There is a lot of evidence that when people are going older, they are actually becoming more loss averse, which I say it’s exactly right. Because think about it, if you’re make a terrible financial decisions in your 20s, it’s only a small amount of money, and you’ll have time to recover. So you know, no big deal. But if you make it better, but it’s question actual decision just after we retire, there is no way to wake up and it’s only allowed amount of money. So actually been shown to be more or less avails, because they need more money. And you know, they cannot recover, if they make a mistake, or markets go down. So definitely, prevalence is still changing, even without what information is just because of the circumstances, okay, and we definitely need to keep track or File Preferences are changing. But also other things are changing, you know, constraints are changing, because there are different finance. And you know, it used to be that we will all on defined benefit pension plans. You know, one of the advantages of defined benefit pension plans was that all the risk and all the changes were on the institution, but now it’s on me. So of course, my constraints are changing over time. And finally, also my goals, you know, now, I think that I will be skiing and snowboarding until my 80s. So I want to buy a cabin in a ski resort, but maybe I will reach my 60s and I see that I want to play bridge. So okay, anyway, we need to we bounce everything. This will never happen to me the bridge, but nevermind, it’s an excellent well done

Dean Holmes
side, never I’ve had lots of clients move into the bridge phase. And it surprised me, one of my clients learnt Spanish so that her goal was not only to play bridge, but to learn Spanish. So then she went to Spain to play bridge in Spain. So that’s obviously two levels of complexity there. In terms of bar playing, playing bridge as well. So Simon, how do you think you would use the process? As in when clients are going through different stages? And how you how would you flow that into part of your client reviews and things like that?

Simon Cammiss
Definitely. Well, I mean, because things can change a lot in 12 months, if you’re working in annual review, sort of cycle, it’s really logical to bring this up as part of the agenda. And in fact, I do yeah, it’s, it’s, it’s something early on, because if we don’t have this discussion towards the start of the review, there, the discussion around portfolios and markets may not be right, and may not kind of suit the narrative of what the client needs. So I would have thought radially a bit like going to the doctor, but also when there’s been a major change to circumstance, because that’s particularly when the goals might be shifting. So loss of job, chat, misgiving and change of circumstances, that’s when that’s when you really want to wheel it out and go deep on it.

Dean Holmes
So tell us a little bit about the the bucketing of preferences. So Simon is I’ll start with you like what have we done in the past in terms of clients, you do a risk profile, then you try to get your clients to fall into multiple different buckets because they have multiple different goals. How have you navigated that in the past? And I suppose then we’ll have a conversation around how we can use the the tool and the process going forward to make this better?

Simon Cammiss
Sure. Yeah. Well, the classic is, you know, someone saving for a house yet, they have long term investments, like super and other longer term elements, but usually just do one questionnaire, right? Because it’s pretty hard for a person to answer the same set of 12 questions with a different hat on to us. And it was lengthy. So yeah, commonly, you’d kind of invest the long term money in a more aggressive approach and the shorter term money less aggressively with a fall note or Saudi, it wasn’t great. So the great thing about this cap preferences tool is that it only takes a few minutes to do to go through the exercise. So even yesterday, I ran through it with a 24 year old girl, saving for a property, but also has long term money. So we just did it twice. So it was very easy. Because we scaled the exercise by the amount of money, we had to invest in both scenarios. I just said, Okay, let’s do the first one based on your biggest priority, which is to buy a house. So naturally, she probably wasn’t as willing to risk her capital built up for that purpose. But then when we redo the exercise five minutes later, for super long term investments, totally different story. And the analysis that comes at the end, it’s really easy to kind of go talk about capacity, goal, constraints, or preferences, and it just makes sense.

Dean Holmes
And so that’s the drop of the ocean of the revealed preferences Chicago, they that Simon’s job is to set the context, and then you can drop into the detail.

Shachar Kariv
Absolutely. So you know, it makes so Simon’s example, I actually think it’s perfectly to really make sense. For let’s suppose that I’m saving now money that I actually want to buy a house, it’s still a down payment for two years, you know, here, I have a very short horizon. And, you know, getting a getting a downpayment is also what we call a threshold goal. If I go below the threshold, I cannot afford to buy that the house that I want, because I need to put 20% down. So this requires a completely different types of investing, then I’m investing for sale deals, I’ll just put the money there. It’s not a delicious goal, right? It’s something we’ll sell to yours. And we worked very hard. And I’m very pleased that Simon actually found it to basically set because you’re getting around every experimental game that is framing, such that the adviser can actually take the same tool, the same game, but frame it to different pots of money, and get all different goals, buying a house or saving for retirement, it’s very big, big statement. It has different preferences, different goals and different constraints. Good.

Dean Holmes
So that makes a lot of that makes a lot of sense. I think that’ll make Simon’s job much easier as as well in terms of we’ve always said the bucket leads to this kind of concept of bucketing towards risk profiles and goals, but it leads a better conversation. And yes, if you can do it in a couple of minutes, Simon, instead of doing a third risk profile for the third investment portfolio, I think that that’s going to work quite well for us. So how’s the game going to change in the future that you have? So at the moment, it’s just risk risk return? But what are the elements? Can you? Can we test our clients through this process to find out other things about them? That we didn’t know? All right,

Shachar Kariv
we had, we have tons of verticals that we are doing. It’s really the risk versus return is really the tip of the iceberg. So the second one, let me go one by one. The second one is actually about what we call patient’s time preferences and present bias. And let me give you a story what is actually happening underneath and what we actually want to want to test. Let’s suppose that you take a client and you ask the client, what do you prefer $1,000 In a year, or $1,100 in a year, in one week, you’ll see the trade off 852 weeks versus 53 weeks 10% gains. I think that most clients will tell you, you know and wait the extra week and let’s go for the 11 153 weeks, not even knowing what the interest rate is right. Now. Let’s stay with this trade off to the present and ask the end. What do you prefer $1,000 Now, all $1,100 in a week, you’ll see it’s just a week difference. But I took the trade off and I bought it too. Now there are people that will flip we call it preference lever sale sells, you know, when it’s farther away, they will say we will wait an extra week for another $100. But when it’s now they will say, No, no, give me the money. And we’ll you know, they will run to the store one one or one to the power. These people we call them present by us, it’s the people that this trade off between something in something more in a week is changing when it’s really close to them. We know that these people that and of course, pleasant bias can come in with different degrees, we know that the people that have very high present bias, these are the people that you put them on a portfolio, but they will actually it has nothing to do his market goes down, he will just pass next to the car dealership, and he will buy a car that he didn’t tend to buy in the morning, and he doesn’t need to pay for the car, he will need to sell his portfolio. All right. So it’s nothing too tall. This is, for example, just an example of things that you can actually get for time preferences.

Dean Holmes
It’s very interesting. And the Australian example, which which you might appreciate is that one of our largest superannuation funds the name of the option, which is the default option, the name of the option is called balanced. And so I argue that the decision to name it balanced, even though it has 80% growth assets, it did two things, obviously, it was default. So people stuck with the default, as you said there, but it kind of made people comfortable that they were in in a in a portfolio that was appropriate. And I argue that because it was a 35 year time horizon being in a balanced portfolio. But 80% growth actually was the is the right thing for them. But we needed to use this element of of a game around the language. Absolutely. And knowing that it’s default to get people to be in the right portfolio. Absolutely. And that that one decision that has made Australians millions of dollars by being in the right risk profile at the right age. So problem is in the next phase is they don’t know when their preferences have changed that that’s no longer an appropriate portfolio for them.

Shachar Kariv
Absolutely. And given what we talked about, you basically need to have kind of a gliding pattern. So for reduced risk is is close you out to is closer when you get to retirement. Because from the reasons that we said that you don’t you know, it’s allowed you to mount and you cannot recover. And however you are gliding Penny should actually go down the risk. But you know, mine can be different than say moms and can be different from my wife. So you know, we need to find exactly the right path. And I think that this is a this is a major task for us to do in order to get people you know, the issue is the bottom line is, look, the issue is that life was simple. Because we were all on defined benefit pension plans were retired in our mid 60s and dies in our mid set in diag in our mid 70s. Problem solved.

We now that what do we tell

you even earlier, we live until our 90s we want to have fun at the beginning of retirement that the second part of retirement we need to take care of our rent. This is very expensive. So we need to take to get people to retirement that they have basically the balance they have the financial means to do what they want is a very large part of life

Dean Holmes
apps. Absolutely. Simon, you’ll obviously use this podcast with your with your clients, or maybe just this part that you’re about to do. What questions do you have in terms of being able to use this for your clients how it can work going forward, let’s have a sound bite for you to send to your clients as well.

Simon Cammiss
Well, reveal preferences is the way forward because essentially, the science behind it means that we can adjust your investments to match goals, preferences and time. I’m going to find things about you that you don’t even know yourself that your partner doesn’t know. Through this, we’re going to have much better data to help manage your money going forward as life changes.

Dean Holmes
Excellent. We like that.

Shachar Kariv
This was great. I’m going to use this soundbite with my students I’m getting like 300,003 graduates this semester. I’m going to play you and I should tell them this is why you should listen to me

Dean Holmes
so you they can you can play the whole podcast if you’d like the ensemble podcast gets we’ll get some interesting lessons from the from the US of course as a as a result. So Chicago in closing, do you want to just summarize as as a as an academic would do about the what you see in terms of what you’re proud of in terms of what you’ve helped to build in terms of your lifetime of research. And then What what excites you going forward to to actually mean that you’re not retiring next year? And that you’ll be doing this for the next 20 years as well?

Shachar Kariv
Yes. So I think that, you know, he said, he said, what we have bought now to market, it’s just the tip of the iceberg. And we are going to continue until the entire, I would say, a limited range of experimental games that we can bring to the market will change how we actually get people to repair with a and increase their financial well being. And I don’t think that no matter what with all the machine learning and artificial intelligence that we have, we will still need it. Though I’ll end with a short story that you can cut. By, you know, I taught a course with a computer scientist, a very interesting computer science about one of the leader of AI into philosophy hills, it’s a joint course, it was, it was painful a time when you bring paper in from the it’s like fuse and fold in academia. And you know, 1000 felt can be good or can be catering. So at the time, it was good the time it was terrible. But, you know, we talked about the title of the course was beneficial AI for humans. And the computer scientists and the philosophers kept talking about self driving cars. And I said, stop it. self driving cars is actually a simple problem. Maybe computationally, it’s difficult. But it’s simple. Because preferences don’t matter. You know, the self driving car, it doesn’t matter whether a shopper is in the car, or Simon is in the car. It basically needs to get us from A to B without killing ourselves from killing everyone else, then if I want to be like crazy, the self driving car suit C sharp, are we overboard, you and I kept saying I want a piece of AI that will drive me to retirement? Well, this is difficult. Why? Because it depends on your preferences. So even in the future, you think that the cockpit of the financial advisor will have all the AI and all of this which made it will steal to feed the beast to feed the machine, you need to tell whether it’s shockable Simon so you need the machine to know why Python says which the machine doesn’t need to know if I die the cow. So I really think that this is a journey for the long run. And with improvements of machine learning AI and data, this style of knowing the client’s preferences and the financial advisor, we only become more and more and more important.

Dean Holmes
Excellent. I can’t say anything else if you if we can. We’re going to finish the podcast with the financial advisor is is more and more important. We will all agree with that Shachar. On that point, thank you so much for making the time again. It was sunny, obviously in California. So we appreciate the timezone although it’s worked for us for us very well and Simon, thank you for your time as well and look forward to sharing the next podcast in this series with the listener as well. Until then, have a great day.