In this video Paul Chong from Ophelos chats about his experience and perspective on the evolution of digital collections in the UK. What works, how this is in some ways reflecting customer preferences that were there before, and where the real opportunity lays.
Find out more about Ophelos -> Here.Interview Transcript
So hi, everyone, I’m here with Paul Chong today. He’s the co founder of philos, debt resolution platform, you know, unconstrained and things like AI and data centric in particular. So when Paul, thanks very much for joining me today, I really appreciate it. You guys are very much in that sort almost like, like digital space. And then we were chatting about that a little bit before. I mean, I mean, how would you sort of describe yourselves in terms of like, as, as we’ve seen this sort of massive migration on wave towards like, almost like automated sort of online processing, how you think all that kind of fits in really, it really comes
from the basis of who we are as a company, and what the makeup of our organisation is. And we’re very much from that core of technology, my own background, being in companies like IBM, or spending an awful lot of time in AI and advanced technology. I think that sort of gives you a sense of where we come from, from a technology perspective, rather than, let’s say somebody looking at this problem purely from a service perspective. So it’s all about for us, using the very best technology to solve problems and to deliver outcomes. So to some degree, you know, yes, this concept of digital is important. But largely speaking, it’s about using and applying the very best technology to provide the very best outcomes.
But how much do you think so digital always used to be around sort of like, how do you take cost out of the process? How much do you think should not be about that versus as data versus customer treatment? To a certain extent,
I feel it’s an over applied term, digital, and it’s easy for people to put in occasionally, you put in a website, that’s not too difficult, you can make it reasonably easy to to pay get someone to pay in full. But actually, it’s bigger than that. And it’s largely taking this customer through some type of triage, that gives them access to, I guess it gives them some sense of taking back control of their outcomes, giving them the ability to make decisions and flexibility. And that overall digital thing is about convenience. Right? So yes, I get your point about Digital’s about cost saving, but actually think it’s also about customers, frankly, not wanting to talk to people, it’s not to say that people, people find they have to speak to people, because that’s the only mechanism, you have a phone call, you might have a live chat, Oh, damn, I can’t solve this for myself, I’m gonna have to speak to somebody. But you can bet your bottom dollar at the same time, they’re getting incredibly frustrated with the process. And I don’t think this is about cost anymore. I think this is largely about the fact that we can’t get enough people to do do that type of work. Getting people to chase people to to pay is not a great mechanism for someone to solve their problems. But it requires a huge amount of work and a huge amount of effort to think about the end to end process and the journey that someone might take,
that’s convenient. But also almost like efficiency from a consumer point of view is like the efficiency of getting stuff done, I need to get done as quick as possible. to certain extent, two things
are really important for me, we’re all reduced in terms of the time that we have. And frankly, a lot of people don’t want to spend their time solving their debt issues. We’re also in the stage where we’re having an ever reducing wallet size, right, so the wallet is getting smaller because of cost of living. And yet there’s reduced time to spend on these things to get them done. So for me, the debt industry is having to compete for time, and the share of the wallet. And so you have to compete means you have to be as good as someone making it really easy to buy a product online. Right? So you have to be as good as them to compete for their time and for their space. And frankly, for their money.
Well, quite interesting to note, like moving up the hierarchy of payments on is almost like digital servicing mindset can move you up the hierarchy of payments, at least I normally use the word digital because you sort of saying, well, maybe we shouldn’t be thinking about that. We think about it the wrong ways. But the technical customer friendly way of doing things moves you up the payment hierarchy.
Yeah, exactly. People don’t want to spend their time paying off debt. And largely speaking, if you think about it, there is no gratification point that gratification was passed from the original purchase of whatever it was at that time that they have quiet enjoyment on. So you’re at a stage where it’s tricky to get people to engage with you. So largely, we want that sense of giving back control, letting them have convenience to do so not taking away that personal responsibility for someone’s debt. But just allowing them do it in something that’s familiar to them right in a familiar way that they buy something they’re handing, you know, they’re paying for their debt, and you’re doing it in a very convenient way. Right? But it’s not about having to speak to someone is not creating friction points where you don’t need them. So a lot, that’s about sort of finding the very best ways to build that engagement with a consumer that finds themselves
with that. One of the things you just mentioned, there was around control. And that’s just this, this idea of being able to be almost like in control of your own destiny, which has definitely come as a result of the internet, you know, some of the online processing. As consumers, we all feel much more like we’re in control of what we can do, what we can buy, how we can customise our products, those kind of thing. How much of that do you think is important in terms of bleeding through into the into the collections industry, essentially, as well, that control rather than sort of saying, Well, we’re going to impose what we want you to do, rather than I feel like I’m in control around what I want to do.
Sometimes it’s perceived and a sense of control. I mean, largely speaking, the word control has been monopolised by Brexit, you know, Brexit was a great one, they had a line of take back control. And largely, that was one of the strap lines that really got people engaged with that problem statement about what should we do, we’re having all these issues, you, we’re going to give you back control, we’re going to take back control, that is a behavioural science concept is well known as well versed. There’s a lot of paperwork, research around it. And so yeah, we very much are looking to give people that sense of control and give them that sense of flexibility. Make choices for yourself. But again, as I said, it’s not saying you don’t have personal responsibility within that process. It’s just saying, Yeah, actually, I now have control, I haven’t got to speak to somebody on the other end, I haven’t got to work out whether that number works for me. It’s allowing them to actually fulfil their own responsibilities and outcomes, frankly, and not everybody wants to feel like they’re in control. When you
said control there. And as you mentioned, Brexit, they’ll the B word, I actually thought you’d mentioned the concept of control. She talked about the regulator, the regulator, sort of like enforcing control, because, you know, as regulated entities, you know, everyone’s sort of being forced to have much better controls from that angle, though, as well. I mean, how do you think the regulator’s kept up with some of these new approaches, and I get a sense that sort of, there’s also a bit of pressure to go back to when you can always rely on a human to sort of have that interaction with customers? And that becomes a bit of a safety blanket for us. Are you finding that obviously, as it’s almost like a technology first type of approach? Is that something that’s gradually changing? Or is it changed at all?
Sadly speaking, I think there is this sense that if somebody if a human is involved in the, the chain, so as you say, then ultimately, there’s someone to blame. And sorry, that’s a blame culture thing, right? Where you go, Well, I’ve got to have someone to blame for this process. If it didn’t work. I think if I’m honest, from the conversations that are ongoing with FCA, I think they’re largely open to you know, what makes sense and what’s right to treat customers fairly. And so we spend a lot of time articulating how our journey works, how it operates, how it triage is, right? You know, it’s not about just saying, Well, if the digital journey finishes, that’s the end of it. It’s not how we work, you know, we do have phone calls, you know, you can call fellows at any point. The reality is, however, that we believe you’re best served by solving for yourself. But there are always circumstances where certain customers will need more hand holding, and we’re ready to deal with it.
And what are you saying, when you sort of talking with clients? Are they on board with it? Or? Or is this sort of undercurrent around? Well, sort of, like, relate to it? Let’s take for example, vulnerable customers, like you have to talk with someone? I mean, I’ve heard that before. Are you finding that that’s, that’s changing as well? Or? And are they thinking of it as being a benefit? Or is it still just really sort of like, well, I can take cost out?
If I’m on it? Well, the way that we see it is that I still want people involved in the engagement, especially when they’re vulnerable customers. It’s like trying to unpack the last mile of anything, it’s incredibly difficult. It’s very edge case, it relies on a lot of bespoke information about that individual to determine it, don’t get me wrong in the future, 510 years time, you know, maybe there is a pathway where you can fully automate that journey. But as I said, this point, there’s very important aspects of the way we deliver it. And in parlance, triage is, you know, I would love my team to be just pure vulnerability consultants, consultants, I mean it as much as they’re talking to customers. They’re finding the right signposting or engagement. I’d like them also to have that advice capability so that they can actually start to help people solve their debt in the long term. And to do so you’ve got to understand their problem. So, you know, we’re not we’re not saying there’s a digital solution for everything, or even an AI solution for everything. What we’re saying is though, we can start to understand what particular customer situations exist, and how best to deal with it. But yeah, for vulnerable customers. You know, we’re very mindful that we pick up on those and those who can serve for themselves, if you just need nudging back in are doing so in the right way.
So your approach to almost like the digital transformation, I’m going to use the word digital is almost like the most like The Pareto principle in terms of like what you’re going to take, tackle the 80%, for you the H percent first, then you’re going to do the next 80%, then you do the next 90%. And just keep on going. So there’s always this little bit that’s left, but you just sort of keep on filtering all the way down. And over time, you’re getting this curve as it sort of flattens off to be attending to 100%, but not actually necessarily, ever being 100%.
Yeah, the normal distribution is you always have edge cases, right? Even when we came into this industry, and bringing new technologies like machine learning to know who and how and when to contact people. There was always edge cases within that, right, these systems work like human beings, they work on probability. But what we also do is look for continuous improvement of our processes. So we’re saying, Okay, let’s test them experiment. What if we did this in the process, what happens next? And so it’s always testing those things before we implement anything into production. But that’s one of the beauties of as you say, you’re slowly slowly pushing, pushing, pushing to the endpoint, where arguably, you ultimately will get to a stage where you’re dealing with the market of one person. And everybody I know wants to be dealt with, like a human, but also as an individual
and data. And you can think of collections almost like as an information gathering process as well. I think that that way, which is like every single interaction, you gathering extra information, you don’t have externally as well, what’s the balance of almost like, external data versus internal data you might gather through your process? And how far can you get just external data, a lot of emphasis that are in the market, but is it everything?
Data, I guess, in just broad bucket terms is static and dynamic data, static data that you might get from a credit reference agency, you might get it from a primary lender. And then there’s all this dynamic information on how someone’s interacting on your platform, whether they’re engaging with you? What type of engagement does it look like? That, interestingly enough, becomes a much bigger piece of our understanding of customers than does the static information. The combination of both Mexican credibly powerful data engine, not just for us, but also for clients that we work with, because frankly, they get to see everything that’s going on in their business. And, frankly, how we’re treating customers, which ultimately, were the sort of threshold that FCA hold us to
write and talk to talk a little bit about AI and using AI. And that’s been a term that sort of bandied around, particularly sort of five years ago, an awful lot in terms of sort of machine learning or using statistical methods to do it. And it almost feels like there’s been, there’s been a lot of talk around it, but it actually means a lot of different things to a lot of different people. And there’s a lot of different ways of almost like creating almost like use cases and solutions for different processes as well. So it’s not just like one term, you know, how do you think about it? How do you use it? How do you use it? And what are some of the use cases, you think of sort of the most successful in the collections context?
I think most people’s understanding of AI or machine learning sort of represented, is represented by chat bots. And, interestingly enough, you know, I’ve been in this sector of AI for almost a decade now. And, you know, there are still challenges around chatbots. Right, and they can be sometimes as bad as an IVR system. And, you know, think very carefully about how you implement and how you deliver strong outcomes for people and not create frustration in the process. It’s not to say they don’t have a place, they just need to be done in the right way. And, and that really, the Chatbot is all around natural language processing, the way that we think about how we can apply natural language processing is, as an example, how we can understand a customer’s behaviour and whether there are indications that they may be vulnerable. That’s a really good use case is great for compliance. But it’s also great to understand what type of pathway should we put them on. And then that gives us an opportunity potentially to automate in the future as well as those journeys. And so that’s, that’s around natural language, there’s huge amount of opportunity. And don’t get me wrong, the technology is advancing. So where where I was 10 years ago. We have seen accelerations of advancements on how capable that technology is for right and I think that’s what people forget. All we’re doing is with machine learning, or AI Call it what you want, is taking the intelligence and expertise of one person. In fact, this time it’s embedded within the data, and then just scaling that kind of expertise.
And how do you go about almost like describing those use cases? Or describing the outcomes or finding those outcomes? Because you can, you can design it for lots of different outcomes. And we can probably come up like four or five straightaway. And then you can just iterate those. I mean, how do you decide which one’s the best or which one’s the right the right sort of scenarios to go after? You talked about like vulnerabilities and example? Right, next best action or right time to call? In? Those are some some obvious ones there. But there could be other ones as well. I mean, how do you land on which ones to look at first?
Yeah, of course, there’s, there’s always, you know, as a co founder for the business, we’re looking at what opportunities there are to improve processes, but largely also outcomes for both clients and consumers. The way that we do it, though, there is obviously a process around how we think about testing and experimenting. But also, I think, what you have to remember is that our models have this is not just one thing, right? I think this is what people realise it’s not a analogous just one sort of beast of an AI or ml system. What it’s doing is it’s providing a constant feedback loop. And it’s that feedback loop that helps both improve those models, and find and seek opportunities that are missing through that process. And so it’s that feedback loop. That’s really, really important. And, you know, when we started this business, the one of the great things about debt collection, compared to some other industries, and is it’s relatively narrow. In its specifics, it’s not to say it’s all the same. I’m not saying everybody’s the same, but it’s very narrow, which means using applied machine learning is a whole lot easier than it is to, let’s say, healthcare, where you could have 20,000 Presenting conditions for an illness. And then you’ve got to expect the system to understand and interpret that. I’ve got us I’ve got a sore throat, I’ve got a headache. Oh, well, that therefore implies this, we’ve got a much more narrow use case, in debt collection. It’s not easy, but it’s understandable. And it’s far more defined,
I suppose as to the other extent, to another extent, almost the flick through financial services been quite data rich for the longest time as well. I mean, you’ve had credit risk out there. I mean, so that’s quite an evolved kind of system in terms of like being warmed to some of the approaches, although doesn’t necessarily mean to say it’s easy, because, you know, otherwise, we will be almost like there. Yeah, right.
Yeah, there is a lot of data. And obviously, you know, there’s a lot of rich data with credit reference agencies, even the government produces static data around social deprivation indices, right, which are a good proxy, sometimes for CRA information. I think, don’t get me one that we are always looking for what data can be used, either to improve the journey or for the model to consume? And then determine what the next best action is? So yeah, we’re always looking at where on what possible data can have an impact?
And what about recency of data? So you talked a bit about credit bureau, which tends to be sort of like lag lag, somewhat, you talked a bit about earlier, a little bit of our website interaction, which is, which sounds like that’s very predictive, at least in terms of behavioural and sort of the combination of the two, how much of recency of data do you think is going to be important? And particularly looking at things like website interactions in terms of predicting what’s going to happen in the next the next week or the next month? Versus over longer term periods? I mean, are we in this almost like shortening of timeframes and outlooks, particularly if we look at the pandemic? And I suppose cost of living crisis as well?
Yeah, I think that’s, that’s one of the biggest benefits of using machine learning and AI in this field, is it starts to, we start to see different actions and reactions by consumers and how they engage with us. That starts to inform if you have a feedback loop on your machine learning rather than just using it in a historical, scientific kind of research way. When you feedback, that loop, it starts to reflect and look for different outcomes or looking for an outcome, but ask it to take different actions off the back of it. And so where typically, people might have had some very good rules, you know, and I guess more deterministic systems to allow them to make a decision. When you use machine learning, it starts to adapt very quickly off the back of changing behaviours of consumers and how they’re acting and reacting to things. That gives us an opportunity to optimise the messaging, but also the journey itself and go, Oh, actually, we need to do something differently here because we’re seeing that people are missing this point where they should be signposted, and we need to do more work on that. Things like that. Right? How do you how do you how do you deal
with things like false negatives or false positives, I suppose in the data were in because the machine learning gives you a probability that let’s say that someone vulnerable as an example, that might Like to a certain extent lead you to take certain decisions, I suppose was the fear, or could indicate that there’s an 80% likelihood that this person has is in this particular situation. Obviously, there’s a 20% chance that they’re not. And you know, so how do you how do you sort of deal with that ambiguity within? What can be quite a tricky conversation or process sort of, you know, within collections?
There’s no, I’m not a great believer in absolution, right, that there’s black or white, arguably, machine learning is all about probability. Right? So yeah, let’s say the model is saying that it’s 80% probable that this of this action will have the right outcome, largely speaking, you could go and take that outcome, and it might not deliver it. Therefore, there’s certain ambiguity in the journeys that customer taken and the communications that we give that allows them to find, you know, with ease that other option that’s right for them, right. So it’s not about, I think people get a little bit stuck that you suddenly go, Well, I’m going to because they did this, I’m now going to do this same way as we’d like to, if an agent is talking to somebody, and that communication starting to show slip signals that the customer is potentially vulnerable at that stage of that conversation. It’s only highlighting that that might be the case, it’s not saying, oh, gosh, that customers now needs to be put into a vulnerable customer journey. That’s not how it works. I think that’s what you’ve got to understand when machine learning is that it’s okay to deal with ambiguity. You just got to deal with those journeys in the very best way.
I like to think almost like it’s almost like using, you’re on a plane and you’ve got the different dials in terms of giving you guidance around how you should fly the plane of which you there’s a probability it should be done a certain way versus this is exactly what’s actually happening, almost like a machine like mechanical machines sort of thing. Yeah, exactly.
And I think that’s, that’s where people just, it’s easy to think that and it’s easy to talk about, general artificial intelligence and robots walking the streets. The reality is, is how you apply AI in a very ethical way, but also look for journeys that don’t create that sort of black and white sort of outcomes. It’s not it’s this or it’s this, it’s trying to be subtle around the nuances that you will often find within those journeys, right. And as we know, vulnerable customers, it’s about a point in time that they may be vulnerable. And arguably, the journey still might be right for them to fulfil and complete their payment journey. It’s not as straightforward as everyone likes to say, Oh, well, you do this, you then you do this.
What do you think we go from thinking particularly to like cost of living crisis? And some of the things you might be hearing around that are seeing in the data already? What’s your outlook for the for the rest of the year, and when we were expecting that to be huge volumes coming through as a result of the pandemic over the last two years really, which, which for a variety of reasons, really didn’t come through? I mean, everyone’s saying, Look, cost of livings, certainly in the media, it’s now starting to increase, it’s starting to hit a bit towards the back end after that after the summer, what’s what’s your kind of view on on the outlook,
we’re seeing signs already. And therefore, we’ve adapted accordingly, we’re fortunate to have had a further injection of investment from our venture capitalists, who are backing us in terms of solving this problem in the long term. But in the immediate term, we know that we need to improve and we need to move quicker. And therefore we’re looking at how we resource things. How do we resource things for vulnerabilities specifically? What kind of journeys do we need to think about? Is there further partnerships we need to think about from a signposting perspective, I think it’s a very broad subject matter what we’re not going to do is leave customers wanting that’s the worst situation that we can get ourselves in. But I can tell you now, Chris, the answer isn’t more people, because there aren’t more people to do the very work that’s required. And I’d say one more thing as well that I know, during the crisis of COVID, that people withdrew from communicating and engaging with customers with debt. Again, I’m not particularly in favour of that either in the sense that it obviously depends on the type of engagement. But keep keeping that constant engagement, keeping that interaction going with customers, getting them to understand you know, some of their responses visiting when they can afford it are incredibly important. If you just switch off the lights and say, Well, I’m not going to talk to them anymore. It’s just a really, really bad thing because at some point, that’s going to end up with more depth, more problems to solve and it becomes more ingrained and it becomes harder for them to get out of. Don’t get me wrong, you know, we’re doing we’re also doing just offers? Well, Chris, we’re, we’re a B Corp. Pending. But we’re also it’s not just profit, it’s also for a purpose as well. So we’re looking to help by engaging with the community, people who are helping, you know, I guess that unpacking that last mile, where people say, hey, look, I want to solve my debt problems. Help me I’ve got all this paperwork helped me through that process. So we’re looking to find other partners that we can work with, that we can fund, and that we can support so that we can help individuals as well, frankly, within that process, because we can’t always touch those people. But we know that there are people out there that are doing some really good work, helping guiding people into the right solutions.
So what should we be thinking about? Now? I suppose you think in terms of the cost of living crisis? Is it around getting hold of people as soon as possible, or getting them on to solutions as soon as possible? I mean, is that is that our responsibility? Or do you think it’s the more than once you’re doing then around sort of really generating solutions that can really, really kind of help from making it easy. From a customer experience point of view,
a lot of the work we do from behavioural science perspective, is getting people to engage, but doing it in an incredibly empathetic way. But once you start to have a reasonable engagement with people, you treat them, like adults, you treat them with respect, you get into that situation where you can have different dialogues, or you can build different journeys for them. The important thing for me is that dialogue, whatever way it happens, you know, whether people making phone calls, or whether people are creating digital journeys for people, that that communication doesn’t stop. Because, you know, from a years from now, if people are increasing the level of debt, or they think that it’s better to take on more debt than pay down existing debt, that it’s better to acquire something over something else. It’s kind of taking people in the wrong pathways, right? So it’s really important that the industry looks at this in a positive mindset for engagement, not Oh, my gosh, people can’t afford it. I won’t talk to people. Yes, a lot of people won’t be able to afford it. But actually engaging with them finding pathways that they can finding payment plans that work for them, that they essentially put back in control, you’re still giving people some great outcomes in the long term, right? People solving their debt is a good thing. People being out of debt, not in stress, not feeling anxious is a good thing. It’s just a question of how you engage with people to make them feel that sense of respect, but also control. And you know, and I think that’s a really big feature of how we think about solving at that front end of getting people to engage with us. One of the interesting aspects for us is the way we think about it is that there needs to be less shame about debt, right? Because the more shame there is there more shameful that everybody thinks their practices are, and they need to then control themselves, and then they need to stop communicating. We don’t want that to be a taboo about debt. And the more that people you know, the same way, as we’ve seen other areas of community and social life change, I think we should be looking for the same thing for debt, that it’s okay to talk about debt. It’s so that’s a much better way for people to start engaging with anybody, I don’t care whether it’s a fellas or not, to engage in this concept of actually, yeah, I would like to solve my debt. I’ve admitted that I have this debt. And I’d like to find a way out, right, whoever is in this industry to solve that problem. So that’s where Yeah, and a lot of things that we tried to do are more agnostic to the industry, you know, the stuff that we write on our website, the content that we try to push. It’s all about a lot of it’s about consumers, because we are yes, we’re a business to business. But we’re also a b2b to see where it took consumer. And so that really matters to us. Right. So yeah, I think it’s yes, I think we could all do more. But we should be less shame, for sure. Shameless say about what we do. It’s really important to communicate and engage with people
taking a step back one step back and talk a little bit about the pandemic and what we’ve been through over the last three years. I mean, obviously, that was, that’s a big shock to a lot of people, a lot of structures kind of changed in society. And this will let you know, I was in your in London, I was in London the other week. And we were looking at, like, the dynamics around how many people on the train when they’re on train, the shopping patterns, those kind of things. And it feels like, almost like we went through this massive change. And we’ve sort of gone back to normal, but have we completely gone back to normal? And I wanted to get a sense around whether you sort of like the you kind of feel that maybe we’re gonna go back to the way things were three, four or five years ago, are we seeing like a fundamental change in business and how we interact with businesses? And then what does that mean sort of going forward? What was the how we think about the industry, but then just more generally, in terms of like society going forward in terms of the collections, the collections business,
I think things have fundamentally changed right, you know, even an IRA In business, largely speaking, we were born during the COVID. Were born on the cloud and were born during COVID. So perhaps, you know, as a team, we don’t know any different. So remote working is yes, we have an office here. But yeah, there was a remote working, and we positively encourage it within the business. And we don’t distinguish between whether you’re an engineer, data scientist or customer operations, team member. So yeah, things have changed. That means, you know, when people are working remotely, you have to think about the movement of data, the security of data, the privacy of individuals, whether you’ve got the right team in front of the consumer at the right time, and have you got the right technology in front of the customer at the right time, I think those things are becoming ever increasingly more important. And I bring you back to that point earlier that we’re competing for space for time for money across the market. And it doesn’t matter whether it’s something a point of sale item, or whatever it happens to be, or whether it’s a buy now pay later product. We’re all competing for consumers time. And so we have to think about that in the broader context of how technology has changed how people buy today, how they receive this instant gratification on everything people require you buy something, it will be within my office within an hour. So which so as that’s changing, I think it’s incredibly important for the industry to think about what are those next steps. And I think, and this is not having a go at anyone particularly. But I think in the past, it’s always been one or two steps behind, where the markets been going. I genuinely believe there is an opportunity for anyone in the market that willing to take it is to drive and be the very best and compete with the very best products and services out there. That’s what’s important, Chris, for me as we go forward. But yes, to your point, I think things have inextricably changed. And I wouldn’t say for the worse, I just think things have changed our Have you adapted enough to accommodate people in the right way,
I just I just get the sense that it’s almost like we we had a certain construct and I was like that for for most of my life. And like the pandemic was like, like a Lego bricks, they sort of bash their fingers on the on the board, everything is going up in the air. And things are definitely settling now things definitely settling but I just I just get the spidey sense almost that it’s not necessarily settling in quite the same configuration it was before. In fact, it’s actually a fundamentally configuration was before the signs were there before all the pieces were there before. But now it’s gonna be quite a lot different. And if we don’t adapt, then, you know, we’re going to lose out some of the you know, perceived wisdom, the norms for before are going to be gone. And we were not going to go back to those. And some of us are still waiting for those to still happen.
Yeah, and by the way, I don’t think you can necessarily attribute this to particular age groups, although it’s often attributed to millennials and Gen Zed, but people are demanding more. People are demanding more they want things in a certain way. People want to find balance in their life, they don’t want to spend time speaking to someone over the phone call, especially over debt, it just isn’t something that people feel comfortable with. So we’re having to think differently about how to offer up what is frankly, a service from the debt industry and how it delivers it to people. And so I think largely, the big change here is people have taken a bit of a reset and decided this is how I want my life to be these are the ways that I will these are the ways that I want to be serviced in terms of supported by brands. And that’s it’s not just the debt industry. I think it’s every industry is being are you doing things in the right way? Are you doing things in the most empathetic way to deliver outcomes, whatever that outcome, whether it’s paying down debt, or whether it’s buying the latest iPhone? So yeah, people just asking and demanding more
and less. Last question. If you’re going to put your money on what where are we going to be in five years? What would you say that the technology used to look at? And it sounds like AI is machine learning still got a long way to go? There’s a lot of more sort of like process transformation essentially, was what you’re doing with with technology. I mean, but are there any sort of themes? You think, Well, this, this I think we’ve got to keep an eye on for the next three, four years. And over and above what we’ve we’ve already started
at the core of and I think this largely is directed at the primaries is the provenance of everything that’s done and the debt and the beauty, you know, to avoid essentially what the industry has to deal with, which has a lot of disputes and complaints. So the things is whether web three dot o whether blockchain have a part to play within this concept of provenance about the debt, and being assured that when you are collecting, that you’re collecting the right amount from the right person in the right place. And I think that that’s an interesting concept that I don’t think has really taken hold or, you know, frankly, people are spending a lot of time on but I definitely think there’s a lot of there’s a lot of value in the blockchain in relation to, you know, whether things exist or not, or whether things are real or not. And I think that has huge potential as we go forward. I won’t talk about VR, Chris, because, one, it’s not my subject matter of expertise. But also, I’m not entirely convinced everybody’s quite ready for that yet in this space.
It’s quite interesting. Also, like, what’s like the change kind of isn’t on like, so we’re sitting here and like, a lot of the cryptocurrencies as a former blockchain have sort of gone through a massive crash. And it’s almost like you see, you see, it’s almost like you get these ideas, and they sort of the run up. And then there’s like, what, it doesn’t quite quite work in history, the way the format is. But there’s still some fundamental stuff there around blockchain and provenance. I think it’s a good way of putting it. And now now we actually going to start to see that really sort of start to build build through. There’s no doubt about blockchain. Right?
Yeah. And I learned, I learned my lessons over the last 1020 years around the gut. You know, Gartner describe it as the hype curve. And, you know, it’s looking at the technologies that are appropriate. And I think one of the things that we’ve been very careful, especially in this space, because we care for our consumers and customers, is its application and its efficacy to application, right. So it’s not a question of just saying, Oh, well look, you know, AI, you know, that’s a sort of shiny star for us. It’s more than that. It’s more than just the tip of the iceberg. But it is everything that we think about. If it’s not appropriate, then we won’t use it, you know, and that’s really how, I guess having been through some of these hype curves. This has really been about it for me is about its application, more over than technology for technology’s sake.
Very interesting. Well, pause. Fascinating discussion. Thank you. Thank you very much for making the time today. I appreciate it. And it’s good to see you’re back in back in the office as well. I think we were chatting earlier. And I know,
we could have had a we can have an a face to face in the office. Because next time and let’s organise
that. We got to do that. But we’re talking about being in the office for for cooling reasons. And I think in the winter is going to be heating reasons, isn’t it? So like, getting out of the house, so So that’s great. Well,
if you can save your if you can save your energy bill at home. Yeah, I would definitely spend a bit more time in the office.
Thanks very much, Paul. Appreciate it.
Awesome. Yeah. Thanks, Chris.
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