410. Nudgeable Moments: Tackling Insurance Fraud with Dr. Benny Cheung (Refreshed Episode)

Welcome to episode 410 of the Brainy Business Understanding the Psychology of why People Buy. Today's episode is a conversation with Dr. Benny Chung of DEC Tech. Ready? Let's get started.

You are listening to the Brainy Business podcast where we dig into the psychology of why people buy and help you incorporate behavioral economics into your business, making it more brain friendly. Now, here's your host, Melin Palmer.

Hello.

Hello everyone.

My name is Melina Palmer and I want to welcome you to the Brainy Business Podcast. Today's episode is a refresh of my conversation with Dr. Benny Chung of Deck Tech, which originally aired back in February of 2021. This episode has one of my very favorite examples of an applied research study which has to do with opportunistic insurance fraud. It has such great lessons within it. I've included it in my book what your Wants and Can't Tell you and share about it in my talks and trainings all the time because it has such great lessons for all kinds of businesses. I'm not going to spoil it for you by sharing the details now, but just be ready to take notes and be thinking about how these learnings could apply in your business, whatever industry you're in. I also love the discussion around Benny's dissertation because it definitely goes to show the diversity of backgrounds in behavioral science and. And you'll see what I mean in a minute. Don't forget there are links for everything including my top related past episodes and books waiting for you in the show. Notes for this episode which are found within the app you're listening to and at the brainy business.com 4:10 all right, let's jump right in. Dr. Benny Chung, welcome to the Brainy Business podcast.

Thank you Melina. Very happy to hear and very happy to meet you.

Absolutely. Well, I'm so excited to talk about this project that you had worked on. Had some amazing results. But if you can first tell us a little bit about your background, you know, who you are, how you got into behavioral science and just. Yeah, let us know what your interests are.

Sure. I'm, I'm actually from a life science background perhaps you know, atypical, you know amongst the previous guests on your podcast. I did my PhD at Cambridge University and a postdoctoral research fellowship there in behavioral genetics. So I actually using a worm animal model, nematode worm model to study feeding behaviors which has implications on issues in humans such as eating disorder. Now very interesting stuff, but that's maybe for another day and time. I joined DAG Tech back in 2005 after my academic career in behavioral genetics with the view of applying some of these techniques technology in behavioral science in a commercial backdrop supporting clients to understand their consumers better. Now nowadays our mission at dectech is to provide the tools that will allow our clients to make more accurate and cost effective predictions about their consumers behavior in whatever circumstances, context in future.

Yeah, well, I would be interested. I like to hear when people have a different background. I think it's always so interesting to see. I've had an ethnographer on the show and I think anthropology is so interesting and even and very much looking at the behavior of animals and how it ties into human behavior. Do you have any sort of insights that you can share about kind of the behavioral genetics and how it all ties in? Some of the like what you find.

To be really fascinating.

Yeah, somewhat off piece but it's interesting. Yeah. So I think a lot of behaviors, actually a good proportion of the behaviors are hereditary. So it's coming from this nature nurture trade off. I think a lot of the behavior, certainly physiologically we can trace back to the genetics. So you inherit a lot of behavioral traits from your genomes. And you know, the worm, the animal model that I studied is nematode. Worms, you know, share very similar genomes with us. So we are, you know, at that level, very similar. And that's why, you know, using those animal models is actually very good tools to study, you know, some of the behavior certainly in a clinical sense. But obviously nowadays my focus is more in a sort of commercial backdrop. So we are interested in consumer purchasing, commercial decision making. So very different outcome behaviors that we're looking at. But yes, but on the topic of genes versus nurture is very interesting and it's very fast moving too. But as I said, maybe for another day.

Well, I'm one that we've got plenty of time. I like to learn a little bit about the scope. So if you're okay talking about it a little bit. I think because we haven't had anybody really talk about that before, but I do get questions all the time about how. And I know it's not necessarily personality, you know, and how personality ties in with the behavioral economics, behavioral sciences. But having more depth from an expert such as yourself as far as how the nature piece ties in, I personally find to be very interesting and would love to hear a little bit. If you're willing to just share on that, humor me for a few minutes and then we can jump in on this study.

Yeah, of course I, we. I mean the behavior that I was studying I mean, this is back in the year I started my ph in 1999. So there was, there was a while ago. So the behavior we interested in was feeding behavior. And so just a little bit about, you know, how genetics is so intricately related to the, to the behavioral outcome and feeding behavior. The behavior that I was studying at the time is, is one of those example. By changing one single gene, you can change how the worm. So this model organism that was studying how they behave when they forage, okay, so in the wild, worms forage in, exhibit two different foraging behaviors. So some worms like to forage on their own. So they are loners, they like to eat on their own. They don't want to be bothered by their friend worms. Another type of worms, same species, but with a slightly different gene makeup. They like to aggregate when they feed. Now, the only difference in the genomic makeup between those two worms is down to one single gene, which is really striking when you think about it, because behavior has always been thought of as this very complex outcome a living organism could exhibit. But in this case at least it's all down to a single gene, the makeup of the gene. And you would determine one way or the other how the organism behave. Now, I'm not saying all behaviors are that simple. Sure, there's a very good example, a very striking example to just show you that, you know, genetics has a very important role to play in terms of the behavior. But obviously lots of study has also shown that, you know, nature, nurture. Sorry, plays an important role too. And so, you know, the environment you're bringing up would have also an important modifying role to play to your behavior. Context. Context is king.

Absolutely, definitely. And it's almost, it feels like we've got our, the difference between our introvert worms and our extrovert feeding worms, I guess, is just that single gene kind of a funny little tidbit. Okay, well, thank you for talking about worms with me. I appreciate it. And I, I mean, I don't know how much you get to talk about worms these days.

Not anymore. That was my former life. Yes.

Yeah. Well, I know that all the listeners of the show are just constant learners like myself, and so finding those little tidbits I find to be interesting and I assume everyone does too. So let's go ahead and we'll jump in and we'll talk about from worms to fraud and you know, lessening the kind of simple white lie type of fraud behavior. Can you talk a little bit about the project that you worked on? The problem that was presented? I Love the step by step of how this kind of came about. So if you can just talk about the project, I think that'd be great.

So the topic is, as you said, insurance fraud. And to be specific, we are talking about opportunistic insurance fraud. So these are not your hardened fraudster that are involved in crash or cash, for example. I'm talking about everyday consumer that are giving into temptations of being less than honest at a specific point during their customer's life cycle. So to give an example, you can be involved in opportunistic fraud during the applications process when you often ask, you know, questions about your past record that might have some implications on your premium. So for example, you know, when you apply for motor insurance, often you get asked questions about your previous motor convictions or whether you know your claim histories, for example. Now those questions I think consumers know that you will, depending on how they answer those questions, you will affect their premium. And some people might give in the temptation at the time when they are going through those process to be less than honest in the hope of saving a few bucks. And conversely, in the claim process, people might hold a vehicle. There's a myth about just a chance to recuperate some of the money that you've been paying for insurers and therefore it's okay to exaggerate your claims either in terms of value or actually inventing items that was not lost in the first place. I'm talking about home insurance setting here. So those are kind of examples of the kind of fraud we were tasked to address in this project. The project is for the Insurance Fraud Bureau here in the uk, their industry body that are in charge of helping insurers to fight fraud crimes, as I said, opportunistic fraud is kind of this strange different territory from a lot of them, more high profile organized fraud that the ifb, the Insurance Fraud Bureau deal with. It is very different in the sense that most of it is undetected. So how do you solve a problem that you can't even detect? So that throw up a big challenge for the industry and also makes a lot of the existing method in fighting fraud crime sort of render them less effective. Because if you can't detect, because a lot of the current methods are based on detections, investigations and then resolutions, be it prosecution or settling out of court. But all those kind of rely on the crime being the fraud having happened and then relying on the ability of detecting that fraud, then you can follow up with the investigation and so on. But when it comes to opportunistic Fraud, it's tricky because most of it go undetected and indeed it's a big problem for the industry. It's been estimated to cost the industry around a billion pound every year. So the IFB client comes to us and tasks us to try to come up with solutions in fighting this kind of opportunistic fraud. As I said, the traditional method in fighting fraud are unlikely to work here. And then the idea is that behavioral science might offer an alternative, an effective alternative in fighting this crime.

Yeah. And so what are just to get the lay of the land here as far as the traditional methods for fighting that type of opportunistic insurance fraud, I'm guessing is, you know, threatening letters or what sort of things were people would they have tried before that wasn't working to get people to actually say that the laptop that was stolen was worth £500 and not say it was actually 650 or something like that? What's the, what were the tactics that they had tried that didn't work?

I think actually there hasn't been a lot that's been done. I think the industry collectively, or at least in the uk, has been reluctant to try to enforce solutions. I think largely because this is just so hard to prove and there's certain operational risk involved because if you start accusing people something that you can't prove, then the risk is that you could have false positive and a lot of undesirable consequences in terms of the brand risk and customer complaint, etc. Etc. So I think on the whole, I think in the uk, I mean, this is just one of those topics, I think as an elephant in the room, everybody knows, is costing the industry a sizable amount of money every year. But there isn't really very satisfactory solutions out there. And to the point is, I would say it's kind of untapped territory until the rise of behavioral economics and behavioral techniques that might offer solutions.

Right. And so in that point, you know, so you all from Dec Tech being brought in to work on this problem and so, you know, you know that people are having this opportunistic fraud and then knowing that basically that means, you know, it's generally good people, they're having the, in the moment, you think, like, maybe I'll go ahead and do this. But being able to know that, like you had said and kind of alluded to earlier, that it's not a well planned, you know, that somebody thinks for, you know, days or weeks or whatever it is that they're going to do this, it just is something that Happens in the moment, which presents a unique opportunity in being able to address the brain essentially in that moment when they would be teetering on the edge of the should I, shouldn't I question to put in some sort of an intervention to nudge them to do the right thing.

Right, correct. I mean, that's. That's absolutely correct. I think as the intuitions, you know, from the client is that this could be a very fertile hunting ground for behavioral science for nudge to work. I think, you know, I mean, we collectively in our field, we talk about nudging a lot. Nudge is not the silver bullet for every single problem. I think nudge, as we know, only really works or worked well in certain situation. I like to use the analogy of, you know, you can never. You can really only nudge someone if they are kind of on the fence, sitting on the fence of a decision so they can go either way. They need that little nudge to encourage them to go one way or the other. So you will never be able, you know, no amount of nudge, you're going to change someone else's decision if they are so far, you know, away from the fence on the other side. So it's about identifying those moments in decision making that are nudgeable. And I think the thinking before, when we were called to look into the problem, is that this potentially could be one of those moments that consumers are very nudgeable, and then we subsequently kind of prove it.

Right.

And so you work to develop, using five different behavioral concepts, essentially put together 18 different nudges, you know, sort of those opportunistic moments to see what worked the best. Can you talk a little bit about the five concepts you chose, maybe how you got to them, but then also the way that those were being executed, Just giving examples of a few. We obviously don't need to talk about all 18 that you tried.

Yeah, sure. I won't go through the whole list of 18, although some of them are very interesting. So I'll try to restrain myself. So our tasks consist of two parts. I mean, the first task, as you said, is to come up with those potential nudge candidates that can be applied during this. What's called the operational communication processes. So these are basically touch points between consumers and the insurers. So, for example, when you apply for insurance, you're filling out the insurance form. That is an operational communication process. Right. So what are the nudges that we can use intervention that we can include in that process to dissuade people from being dishonest? So for example, when they answer questions about their driving conviction, how can we come up with what nudges can we use to make them answer those more honestly? And conversely, in the claim process, there's another operational communication process that people will fill in a claims form and there will be opportunity for them to lie. And again, the idea is whether intervention, well placed, timely intervention message will allow us to kind of nudge people down the right way. So coming up with those intervention messages is task one and then task two is to come up with a testing paradigm which we can at least in principle, test their effectiveness. So do they really improve honesty, dissuade dishonesty? So those are kind of the two tasks that we have. So let me just answer your question, which is the first task. So yeah, so how do we come up with those intervention? So that's by way of a literature review of, you know, all the previously published studies in kind of similar setup, both in, you know, academic and commercial backdrops. So the idea there is to go through those studies and to see what kind of intervention message that people have used in the past or be in different contexts have worked in terms of changing consumers behavior. And so yeah, so we go through literature review, hundreds of papers and then we kind of distill the learning and find that really there are kind of five areas that these kind of interventions have come from. So we have norming and I'm sure, you know, it's a very people likes to be consistent with their peers. So giving people some information about what their peers do might have an impact on, you know, making them change their own behavior. So one example, one of those intervention that we crafted under this norming domain is one of showing people how honest other consumers are when they are applying for insurance, for example. So one of those message that we tested is 95% of insurance customers complete their application forms correctly and honestly. It's good to be one of them, right? So that's just an example of what one of those intervention message looks like. And that's based on the principle of norming. And similarly, the other four domains where we picked out we use to generate this intervention message are self consistency. So people don't just want to be consistent with other people, also like to be consistent with themselves. If you somehow tell them that you know they are honest, then chances are they are going to follow through. And at least you know, they are. There have been studied to show that. So one of the intervention that we tested there under this domain, self consistency, is to actually get them to sign an honesty pledge up front before the whole process. Because typically when you go through one of this application process, you sign at the end and then you, you make a pledge of, you know, I provided those information honestly and truthfully. But there has been studies to show that actually if you do that upfront, you improve the honesty of people in a substantive way. So, so we decided, you know, that is a worthy candidate to, to test out. And then priming turns out that people not only want to be consistent with themselves and other people, they sometimes they want to be consistent with something that they've seen or heard, even though it's completely unrelated, irrelevant to the task on hand later on. And again, numerous studies in academia have shown that you show people random numbers and ask them to crawl a price. People will, you know, if they see a high price, high number before they will crop a high price. So plenty of studies that show this priming effect. So yeah, so priming is another principle that we, we generated interventions from. And I particularly like that one because the example, the candidate intervention we use there is quite clever actually. So, you know, when you go through this website, sometimes you have to do little tasks to show that you're not robot. I absolutely hate those tasks because every time when they ask me to take pictures, that was a car in, I always see a lot, you know, every single, whether they're there or not. Right. So anyway, so using that idea, so what we did is, okay, so pretend that you are doing this application process. Such tasks come up to say, just to show that you are not to prove that you're not robot. So here's a list of words. Can you tell me which of these words relates to the word honest? And then you have words like open, transparent and then amongst other red herrings. So they would do this task and they would say, yeah, I'm not a robot. So this is completely covert. We're not even telling them, you know, that, you know, giving them information that to do with the task on hand or prompting them to be on. It's all prompting in a kind of very covert way. So anyways, the priming. So that is kind of the inspiration behind that intervention. And then we also tested framing and reciprocations type intervention. So framing is your classic loss framing leveraging on the principle of loss aversion. I'm sure you and your listener will be well versed and reciprocation again, you know, very well published topics. If you tell people that you're honest, then chances are people will be honest to you. So there the example that we use is Lemonade insurance charity case studies again Lemonade actually the case in point is American Insurance Company the great Dan Ariely has a hand in setting it up. I mean they famously being very transparent in their pricing model. Part of their preceding goes to charity and it's a great brand assets for them. So we think that there could be some mileage here in driving dishonesty in consumer because by telling consumer that you are honest you are fair. Chances are there's a chance that they might reciprocate. So that is the kind of the lemonade intervention that we use under the reciprocation umbrella.

Yeah, absolutely. And so I actually have episodes on most all of what you had talked about. So for those listening and as Benny was talking, if you haven't heard these already there is an episode on priming. I have an episode on Social Proof which is where we would have talked about that norming kind of concept. There's also framing, reciprocity, loss aversion. My interview with Dan Ariely the those will all be linked in the show notes. I don't yet have something at the time of this recording on self consistency and pre commitment but I've added it to the list. So if it hasn't come out yet it will be coming soon. It might be. I like to kind of stagger them. When a guest talks about a concept that hasn't had a dedicated episode yet it gives me an opportunity to make one right. Helps kind of build out the content. I too loved. I love the priming example and it's such a subtle thing where if and I really appreciate that as someone who's had to prove I'm not a robot a lot in my life just like everyone who's listening, you don't question the motive behind the word on the captcha or whatever it is. Right. You just assume it's random. And so having that come together in that way versus having a pop up that says be honest which I know you did have some work with pop ups as well but it's an interesting way to kind of sneak it in there and also be forcing them to consciously engage with what happens to be there versus you know, an ad that happens to be on the side where it might get filtered out by the subconscious you're not going to really pay attention. But when you have to focus on the words it has a different impact on the brain. Right?

That's absolutely right. Yes. We'll talk about the conscious and the subconscious later because I think that is a very important Point because obviously one of the things that are really important to insurers is that for this intervention to be usable, they cannot leave a negative perceptions or imprint in their customer. They cannot risk alienating their customers by exposing them to this kind of intervention. And also a true nudge should be inconceptible, so you shouldn't even notice you've been nudged. So that's one point I would go back to later on when we talk about the outcome, the results.

I think we're in a point where we can just jump in on the results now. So we've talked about how you built it and which ones worked and what did you find?

Yes, perhaps I would just stop just describing the actual paradigm, the testing paradigm. How do we actually test it? Yeah, so this is using what we call a randomized control trial methodology. So we call it our behavior lab approach, which is basically a quasi online experiment setup. So what we did there is we in that online environment, we replicated a mock up applications and claim online processes so that are designed to look like, you know, what consumers will encounter when they apply for motor insurance online or when they make a claim online on their motor insurance policy. So I think that realism, that recreating that realism is a really important aspect, really important point. Because as we know, behavior is incredibly malleable. As we discussed earlier, context is king. In order to really be able to measure behavior to a high fidelity, you need to want to make sure the decision making environments are realistic. So we put in a lot of care and attention into crafting that application or claim journeys as realistic as to their real life experience as possible. And in this process, in this experience they would encounter some what we call sort of contentious questions. So these are the contentious questions that they might be incentivized to lie about because they know this may have an impact on the, be it the premium or the claim amount. So as I said, this is a motor insurance paradigm. So the question that we included are, you know, have you ever been convicted of speeding? So that's one of such contentious questions that they have to answer in a mock up application process. And they are ordered. So those are the kind of the dependent variable, if you like, of the study. So the way that we measure their honesty is by way of an aggregate which set of people come in and see a different version of that process, the control version of that process, without any intervention message. So they would just go through the whole process, answer those contentious questions without seeing any intervention. Whereas test conditions scenario is the one that will try each one of the 18 interventions in turn. And by comparing people's response collectively towards those contentious questions between the different conditions, then we will be able to see how effective are those intervention in swaying dishonesty. Because you would expect if the intervention is working, then collectively more people will be willing to admit that they have been caught spitting before compared to the control. If that makes sense. Yeah, yeah. And then we got, you know, more than 12,000 consumers, these are motor policyholders, to come through and take part in this online quasi randomized control trial studies which as I said tested, we tested all 18 interventions along with the control and no intervention control. And the results are staggering because on average it turns out that those intervention are able to sway 36% of the dishonesty. So this is to say that, you know, 36% of the people that were prepared to lie in the control conditions have become honest on average in those conditions where intervention were shown. And perhaps, you know, interestingly is the one in the norming category. So the intervention in Norman category have proven to be the most effective. With the example of the 95% of customers being honest. That message is a top performing intervention. And then that has an impact of 55% dishonesty swaying, which is, you know, impressive because all we are doing there is just showing a little pop up message before they answered the questions. And then that was we were able to nudge over half of the would be offender down the right path. So not all of the intervention works the same. Some work less well than others. But I think of the 18 that we tested, only one that didn't really work. But all of them have shown some positive impact in this weighing dishonesty. So that again, sort of, you know, give us a lot of confidence that, you know, we didn't just fluke it with. In one instance we have catch people, we have hit a sweet spot. You know, back to the point about, you know, catching people, you know, making a decision on when they're sitting on the fence. So we are really catching people in, you know, in a position where they are on the fence. And this notch has proven to be very effective, right?

Absolutely. And I love that. It just shows the importance of testing as well to where if you were to just say, you know, I'm pretty sure if we were to do this priming thing, that'll, you know, that should have an impact. Let's just go ahead and do it and hope it works. Which I think a lot of businesses just, you know, maybe you see something you heard a little bit about loss aversion and so you decide to throw it in and see what happens. But when you do have the capacity, when the stakes are high like this and you've got, you know, a billion pounds that's being lost and it's difficult and you can test, you're able to see they all made a difference. So that's great. You know, any of them are better than doing nothing, except like you said, maybe one. But now you're able to see that that norming pop up was significantly better and is saving hundreds, you know, it's a difference of hundreds of millions of pounds that are saved when you use those really great intervention like finding the one that works the best. And then I'm sure there are opportunities for the, you know, the bureau and everything to go back and you know, maybe try a couple of them in combination and see what works. And you know, just being able to put that out live into the field and see how it translates from the test.

Indeed. I think the, I mean I haven't listened to some of your previous podcasts. I know you're advocate of testing, which you know is, you know, so I think we are all the same opinion on that. And perhaps, you know, we are an even stronger advocate of testing because we build up a whole business model on it. Indeed, test and learn is the essence of a true science when it comes to, you know, behavioral science cannot really be called behavioral science if you can't experiment and test and prove or disprove hypothesis with it. And for us it's just paramount that you know, you need to test. And also there is the point about the holy grail of testing is doing real life trial. But those are expensive and sometimes risky to do and hard to scale, right in the real life you can only really test so many variants. And some of the more out there ideas perhaps are just not suitable to test because they might just be too risky or unrealistic to realize in a real world context. So these kind of quasi experiments kind of give you the middle ground that you can really go out before you go out and do your real life test to test a wide variety of different ideas to hone into the one, you know, it's a proof of concept exercise to hone into the one that are really have shown good potentials and then you can go out to fail and do your real world trial to asking the impact and establish the business case. So we've been working with a client advocating them to do this kind of, you know, quasi experiment. Our behavior lab approach in conjunction with Their real life A B testing because we think those are actually very complementary and cost effective because you know, you can narrow down the idea to a feel good ones that you know, you know will probably work. Most probably work before you go out to the field because let's face it, going out to the field is expensive, takes longer to do and comes with various risk.

Yeah, absolutely. I think that is a really great combination. And when you have the freedom to be able to try something in a test like this where you're able to throw in that random intervention that you say this seems weird, but let's do it, it probably won't work. But anytime those get thrown in there it they just have the chance to surprise everybody. And I've seen so many examples when I've had conversations with people that are out doing these tests that you know that one thing that you thought, well, why not? Right? It ends up doing better than everything else. So it's just good to get out of your own, your own way and test things when it is a safe space so that you can see, see you know, what amazing things can come out of it. And sometimes, you know, social proof does the trick and you prove what you knew anyway or whatnot. But it's, I think it's just a really great opportunity to check into it and make sure that you're on the right path. Like you said before, you're where you're not having to really risk and lose a lot if it messes up.

And also you lift the ceiling of creativity and innovations because they are just things that are so out there that you can test and in a way that are no risk because it's a safe room, clean room environment and you can do so, you know, relatively quickly and cheaply because you know, everything just happened in this online crossout environment. So I was saying I would go back to the point about these interventions are sort of operating in a covert manner, sort of, you know, operating sort of in an under, under the radar kind of way. So as part of the task, after they've gone through the mock up application or claim exercise, the each respondents were asked to rate their perceptions towards the insurers and also towards the process. And these are things such as, you know, yeah, I think this process is easy, it's clear, it's fair. This insurance, you know, give you, you know, value for money. They are honest insurers, that kind of thing. Right. So they're perceptive statements that they have to rate. We're doing this because of the concern that is not A good nudge if everybody has noticed what you're doing and also if people living the process with a bitter taste in their mouth. And when we compare those perception scores, outcomes across the different conditions that we run, when we test each of the 18 interventions, it turned out that none of the intervention actually significantly impacted these perception scores. So in another word, basically, people just really don't notice that this intervention, they've seen this intervention at all. Right. So the only one that have a significant impact is a positive impact. So people actually leaving the process having a better perceptions than those in the control conditions. Now, this is the laminate charity reciprocations interventions. So in terms of swaying dishonesty, the lemonade intervention actually didn't work that well. So we are talking about sort of 14% dishonesty being swayed, but they have significant positive impact on perception. So this is saying that, you know, you might not improve people's honesty, but people certainly feel better having known that you are honest and open and fair insurers. So it's just a more positive head for the insurers anyway. So that aside, I think the key point here is, yeah, none of these intervention left a negative impact on the outcome perceptions, which is really good news because these are under the weight, true nudges, right?

Yeah, that's. So it's exactly what you want. And then you have the opportunity to say, well, maybe we combine that lemonade piece with the norming piece so we can get the positive halo and we get the honest effects or whatever that happens to be as they move forward. Which is. But knowing that none of them made it to where people had that kind of bad taste in their mouth is. It just leaves a lot of options open for the insurance companies, which is great and really beneficial. So thank you so much for joining me to talk about this really fantastic project. I love that there's so much detail and we'll make sure to, you know, link to more information for anyone who wants to read more about what you all did on the project and seeing some more about that. But what's the best way to, you know, learn more, get in contact with you if people do have other questions or, you know, want to see what other stuff you're up to?

I mean, you can contact me on LinkedIn. You can also follow me on Twitter. My Twitter handle is anydecktech. You can also come to our website, Dectech.co.uk where we have loads of other case studies, including this one where we have utilized this behavioral lab approach, this randomized controlled trial. Study approach to solve clients problem in different industry.

Perfect. Well we will definitely have links for all that in the show notes so everyone can learn more. And I love your case studies from DEC Tech. They're very well put together to help someone really see the process that went into it, how you thought about it, how the questions changed over time, things like that. So those are a really great resource and we'll make sure to have those for all of our listeners to go and check out. And thanks again Benny for joining me. It's been great to chat with you today.

No problem at all. Thank you for having me.

So what got your brain buzzing as you learned from Benny Chung today? For me, I love the insurance fraud example because it shows how when you take the time to step back and think about your problem in a different way, it can actually be solved with very simple tweaks. The thing about behavioral economics is just like any field, it isn't a silver bullet. There's a lot of work and understanding and testing that went into understanding the problem, breaking it down into its smallest components, and then designing some interventions that should nudge behavior in a positive, positive way. In my third book, the Truth About Pricing, I introduce my nudgeability quadrant, a way to look at a problem, project or experience and break it into its micro moments. Then sorting those moments by how important they are and how nudgeable they are to help a company to choose where to focus a test like this. Finding that moment of filling out the form was key. And of course not knowing that the micro moments are even smaller than the whole form. Beyond that, to determine the specific test points like the captcha or other word choice and messaging within the moments. Finding important and nudgeable moments helps to increase the likelihood that your intervention, the behavioral concept you incorporate into your project, will succeed. As Benny showed us today, small changes can save hundreds of millions when they're properly planned. And I love what that means for behavioral economics in all sorts of businesses. As we close out the show, don't forget about those show notes with links to my top related past episodes and books, a timestamp summary of the episode, and more. It's all waiting for you in the app you're listening to and atthe brainy business.com 410 and just like that, episode 410 with Dr. Benny Chung is done. Join me Friday for a brand new episode with Jordan Bridger. It's going to be a lot of fun. You don't want to miss it. Until then, thanks again for listening and learning with me and remember to be thoughtful.

Thank you for listening to the Brainy Business Podcast. Molina offers virtual strategy sessions, workshops and other services to help businesses be more brain friendly. For more free resources, visit thebrainybusiness.com.