All roads lead to ubiquitous banking

Emma [00:00:04] Welcome to another episode of Architects of Change, a podcast brought to you by Mambu, the cloud banking platform to help you evolve your business. I'm your host for this episode, Emma Lindley, co-founder of Women In Identity. In this episode, we're going to discuss the ubiquity of banking, the services and personalisation that both challenger and traditional banks offer, and we'll look ahead at how fintech can continue to provide customers with the most accessible and attractive services. We're going to aim to answer the question today. What do banks of the future actually look like? And, of course, touch on the exciting topic of artificial intelligence. We're going to be referencing the recent Mambu and GCP report; The Bank of the Future, how AI will power ubiquitous services and personalised customer experiences to help me discuss these fascinating topics. Today, I'm thrilled to say I've got Ben Snowman, VP of Partnerships and Advisory from Mambu and Georgina Buckley, Director of EMEA Financial Services Solutions, Google Cloud at Google, here with me today. So to kick us off, I'd be really interested to know for both of you one or two really big macro drivers that you see in banking today.

Georgina [00:01:19] Yes thank you, it’s great to be here today and talk about such an interesting topic. I think we've all been living and lived through the COVID pandemic over the course of the last two years. And I think what we've really seen is the significant increase that has driven digitisation in almost every aspect of our lives. And we've seen that not just in the UK, but globally as well. And I think that's been a huge factor in terms of the acceleration really of digitisation and what we had to talk about today. So ubiquitous banking. I think we've all had to get more familiar with digital and people who perhaps haven't embraced it before, have, just through circumstances through COVID and hopefully are seeing the benefits of that.

Ben [00:02:02] I guess there's the Covid point as well. How can we have not experienced that ourselves? I think if we take a step back and look at the industry, and I joined Mambu from one of the world's largest banks, constant regulatory change from both could call a control, but also a growth perspective, driving the digital agenda in many ways. Infrastructure changes, but also an expectation from customers around how they expect to do their banking when they expect to see their banking and so forth. And in some ways, that's driven by the huge billions and billions of dollars invested in that, the digitalisation agenda, I'd say, but also the experiences and expectations that customers have from the broader digital lives. So to me, we’re here to discuss ubiquitous banking, but to me, there are really two things that really underpin that, and one is about where customers experience financial. I'd say a financial interaction that's a point of need, but also a point of time as well.

Emma [00:03:08] You make a really good point that just about how the pandemic has changed everything. And I'm really interested to go back to you, Ben, and get an idea of what we mean by ubiquitous banking because it's a term that's out there, but not necessarily everyone know what it actually means. So just tell us in simple terms what is ubiquitous banking?

Ben [00:03:27] So let's look backwards and then and then answer that question. Banks have been around for hundreds of years, and fundamentally they do the same thing and have done the same thing for that whole period of time, which is they lend money and they receive your deposits. And as a result of that, they've been very product oriented. What I'd say is since for the last decade, say, post-financial crash in a mobile phone, this new form factor came along and the phone was always with you and it was always on. And so you could do some interesting things. And therefore the relationship with the customer and the brand, i.e. the bank changed somewhat. The banks, they’re still very product lead. But really, what's happened over the last two years because the whole digital thing has just expanded so massively across everything that you do in your life now? And banks invested billions into the digitalisation agenda. Is it the point of need is very different now and at that specific point of time, and therefore banks are now starting to move away from pure product silos. And I'll give you an example of that. Buy now, pay later is the convergence of lending and payments at the point of purchase in a retailer or online. And to me, that's ubiquitous banking because it's all about point of need at the points of time. Payments is a big area. I've just talked about the convergence of payments and lending, but to some extent it's no different when it comes to deposits or anything else for mortgages, for example. As well, we see banks moving into the property auction space. So the mortgage application process just becomes part of that journey and we see banks moving into the used car space, say the loan application as part of the journey of buying a new car. So these are the sorts of trends that we see happening now. And to me, that's ubiquitous finance. Interesting.

Emma [00:05:18] So is that real kind of melding of those worlds together that a consumer would say that's kind of merging banking with other services that they might be doing at a point in time? So just in terms of looking at that from a global picture for you, Georgina, what are the big gaps or differences we see with ubiquitous banking across the globe then?

Georgina [00:05:40] Yeah, it's a great question, actually, and I think you do see a really big variance globally. I think, you know, the digitisation trends we've been talking about, the need for businesses to be structured around customer journeys as Ben was describing. I think you see that in a lot of different countries and a lot of different jurisdictions. I think the main variances in terms of how ambitious people have been in embracing that and fundamentally putting the investment into their businesses to make that a reality. So to think of, you know, a couple of examples which hopefully listeners will know and obviously we've written a report together, actually, people want to go through that and dig into more examples and kind of bring all of this to life after the podcast. If we start in the UK, actually, which I think has led the way in a lot of banking innovation over the last few years, I always think a brilliant example is Monzo. You know, they've invested hugely in a cloud native digital stack behind their offerings. And how that translates into a customer experience is things that, you know, when they launched it almost like, Wow, can the bank do this? You know, this is really exciting. Suddenly, I’m being offered features I've never had before. So when I make a transaction, suddenly my phone pops up and tells me where I am and where I made it, so I can just make sure it was me that really made it. It wasn't someone else that stole my card, or I can get paid a day early, or I can round up when I make payments. So I have a few more savings in my savings account. And now we may be all thinking we can get those features in quite a few institutions, but actually Monzo kind of started and kicked those things off a few years ago. I think people are really excited about that and about doing banking in a new and customer focused way fundamentally. And the reality is that was all enabled by the technology that they had in place because suddenly they could do things that incumbent institutions - the banks have been with us for hundreds of years and they just cooperating with all the technology. It's harder to do unless you've invested in the stack and another nice international example, I always think is BBVA, and I think they have made huge investments in their business and and just listening to Ben, they're talking about mortgages and housing. So they've really developed a super app. So the BBVA app offers kind of every moment that matters in your life. You can go through your banking app and the housing mortgage experience is brilliant in that you can literally take a photo of a house and find out the valuation of it and then go through the application process for a mortgage and those things wouldn't even have been possible a few years ago, but they again have invested heavily in their technology, very creative bank, very creative company and management team. And I mean, they innovate in everything right across the whole customer experience through to security, actually. We do quite a lot of work with them in the AIML space on security innovation. So I just share those couple of examples, I think they are probably relevant companies that the audience will be familiar with.

Emma [00:08:28] Ben, have you got any other examples of kind of world leaders and why they're so good?

Ben [00:08:35] Thanks. I always find the most innovative in Southeast Asia. Maybank is the one in Malaysia that has moved its property auctions because that means the value chain of home purchase Maersk. You have some the customers mindset. It is about the home purchase. The mortgage is part of that rather than selling a mortgage as such, and DBS have actually done something very similar in Hong Kong, funnily enough, OCBC in Singapore. I think that one of the country's largest travel agents now because obviously buying a holiday is a major purchase and there's an affiliate revenue stream there as well. And I think maybe it's up to health care as well. And this notion of remote consultations with doctors, for example. So they're all looking at where you can stretch that the definition of banking into other areas that are relevant, where there might be an interest in some kind of financial transactional engagement.

Emma [00:09:28] So yeah, and I think that whole acceleration with the pandemic has changed things and perhaps people are more accepting of that type of transaction and the way they might be interacting with that technology. So overall, we're seeing really good predictions of what future banking looks like. Question back to you, Georgina. Are these some grey areas that still need fixing before we see real progress or is this kind of it?

Georgina [00:09:50] Gosh, I think there's so much more to do, right. I mean, I think there's so many more places that banks can move into in terms of innovation, both from the technology evolution side and also from a customer preferences side, and that continual challenge to not just meet customers needs but anticipate them. And when you ask about grey areas, the things that need fixing, I suppose I naturally start with the technology stacks that these companies are built on, right? And the core tenet of that is their data. Where is the data on the customer and what state is that data in? Is it clean? Is it manageable? And can it be configured in the right way to really power exciting customer experiences, experiences that people remember and that matter to them, actually, either in moments that are really exciting. So if you're saving for home or something, that but actually also in those moments that can be really challenging in life, if you if you suffer from fraud or you have the death of a loved one or you're dealing with really difficult life moments and actually having the right data core technology in your company to genuinely stand in the shoes of your customers and be able to be there for them in the good times. And the bad, I think, is the right place to start. And so many companies that we work with and the just are in the marketplace. They're just huge opportunities to evolve and embrace their data architecture, just to enhance customer experience, to enhance their security, enhance the risk frameworks. So I think there's loads left to do actually. And I think, can you even just with where we are today, never mind moving into spaces like digital identity, which you're an expert in and things like cryptocurrency and you know, all these new, exciting new technology advances. I think even for where we are today, there are massive opportunities to enhance data and technology architecture and therefore just fundamentally improve customer experience.

Ben [00:11:41] So that's something I think there's a huge question on empathy when it comes to data. And what I mean by that is as follows: Let's say it's your birthday. This is a theoretical use case. It's your birthday and your bank knows that your bank looks at you on your birthdays. For the last X number of years you've eaten at a particular restaurant, say, and there's a case that says the bank rewards you for being a loyal customer with a free dinner at that restaurant. Yeah, that's an entirely possible use case. Now why I talk about empathy, some customers would absolutely love that some customers would find that desperately intimidating and a bit scary and so forth. And so I think there's an ethical lens to actually how you use data in the future when it comes to some of those automations. And really that, I guess you'd say, I read that therefore there's a question about data ownership and permissions and all those sorts of topics that go around it. So. So I think that potentially what the technology can actually do and is absolutely all about data. I think there are some quite substantial societal ethical debates that still need to happen over the course of the next probably decade.

Georgina [00:12:52] I think that's so fascinating and I couldn't agree with you more than actually. And I think the reality is we are all learning together, right? There isn't a perfect answer to any of those things, and just as you're describing, you know, customers are unique, and when you're thinking about your customers and you're segmenting down that data and that personalisation, your ultimate goal is to get to your segment of one right, that's your ultimate goal, to actually create an experience. And perhaps digital, perhaps physical depends how the business models evolve, but something that feels personalised. And a colleague of mine wants to use the phrase kind of cool, not creepy when it comes to personalisation. So something that you think that's really valuable to me, and I'm really grateful for that. But you haven't freaked me out. So and I think we're all learning, and I think that's a fascinating area. Actually, and one of the most important things that, you know, all the different market participants need to talk about, not just just the banks, not just the technology providers, but also the regulators, right? Also the investors, also the shareholders like how do we all see that evolving together and how can we do that in a way that always puts the customer first?

Ben [00:13:55] I think that's another really interesting dimension to that as well. When you talk about regulators, the regulatory regimes in different parts of the world are so vastly different, as well as all the relative controls around data. And so is banking, I guess, becomes more and more interconnected as we start travelling again. Now, as banks, I guess, would want to become more interconnected as well as tap into various, you know, trade flows on the corporate side, but also just to allow for payments and things like that in other countries in a more convenient way for customers. And we haven't even mentioned fintechs yet who have spent a decade growing and will all have or many will have global ambitions. How do we address that topic of different regulatory regimes and which one do you follow, do you follow the most stringent? Do you follow the regime country by country? I mean, those are some other significant topics, and I think what you tend to see or what, but I've certainly seen over the last 20 years is that a certain level of innovation is permitted under the watchful eye of the regulators to say, but without too many controls. And as it starts to hit the mainstream, if you like, the regulatory regime gets a little bit more robust and so on and so forth. And my sense is, here that just as we're talking about Victor's banking and data and AI and those sorts of things that the regulators, regardless of which country now, but the regulators in our sights give us some significant attention I’d say.

Emma [00:15:18] One of the things that I always kind of think about is how do we get people to better understand the way that their data is being used? We've obviously got the regulation like GDPR, but how do we get consumers to understand that you've been awesome in talking through some of those really exciting use cases, so I'd like to kind of explore some of that a little bit more just around that. And perhaps you can touch on kind of consumer understanding as well. So, you know, let's just imagine we've got the average customer in the future. What would a normal day look like for that kind of average consumer using a bank of the future? What would that look like?

Georgina [00:15:56] An example might be if you, you know, in the world of ubiquitous banking, if you wake up and you unlock your phone, which sadly is probably the first thing quite a lot of us do. And then, you know, you've got a commute ahead of you. Your train ticket would be purchased automatically for you and now, given a prompt. If this is the best route, this is the best train for you to jump on, or make a commute as efficient as possible. You know, when you get off the train as an example, the Pret is next to you or the Starbucks or whatever it is, you can go and get your coffee on the way to work. And then while you're at work, your bank is thinking about your financial health, you know your financial wealth. And if you have investments there, you've got those being rebalanced through the day. Maybe get a little update prompt through the day, saying, actually, this is your financial position at the moment. This is what's happened in your investment portfolio today. We're on it. We're taking care of it. And maybe if we visualise it's a special day, so visualise it. On someone's birthday or wedding anniversary, you get a little reminder for that as well, and a little function that lets you order a hotel booking. If you're going to go out for a weekend ahead or a dinner, or some flowers for the evening for your partner and then you get home and you've automatically had your favourite meal delivered to your doorstep so it knows what time you're going to get back. There's your meal waiting for you. You can come in and that really, to me, is a description of, you know, sort of hyper intelligent platform that is predicting needs for customer needs and then integrating them and the finance, they're really the probably the best word for it. It's almost invisible. So it's just happening in the flow of your life. It's funding your travel. It's making it simple and easy for you, prompts to make your day easier and the financial side of it is just being taken care of.

Emma [00:17:39] What I'm hearing you say is that you're going to organise for me to have my dinner ready for when I get home. So I like something like that for sure. Another thing that we talk about a lot, and when I listen to that experience, Georgina, you're talking about that experience. Is this idea that this experiences is frictionless and needs to be frictionless? Why are those words kind of synonymous with the future of banking? Is it purely to do with convenience and efficiency or the other things that relate to this frictionless experience?

Georgina [00:18:14] I mean, in terms of frictionless banking, and it is a word that I completely agree that people use a lot. I think historically, when people thought about banking, you know, the mindset was, I need to allocate some time in my day to go and do my banking or sit down and think about my banking. And I mean, my gosh, we've all got far too much to do as it is anyway. So I think the word frictionless has really evolved from trying to take effort out of the flow of people's lives and just saying, actually, you know, if you had to allocate time to think about it and it was taking your energy, taking time out of your day, how do we create an experience that isn't that seamless integrated that actually fundamentally you don't have to worry about, right? You're not thinking about it. I'm not really sure I understand all this stuff. I need to go and deal with it. It's a bit hard, though it's ever really sat me down and explained it to me. And, you know, a really nice, simple example of that and the way that I think frictionless is integrated into many of our lives is, you know, when you open your phone with your face right and use Face ID, and a few years ago, you'd have been like, No, and I was typing my passcode. It's fine, but I completely take that for granted that you just look at your phone, it opens up and you can do the same very often with banking apps. And actually, what that does, which I think is brilliant, is it creates the frictionless piece. So it's simpler and easier, but it's also increasing security. So I think it's a really nice example of marrying, reducing friction and stress, just making something a bit easier, but actually also improving the security for the customer because of the level of security inherent in biometrics. And I think that's something that adds a lot of value to customers and fundamentally helps them and helps reduce risk of fraud. So that would be a simple example I would share of how I think about frictionless vendors. Does that resonate with you or do you have a different example, do you think?

Ben [00:20:04] I think to some extent it's a bit like a hierarchy of needs, if you like, because I used to work in peer to peer lending before, and the notion was always around simple and safe. And I think the third thing for the banks generally would be better value because people still might have the best rate on a savings product to the best rate online. But I think your Monzo example really points to the next incarnation of that, which is those features that actually wow the customer or, you know, you don't expect. Right? You know, can you go back to that today? Sort of basic needs of simple and safe mortgage application can take a week or it can take two weeks and customers just don't want that. So when it starts to get a little bit false that that's where you get that whole, this is very nice and that's the frictionless angle. But it's that kind of next level that we're talking about around innovation, which really gets us into that space of ubiquitous banking, which is which is the wow factor, the two-minute mortgage application in the journey of buying a home and so forth that I think where banking can actually get to eventually.

Emma [00:21:03] So, Georgina, you were talking about biometrics in terms of A.I. innovations that we were using on a day to day basis. If we can segway to A.I. and how that's helping in terms of the frictionless experience, have you got any other ideas of innovations in artificial intelligence that we're already using within banking to help us on a day to day basis?

Georgina [00:21:25] One really great example, actually, which is like across many institutions, but just because we’re on the call with Ben today. So just to take the HSBC example where Ben spent a good proportion of his career, they apply AI within contact centers. And what that does is analyse the conversation with customers to help the person who's speaking to the customer and take the next best action for their customers who have lost customers. But this, you know, how could you consider helping this customer in the best way? But also HSBC use it for training. So actually, understanding what conversations are coming through? So what are people ringing because they need help with? What's the best answer? How does that lead to a great customer experience and they are used to it to run machine learning models on that, that took a week. And actually, when we developed that with them, with some AI technology then they could run that model actually in an hour. So suddenly, the people who are talking to customers, we're getting feedback on that. The best way to possibly do that and do that job within an hour, right? And that's great for customers. But fundamentally, it's really good for the people who are working in the call center, right, because they get to have a much more rewarding job because they're getting great feedback in a much shorter period of time and they can have much better customer conversations. And maybe when you're in the centre, you don't know that's happening, but very often it is actually. And that's that's an artificial intelligence that is wide stream across banking right now. And I think that's a lot of value to both employees and to customers

Emma [00:22:55] Just in terms of like building on that progress since we talked a bit about biometrics and how artificial intelligence is being used. We just talked about, you know, in the call centre. How else and how do we build on this progress? So what areas should companies be prioritising or utilising to advance A.I. within banking? There are other areas that we can talk about that might be interesting for banks to use.

Georgina [00:23:17] I think there's kind of three areas I think about when I think about the application. So the first is customer experience. So early on in the call, we talked a bit about how Monzo does that as an example of BBVA. And that's really about thinking about how to improve your understanding of your customer, how to make their experience personalised. Digitised in the right moment is by, we're saying so in the time you really want that interaction. And I think that is hugely exciting, actually. And there's other elements to that that you can look at in terms of the API links between platforms. How do you create the right infrastructure? Embedded banking, as an example, is something that we're seeing coming through a lot of integrated banking integration experience that's all created and made possible really by API links. Secondary, I think about operational efficiency. So a lot of banks right now we're sitting with cost income ratios that weren't 60, sometimes 70 percent. So how do you help drive efficiency through your business? A really simple example of that is document API. So to bring that to life, if you think about Google Photos, right? If you take a photo of something and you go into Google Photos, you can search for stuff and it effectively, if you said I want lots of my pictures of the Golden Gate Bridge as an example, it will be able to extract that unstructured data and put it into a little set of photos for you to look at. And we can do the same thing with documents. So document extraction effectively allows us to take unstructured data out of different documents and pull it into a structured format. And then you can streamline processes, make them much, much quicker. So as Ben was saying about the mortgage as an example, and we've worked with a number of different customers around the world on this actually and reduced application time and processing time down by very, very significant margins because we're able to just really speed up that document analysis. And the third area is is risk really and actually having AI help with your risk management and within a trading business that can be something like high performance compute. So running your models much quicker, doing deeper Monte-Carlo analysis and some of the risks on your trading book and on a retail and business banking unit that can be something like liquidity reporting or regulatory reporting, how do we how do we help customers pull in the right datasets to run those analysis for the regulators and for their businesses much, much faster, which is good for a company in terms of its overall risk profile. So I would say customer operational efficiency and managing risk.

Ben [00:25:37] I'm going to add one more, which is around in the risk category today around credit risk on the retail side. So the majority of risk decisions are generally based on demographics, with the one exception, which is all you are or are you not a homeowner? When you think of the wealth of your transactional data and the behavioral insights that you can get from that income and the desire to move that segment of one, you can probably get a much clearer impression of the default likelihood of an individual by actually a single database and type of things with it. You know, it's the behaviour characteristics in the transaction data, and I sometimes wonder if you can infer from that general considerations as well, which could also be a factor. Because if you look at the way credit risk kind of scoring is done today, you're sort of extremely low risk and the bank doesn't make much of a margin. And the higher your risk profile, the greater the level of provision that's priced into the loan, but also, generally speaking, the more profitable you are to the bank as well. And you sometimes wonder if therefore, customers are incorrectly priced based on some fairly blunt data analysis. And therefore, if you add the transactional layer and you look at the behavioural characteristics of the individual and can adapt your credit scoring models. I do wonder if sometimes customers can actually end up with a more accurate price that reflects their risk, which is therefore more favourable to them.

Emma [00:27:08] We've got lots of reasons why we should use AI and we should have frictionless experiences. But are there any reasons that you can think of that we should have not so frictionless, or we should have friction in the customer journey? Give some examples of banking. Why should they still exist, Ben?

Ben [00:27:29] You know, you talk about reasonable restrictions that exist, actually I think about gambling. There was a law in the UK, maybe 10 or 15 years ago that said you need to wait 24 hours before signing up before you can actually gamble. And there are certain controls such as that that are actually really, really good the customer. So that removes the impulse to part ways with money, which allows your chance to reflect and so forth. And I think the same could be true. Some investments and other things like that, for example, like taking a significant loan, for example, over the course of a five year period or your mortgage over 25 years. That's a potentially a life changing decision. So some level of friction and control is actually quite important and in the customer's best interest ultimately.

Georgina [00:28:13] Yeah, I think there's examples for better or brilliant and completely spot on. And just as you were talking Ben, I guess the other one I was thinking about was pensions. You know, these are complicated long-term positions for customers to be in. And there are very good reasons that if you're transferring your pension or you're making plans around your pension, you know you get a number of letters through from the different pension bodies to say, Have you thought about this? Have you considered it? Have you modeled that? Have you had advice? And I think that's prudent, you know, in relation to pensions. I think that that is a big decision and it's important to give people as much help as they can actually in consolidating and understanding their pension position. And I think that, you know, situations like that, you know, deserve considered thought. That's the truth. Yeah. And it's not that AI can't help you make that considered thought. They absolutely can. But I think also sometimes what we have to do is give people the tools and then also just give them hints and nudges just to say - this is a really big decision, you know, do you want to take a bit of time to think about it?

Ben [00:29:20] Even in insurance you still have a 14 day cooling off period set in the UK, and I'm sure you know the markets as well. And so I think regulators would tend to agree with this position that any decisions need to certainly be in the customer's best interests. And so therefore, what are the controls that need to happen with that, that cooling off period is something up to the customer or whether it's a slightly longer process with a little bit more paperwork and the need to go and get some advice? Some another way of doing it, but critically important

Emma [00:29:52] You use that terminology cooling off, period. That's what I was thinking of when you were talking. And I think certainly in the world that I come from in security, we're seeing more friction going back into the journeys we're seeing fraud increasing. You know, we kind of see organisations trying to slow, particularly with Payment Services Directive, secure customer authentication where we're starting to see more friction going back into the journey. So we talked about organisations that are doing it really well and they're already ahead of the curve. Are there any ambitious ventures that you've seen that haven't quite got to the next level, but are really close, organisations you kind of go, Yeah, it's interesting, but they're not quite there yet.

Ben [00:30:32] You never actually know how successful they are. And I think that's one thing around the innovation. Say that telephone crime is involved in quite a lot of the innovation that they did there. And so I think I think the real measure to some extent is about the ambition of the company to actually launch something and put that brand on it and really try something to push the industry forwards. There's a great example of this in Emirates NBD in the Middle East, where, yeah, there was a fitness app on your Apple Watch that the more you exercise, the higher your savings rate would be. And I have no idea if that would. Successful or not, but apparently the customer insight was that there was a, you know, a growing sort of wave of weight gain and obesity in the country, and the bank wanted to do something to tap into that human truth. And there's this whole drive to health and wellbeing. And, you know, the Apple Watch came along and so they create this new product. I have no idea if it's successful. Often it's customer sense. They did something about it. They launched into the market, and that's just fantastic. Is OCBC the biggest of the best travel agent in Singapore? I think it's probably really hard to work that out. They've done something about it, which is great. So it pushes the industry forwards, and these are the sorts of organisations that the others talk about and inspire others to try and do things differently. And that, to me, is the value of innovation.

Emma [00:31:50] So today in the podcast, we've covered some really interesting topics around banking, ubiquitous banking, these frictionless experiences and how artificial intelligence is being used to create a better experience for customers. And you know, we think about that in everyday terminology and how we might be using it every day for customers. You know, it's bringing together those everyday transactions, like going on a train that Georgina was talking about and ordering a dinner and even remembering birthdays with banking of the future. And we've had some great examples, you know, Monzo, BBVA and also organisations like Maybank who are based out in Asia and those are really the innovators in this area. We have some great examples. And if you listen to our other podcast [episode], we've got a podcast [episode] specifically on Southeast Asia. And check it out because they're going to be talking about more of what's happening in that region around this area of banking and innovation in the future. And that brings us to the end of this Architects of Change episode brought to you by Mambu. If you'd like to delve more into these topics and read the recent Mambu and GCP report The Bank of the Future, please visit https://new.mambu.com/insights/reports/gcp-bank-of-the-future . I'd like to thank both of my two guests today, Georgina Bulkeley and Ben Snowman. If you'd like to follow more of Georgina's work, please head to https://cloud.google.com . And for more information of Ben's work within https://new.mambu.com/insights . For more Mambu podcasts, head to wherever you usually get your podcasts. And don't forget to subscribe to our channel so you don't miss an episode. I've been your host, Emma Lindley. I'll see you next time.