DBS Group Holdings Ltd (D05) Earnings Call Transcript & Summary

Good morning, everybody. I really appreciate all of you coming here. For some like Nick, he says he stays close to here, sort of the short distance. Some of you had to slip from the other end of the town. We wanted to do it in this facility because it gives us the opportunity to use our demo -- this is our innovation hub. So it gives us the opportunity to use our demo room, et cetera, and showcase some of the things that we want to talk about in the course of the day. I also appreciate that many of you spent most of last week doing investor visits with some of our competitors. And a few of you actually stayed on over the weekend. So thank you for that. So my job here, I'm going to spend the next 30, 40 minutes. I'm going to do a bit of an executive summary of the things we're talking about. But also I'm going to use this to tee up the agenda for the day, the various speakers. Basically, I'm going to focus on what you should expect to get and take away from each of the presentations that are going to follow through the course of the day. But before I get into that, I thought it might be useful to actually start from here, which is our investment thesis, why we think you should as investors be interested in owning DBS. And I'll start with the extreme left. When 2009, 2010, when we first started and when I first joined the company, we spent some time trying to think about what could we create, which is a differentiated investment proposition for investors. And we decided that essentially, there's a real opportunity for a bank to offer a different way to play Asia. And the different way was effectively this. One, we would not focus on a subregion. We would not be just an Asian Bank or a North Asia bank, and that's what most banks are focused on at that time. We would try to play across the 3 major subregions. We do on North Asia, Southeast Asia, but also subcontinent. So we connect the major flows across the region. We also decided that while we would build a network of connectivity, we would go deep in the big markets. So we would not actually try to do multiple countries. I do a belief and still continues to be that if you're inch deep, mile wide, it's very hard to build scale of relevance. So our premise was that if we took the 4 biggest countries in Asia, ex-Korea, Japan, so China, India, Indonesia, Taiwan, and tried to go deep in those countries, we could actually differentiate ourselves from a lot of the global banks. If you could do this, this will give us 2 or 3 big advantages. One, we have different from the globals, because in the big markets, we go deeper, we'll be different from the locals because we would be able to do the connectivity trade, the trade investment flows around the region. Anchored in Singapore, Hong Kong, that's about 60% to 70% of the business that will give us stable anchor and the 2 big financial hubs, both AAA countries. And the presence in China, India, Indonesia would allow us to gain diversification. And frankly, that would have been useful. If you look at China in the first half of the last decade, the banks were booming. The last 2 years, the banks have got hammered. And the story has been the reverse for the country. So the notion was because emerging markets go through cycles and sometimes the cycles are not aligned. This would allow somebody to get a diversified access to Asia for that. Sometimes get asked, why would we not just buy banks in each country. Well, the reason for that is that you get diversification when you go through a focused region to play as opposed to making bets in individual markets. So that was the thesis basically. In the 2013, '14 period, when we got this epiphany about leveraging technology and digital, we figured that we could really leverage technology to add a differentiated competitive advantage that to supplement that issue. It's not a pivot, but add on to the Asia positioning. And that is really this that if you focused hard and tried to learn from what tech companies do, understood the model of tech companies, how they acquire customers, how they transact with our paper, how they do things instantly, how they use data. You could wind up creating a financial outperformance. So that was the overlay on top of the Asia piece. And then more recently in the last 3, 4 years, has been quite evident to a lot of people, including to us, that the sustainability agenda apart from being good for the planet is going to be a massive trillion dollar income opportunity. And therefore, if you can get on to this early, learn how to figure the sustainability opportunity solutions, et cetera, you could wind up distinguishing ourself. And Asia is going to be a big part of the sustainability play. So the banks which are able to do this well and do this early, should be able to add incremental value from that. So that's basically the notion that if you invest in DBS, it gives you a diversified access to Asia, gives you deep access to the big growth countries, gives you a technology play, which gives you some lift. And then hopefully, can leverage the sustainability agenda. So what I'm going to do, the bulk of today is down the middle piece. So this is why it is called Digital Transformation 2.0. It's really around why we think our technology and what we do gives us a distinction. But I'm going to double-click on the left and the right upfront for a couple of minutes because obviously some questions around Asia and so on and so forth. So we start with this diversified access to Asia's growth. And this question comes up often. I mean is this still valid? Is Asia still the place to be? And is the investment proposition still valid? So I thought 3 points are interesting and useful to make. One is that people ask is still the Asian Century are not the Asian Century. And you've heard enough about this in the last week from our competitors. I'm on the same camp and I think the structural drivers of Asia's long-term growth are intact. Slow Asia still grow circa 5%. China, this year will do 4.5%, 5%, India will do 5%, 6%, Indonesia irrespective of every year, does plus/minus 5%, Thailand as well. So I think Asia's secular growth in the 5% range is still very much intact. The export engines sometimes go down, but consumption demand is picking up. And this notion of an integrating Asia, trade and capital flows in Asia are still pretty much intact. Asia's consumption today as saw the 2020 data -- it's about 0.96 for every dollar that you see in the U.S., which is not bad. And if you look at the fast forward projections in the next decade, Asian consumption is going to outstep U.S. consumption. So the mega trends that drive Asia, the structural area of opportunity and promise, I don't think those are taken away. The second big thing is the large Asian markets. We still have the view that our premise that if you go and build in the big China, India, Indonesia, Taiwan, the opportunity is still intact. If you look at the growth rates of the banks in India, the banks in Indonesia, those are solid. The Chinese banks have been slow, but certainly in pockets. We think that growth is there, it's not going to disappear. So one of the things that we've done as an example in the last through COVID, we took the opportunity to actually double down on these big markets. So we did the LVB acquisition in India and has given us a large-scale footprint, we're going to talk about that as Surojit talking later about the India opportunity. But we've now got the platform and the scale to really grow in India. We bought Citi's business in Taiwan and that makes us by far the largest foreign bank in the country. And while we won't have the same returns profile as in India or Indonesia, we think we will generate a decent return and scale out of the Taiwan market. We built a position in Shenzhen Rural Commercial Bank. It's a minority position, but we know we have the opportunity to increase that stake over the next 2, 3, 4 years. And we're going to use that to continue to anchor greater the area. So again, not dissimilar to many of our competitors, but we will have a platform to be able to anchor and grow that at scale. So this notion that the big Asian markets still offer significant upside and the cards that we have been able to play over the last 3, 4 years allow us to be able to leverage that. I think it's an important point to keep in the back of your mind. And finally, the geopolitical question. So what happens if there's a complete trip, there's an unbundling, decoupling, et cetera. Now again, my best case, which is what we as a company are base lining everything on is that a complete unbundling is very hard. China is just the biggest trade partner for 68 countries, is too deeply integrated into global supply chains into global consumption patterns is the biggest market in many ways. So unlike the Russia situation of cold war, where you could draw an iron wall, we think that's very hard to do. You'll find pockets, semiconductors, you might find an activity, which people try to bifurcate, but fundamentally, not easy to bifurcate. And actually, we look at the G7 announcements in the last couple of days, we don't want [ Otaki ] or we just want resilience and diversification. And Biden's comments last evening, about how we're being to see approachment and warming up in Thai and so on. I think you'll see noise. It will keep going up and down, but we don't see an unbundling entirely. We do think that you'll have to be nimble because it will create tensions, and you will have a multipolar world and people will form alliances and partners for different issues at different points in time. But ironically, this is helpful for Singapore and it's helpful for banks like ours. So we are beneficiaries of this thing for reliance, for diversification reliance. So the China plus one, I don't see anybody pulling investment out of China, but I do see people making the marginal investment in some way in place. Thailand for autos, Penang for electronics, some in Indonesia, some in India. We're seeing a lot of that. Most of it, 90% plus from what I can see, maybe 100% is still in the region. So the friendshoring, nearshoring other than semiconductor, I'm not seeing too much of it going back to the U.S., Mexico, maybe some will happen. But the fact that it's in the region helps us as a country and has DBS. And we've seen that in the flows, both the corporate flows. So companies, Chinese companies, American companies, Western companies, still look at Singapore as a place to domicile for the regional treasury centers for the trade centers, trading hubs. And that's true for private flows as well. And again, we've all seen in the last year, the spate of private flows that have come into the country from all directions. So like I said, in an interesting kind of way, I think we are beneficiaries of some of the tensions. So net debt, I'm not going to do more of this, but like I said, you heard enough about this last week. But I'm basically in the same camp. I think the Asia story exists. It is consistent. I think the way we're trying to play Asia is still a smart way to play it. And I think, actually, we will be beneficiaries of some of these events in the short, medium term. So a quick double-click on the sustainability agenda. That's very early. So I have to be clear about that. But if you look at the McKinsey report, right, the one recently, they said effectively that the sustainability-linked opportunity is about $100 billion a year of the banking revenue pools for this decade, of which Asia is about $30 billion. And I think that's about right. We sort of did back of the envelope. We can see those opportunities as well. So what we've done in the last couple of years is that we've actually been ahead of the game in terms of defining these transition pathways for the big sectors and industries aligned to all the global standards, et cetera. But we've been able to figure out how we get from high carbon intensive sector and make the sector less carbon intensive. So how you go from down to light brown to light green to green. And we've created a lot of solutions to help in that process. So how do you get people to improve. So we believe that the capacity and capability we have to help in this transition process should allow us to put some runs on the board. As a case in point, so as you know, one of the things that the world is looking at right now, the [ Japenese ] partnerships. So is it okay to invest in coal if you can accelerate the shutdown of the coal investment you make and the South African started it. There's some discussions going on in that regard with in Indonesia, Vietnam, et cetera. Now we advise us to [indiscernible] up the sovereign wealth fund Indonesia to think about this, how do you actually work to exiting some of the assets earlier than you would and we can do that because we build capabilities to be able to create solution sets of that sort. Our sustainability linked revenues have been moving quite sharply. So we made about a small $75 million 2 years ago that doubled in '21, that doubled again in '22. So we had about $300 million last year. We have a total originations of north of $60 billion. We did about $25 billion in fixed income. We have a book size of another $30 billion. So I think the revenue pools are there and our ability to be able to track those revenue pools are there. But I'd be the first to say, over the next 8, 10 years, what happens on time is clear. I think we're positioned well. So let me get to the heart of what we really want to talk about today, which is this financial performance driven by digital transformation. And before I dive into that in the agenda, I thought it would be appropriate to address the technology issues we've had in recent times. Our Board and actually all of us, at management, we take these issues very seriously. And so the way we've dealt with it is we've got a Special Board committee, which is running an investigation into our entire technology processes. We've got external independent advisers who are helping to review the entire technology process and what we have. And we will be submitting a report to MAS when the entire investigation process is complete. Whatever comes out of that, if the gaps or the areas of improvement and we're committed to investing what it takes to make those improvements and to address those gaps. I know a lot of you would like to get more details about this at this point in time. But very happy to discuss this at the appropriate time. That will only be when the review is completed. When we've been able to get the end-to-end pieces. And it would be inappropriate to try and discuss in piece at this point in time. And so we're not going to do that. As and when the report gets done in the next few weeks, then we're happy to come back and talk to people about what we've learned through that process. But on the financial outperformance and the digital transformation. So let me take you through a deeper dive on some of these things. Firstly, this idea of financial outperformance. If you look at -- this is end December '22, the top 100 banks in the world by asset size. On the extreme left, our top line has grown at about 6%, and that puts us in the top 20 of those 100 banks, trying to remember probably #16 or something in terms of top line growth. If you look at the profits in this period of time, but I've gone back to 2015 because that's when we started our digital transformation journey. And there's the only chart where benchmark into 2015. If you look at the profits, we've grown 9% and that again puts us in the top 20 of these banks around the world. But if you look at our return on equity, and that's really material, we're actually in the top 10 banks in terms of improvement in ROE in the last 7, 8 years in terms of outperformance. Actually, for last year, we were #8 in the world in terms of ROE, of course you saw the first quarter of this year, our ROE was north of 18%, 18.5%. Now expect some of this outperformance is cyclical. We are beneficiaries of the interest rate environment and the credit cycle. But we think that there's some structural stuff going on here as well because the cyclical factors impacted the whole industry. So the whole industry saw an improvement in returns. And therefore, the fact that our position has gone up from #44 to #8 means there's something more than cyclical going on over here. So the first presentation after me is actually Sok Hui, the CFO, and she is actually going to try and unpeel some of the stuff. So we're going to try and unpeel where we think the structural, secular improvement in our returns is coming from. How you can actually get some line of sight and see the bread crumbs and she will actually then go on and try and give some sense for what is the medium-term outlook. So where we think this is going and what we can expect to see. So that's the first presentation after mine. Sok Hui will basically focus on both the financial outperformance, but also the outlook of what we hope to be able to see. Then after Sok Hui, the rest of the day is architected into 2 big sets of presentations. So on the left, these presentations refer to what I think of the enablers, right? So we'll talk a little bit about what we've continued to do in the last 6, 7 years to create the sustainable advantage with technology. So we're going to have Jimmy is going to talk a little bit about. I have slides on each of these, so I'm going to follow up. The second big thing is we really think that what we've done in the last year has changed the way we work. And again, I've a slide to tell you about it. What this -- the method of working, including a lot more use things like AI, et cetera, is really important. So that's the second key enabler we're going to talk about. And the third, we're going to talk about is our credit process. So we've also upgraded and redefined the way we run credit, again, use of data, et cetera. So these are the 3 enablers. Basically, the way we manage is fundamentally different. Now it's important to understand this because you think about up till COVID I think competitive differentiation technology just came from digitizing better, right? And so being able to change a tech stack, digitizing, et cetera. through COVID, there's a lot of catch up. Almost everybody had to cater to working from home and consumer markets and so on. I still believe that we are competitively different in terms of the range and comprehensiveness of our digital capabilities. But I also believe that as you go forward, the real differentiator is in this. How can you use data, how do you create systems? How do you manage differently, et cetera. And so it's worth spending some time being able to explain that to all of you. And then after that, we have 5 presentations, which are on the right, which really focus more on specific business outcomes. The first of these is the consumer and SME business that we showcased 6 years ago in 2017, the Singapore and Hong Kong business. So we will show and demonstrate how we've continued to make progress in that business, how we've been able to achieve what we thought we could and where we are. This is interesting, obviously, with all of the new banks in Singapore and et cetera. So it will give you a good sense for how we're positioned, where we're going. The next 3 are businesses we did not cover in the past because in the past, our focus was consumer retail. In the last 6, 7 years, we've taken this whole digital capability to large regional businesses, private bank, transaction banking and the T&M business, in particular. So we will showcase for each of the businesses, what we've been able to do over this period of time as well as some sense of, therefore, how big is big, where do we go with this? And finally, we have also in this period of time being able to use the capability to start scaling in some of those growth markets we talked about. And we're going to do a use case, a showcase of India because, again, people have had questions about post LVB what is India looking like. So we'll take only one. We didn't have time to cover loss. We'll cover the India piece of the story in there. So that's the second set of presentations is going to be around the outcomes related to some of these businesses. So let me take, like I said, the sneak preview on each of these. On the technology thing, there are 5 things that Jimmy, CIO, was going to talk to, things that we've done. One is the use of cloud. We -- I think we mentioned in the last time that we've actually built a virtual private cloud, which is world-class. It continues to be world class in many capabilities in terms of cost points, scale, et cetera. But in the last few years, we've been able to create a Hybrid Cloud capability between a good match between the private cloud and leveraging the use of public cloud. So Jimmy will talk a little bit about that. When you talk about data and what we've done with data, and this is probably the single most important thing we've done over this period of time. I'm personally convinced that the future is around, forget ChatGPT, irrespective the future is around deleveraging and user data for AI. But the click to that and the biggest moat in this game is the data. So how do you actually get the data so we can actually constructively use AI at scale with this? It's taken us 6, 7 years to be able to do that, ingest our data and create the appropriate data infrastructure and architecture. So Jimmy will talk a little bit about that. APIs. Again, in 2017, we already started talking about application program interfaces, a different way to plug and play, both with the external world and with our internal pieces. We've continued to build on that. So the API infrastructure and architecture, which allows us to plug and play, this is really important if you want to build ecosystems and partnerships. We'll talk about that. We'll talk about how we continue to mature our Site-Reliability Engineering practices. And then we talk a little bit about the experimentation thing that we have, use of blockchain, use of other kinds of capabilities. After Jimmy, the next one I'm going to -- this thing is we'll have Kwee Juan who joined actually till last month, used to head up our strategy and planning functions. So a lot of these things in the transformation office. And in the last month, we moved and is now the country manager for Singapore. But he will talk fundamentally about 3 big capabilities and ways of managing that we have built over the last 6, 7 years. So the first is how do you manage horizontally? And people call it agile at scale and where some of you went and saw the Trust Bank walk around last week as well. If you think about most tech companies and the way they manage, they all manage horizontally. And the problem is that most legacy companies like us are organized vertically. You will have HR, you will have marketing, you'll have finance, et cetera, but workflow is horizontally. And in reality, I mean, these organizations have known this for a long period of time, that organizing work vertically is done because it's efficient. Max Weber came up with the paramedical hierarchy 150 years ago with middle management and separate specialization of work. That was appropriate for Henry Ford assembly line. Over time, companies have tried to switch that to follow the actual flow of work. It's been hard to do you get more effective outcomes, but you can't scale. It's not efficient. The tech company started doing this 20 years ago, figuring that you can actually organize work horizontally now because technology lets you do it very differently. And so they brought agile practices first to tech development. But then eventually, they brought agile practices to other pieces and everything in the company. ING, as you know, was famous, I haven't tried to do this now 10, 15 years away, 8, 10 years ago, trying to create this, and they had some success. The problem is that most legacy companies, which have tried to do this, have failed. Many of them have failed because it's not easy to convert a company from vertical to horizontal management. We think we have succeeded. Today, 60% of the company is running through journeys and running a horizontal. So the first thing, Kwee Juan is going to talk a little bit about what we've done, how we do it and why we think that we've been able to create or we are managing, which is somewhat different, the concept of agile. The second thing he's going to talk about is how we've been able to industrialize AI. I told the AI is going to be super critical. Half the battle in AI is the data, maybe 60%, getting the data right, and I said we'll talk about that. It's not easy to do. It's taken us many years. But the other big chunk of the battle in AI is not the modeling. In fact, with ChatGPT has become even easier, but even the modeling is important, but the real trick is institutionalizing. How do you get AI into the operating rhythm of the company? So your people at the front doing the journey is all adequately equipped to start using AI in the day-to-day business look. So it's not centrally driven, but federated democrat driven. So he's going to talk a little bit about how we've tried to industrialize AI to get broad-based outcomes. In fact, there's one thing you'll see and we'll go around later across this thing. The one thing that you'll probably pick away is the amount of AI we are now using across everything in the company. The third thing that Kwee Juan will talk to you about is ecosystem. So one of the other changes that we've successfully done in this period of time is been able to leverage partnerships and ecosystems for a lot of our origination, underwriting, creating product value proposition, et cetera. Obviously, there's architectured again of the technology we have in APIs, but there's been a real shift in how we go and approach market in many products and in many countries. So Kwee Juan is going to cover all of that. The third piece and the enablers, Kian Thiong, who is our CRO, he will talk briefly about how we've been able to use all of these tools to rethink the way we're doing credit. And in particular, of course, you'll talk about the efficiency we have in the process. But in particular, he'll talk about how we're using data and information to do credit to originate differently. And that's important because this allows us to scale in growth markets and in segments that we found credit thin segments that we found difficult to be able to underwrite in the past. So you'll talk a little bit about how we can do that, how we can underwrite with our ecosystem partners and how it gives us access to new segments and new markets. He will also talk about how we're using the same data and capabilities to do more effective portfolio management, right? So early warning signals, how do we do our stuff at the portfolio level. We believe, and Soh Kian will point this out that our overall management of our credit capabilities is actually showing up in reduced NPLs and reduced provisioning levels relative to the market. So Kian Thiong will show you a little bit about what we do and how it's beginning to make a difference. Moving on to the right side, the outcome. So like I said, there are five presentations, we're going to start with the consumer and SME in Singapore, Hong Kong. Tse Koon, who ran Singapore until a month ago, he's now Head of Consumer and Private Bank. He will take this and I think we'll do a deeper dive into Singapore, but the numbers on top relate to the whole consumer and SME. So he'll demonstrate, we continue to get solid growth. So this one, again, from the time we started digitizing we've got solid growth in income, our cost income ratios have improved. Our return on equity is up. Again, some of it is flattered by rates. But even if you ex out the rates, about half of the difference is structural, half of the difference is rates. So he'll be able to demonstrate that. And he will focus on these half a dozen things that we've been able to do. One, when we met 6 years ago, about 30% -- 33% of our customers have been converted to digital. And we said then that over the next few years, we expect this to get to 50% to 60% digital. We've actually converted 60% of our customers to digital, which means 3/4 of the activity with the bank now happens digitally. So we've been able to do that. We've been able to close most of our last-mile gaps. So even what we had the last time and the COVID had, essentially let everybody do everything from home. But what that means is that we think we have the most comprehensive digital solution in the country today, [indiscernible] we're looking into everything, digitally on this thing. We think that's important because there are no specific things that you still need to. I can do payments, but I can't do mortgage. We pretty much cover everything. We further rationalized our distribution. So our brand system and our cost of distribution has got rationalized further in the last 5, 6 years, you're going to talk a bit about that. We broadened our product range. What -- in the last 6 years we've been able to do is because of digital, they can create some product capabilities, which are really important game changers and pump that into the retail mass market, democratizing of wealth is one, he is going to talk about that. We made digital marketing more effective. So use of AI and mergers to be able to get better outcomes for our digital marketing. And finally, gain access to new segments. So for example, we weren't a big player in the micro SME unsecured segment in the past. Because of the digital capability, we've been able to get into segments like that. So Tse Koon is going to give you a sense for all the things we've done, which have continued to drive dominant market shares in the Singapore market, actually increasing market shares. Then private bank. So we'll have Joseph Poon come and talk about private bank. In Private Bank, the big question is always at the high end, ultra-high net worth, mid-tier, does digitization actually help. And as Joe will show, we've continued to scale our private bank really well. We are today a top 4 private bank in Asia. Our AUMs over the last -- this thing have grown at 9%. The market is grown at [ 3%]. So our AUM growth has been much, much faster than the market. Our income growth has been solid from $1 billion to $1.7 billion. Our cost income ratio of 46% is world class. I don't know most private banks who've got a cost income ratio in the sub-50 rate. We are in 46% range, and our ROE is at 30%. So it's a very solid, high-performing business. But what Joseph will showed to you is the value proposition, the model that we've created, which we call phygital. At the high end of the market, you still need the RM. But how do you couple that RM with digital capability? How do you inform the RM? And how do you take the digital capability and also make it available for self-execution and set direction to the customer. We've been able to stitch that end-to-end together really well. And one of the easy ways to think about that is our return on AUM is about 1%, right? And he will show you how it's much higher than the return on AUM everybody yes. We think that the way we manage the client and bring it together, we get much better outcomes from doing that. After private bank, the next bit that we'll talk about is transaction banking. Transaction banking, again, we really scaled. The business has gone from $1.9 billion to -- in 2017 and when we showed you last, to $3.3 billion. Cost-to-income ratio is low at 32% also coming down. ROE is up, again, like the earlier thing, about half of this is explained by rates. But half of it is explained by structure and Shu Shan, who's going to do this section, she runs the institutional bank, she will point that out. The 3 things that she will try to make sure you take away 1 that in this period of time, we've really improved market access as the region has gone into real-time instant clearing system. We have plugged them be able to become a member of most of these elements. So a direct member of CIPS in China, we are member of UPI in India. So we've been able to get market access across the region. And we've been able to create capacity. So one of the big shifts in transaction banking is high volume, low value, right? And so the volume considerations are very, very different from what they were 5, 7, 8 years ago. So we've been able to get the capacity to be able to do high volume and very low latency. Now that means that we can capitalize on these 2 mega shifts, which are happening. One, more and more of commerce is moving online. And when commerce moves online, the way you do your transactional banking, your collections, payments receivables, it all changes. It changes because you don't have -- you can't batch and aggregate. Earlier, your sales person went. He went to the shops and collected a lot of checks, but you gave the bank one single transaction to do, which is all the sales proceeds for the day you hand it to the bank one. In a real-time world, you have to deal with every transaction in your time. So you've got to change the whole orientation for how you run this. Similarly, supply chain shifts. COVID have -- but even before that, the supply chains are changing quite fundamentally in the way they operate, much bigger use of things like platform, much bigger use. So Shu Shan will point out how the technology and capabilities we have, have been able to leverage on this disruption in the way transaction banking capabilities are needed and given us some reasons to be able to scale what we have. And the last thing, we'll talk about is Treasury & Markets. So Treasury & Markets, again, you can see we've had very stellar outcomes. You've grown from $1.9 billion to $2.7 billion in income. Our cost income ratio has come down. Our return on equity is -- by the way, this is not just the trading income. This includes trading and sales, to some of this is a duplication from the earlier slide. But overall, we're getting a 14% ROE in the markets business. In some ways, I think in this area, we've actually just played catch up with what some of the big banks in the U.S. had. But relative to Asia and the Asian banks, I think we've created a capability which is quite differentiated. So Andrew will talk about this, have we been able to create pricing engines, so we can price and structure at speed, how we've been able to get electronic distribution. So both internally, externally or our distribution or happens electronically. And how we've been able to create trading efficiency, including the risk warehousing that we do, right? And so Andrew will cover this piece. Actually, the one key takeaway, which I think Sok Hui will point out, if you look at these 3 businesses, the translational business, the private banking business, the T&M sales business, in particular, these are all capital-light businesses and high return businesses. And if you look at the relative share, therefore, these businesses and the mix of DBS, this has been increasing. And we think that this is a phenomenon that we will continue to see in coming years. After the 3 business lines, back, you want to talk a little bit about India. So if you look at India, we think we finally cracked the puzzle and started getting scale. Our income between 2017 and '22, we did about $550 million last year. Our cost income ratio has started to come down 78%. But most importantly, from a loss-making franchise has now started making money. Now 5% is not great ROE. But the switch from a negative to positive ROEs material and we think the outcomes as we go forward into this thing is that we've got the trajectory right. So Surojit, who runs our India business, will talk about some of these things. We talked about our expanded franchise. How again, bringing phygital has turned out to be the best way to play this game. So we migrated from pure digital to physical presence. What we have now is a full-service platform. So we can do everything that a Kotak or HDFC, any local bank in India can do. We have a complete platform, which lets us do everything like them. And how we're leveraging digital capabilities and ecosystem partnerships to really grow in the high-return segments, consumer and SME. As you know, our India franchise was typically a large corporate franchise, which is a lower return franchise. The big returns on consumer SME and we're beginning to see traction and grow and therefore, the better return part of the country. So Surojit will cover that. So like I said, an update on consumer SME is Singapore focus, the 3 big regional businesses and 1 case study of the India opportunity. So to bring it back, the overview is my section. Sok Hui will do the group financials after that. I'm going to come back and then for some closing remarks. The enablers, the technology capabilities, the new way of working credit risk management. and then the stuff at the bottom. Now as you noticed, I've got some italics in there. The italics in there represent 5 showcases that we have around the room. So we're going to have 1 showcase on how we use data and AI, which is over there. We have a showcase on how we're using workflow and work engines to drive this horizontal working. We think that that's the route of being able to get it, right? So we showcase on that. We were focused on how we've been able to use Singapore open banking to democratize wealth solutions, which is what's giving us this big thrust in the retail segment, wealth segment in Singapore. So we are showcased on that side. We're going to showcase on how we rethought transaction banking to help companies transform for this e-commerce and new world. So we will showcase on that. And then finally, we showcase behind the corner on how we have used the data and AI to reimagine how we do treasury markets. These are the 5 show cases. Now I think [ Merna ] is going to come and give you some instructions later on the showcasing the 5 of them. Each of you have a badge, which is color coded. And basically, depending on your color, you're going to go into a different showcase. Each showcase is about 8, 10 minutes. So its useful if you go there because then you can hear the full story as opposed to it, and different and [ Merna ] will give more specific instructions around that. At the end of all of the presentations and in the afternoon, we'll leave button on for Q&A where a few of us will get up on stage and happy to answer any questions that you might have. That's what I have to tee off to you. Hopefully get a good sense for what we think we've done, why we think we are different and what you expect to see and take away from each of the sessions in the course of the day.

Good morning, everyone. I'm Chng Sok Hui, Group CFO. Earlier this month, we announced our first quarter results. Net profit, $2.6 billion; ROE, 18.6% and we gave guidance for the full year with profits to hit $10 billion and ROE to be above 17%. But I know you are looking past 2023. As you calibrate your valuation models, I hope to help you build some convictions around the following questions. To what extent has DBS outperformance been the result of a higher interest rate environment and a more benign credit cycle. To what extent the structural factors play a role in growing our ROE what might be the medium-term outlook ROE in a more challenged interest rate environment? And what are the opportunities and drivers for future growth. You have heard Piyush unveil our investment thesis. My colleagues will provide proof points of how our digital capabilities, our new way of working via managing through journeys, leveraging data, artificial intelligence, ecosystem partnerships and the momentum in our growth markets will help us drive the medium-term ROE from -- to the range of 15% to 17%. This chart shows you that our successful digital transformation since 2015 has led to a higher ROE and better shareholder returns. The top chart shows you the ranking of the top 100 banks by asset size. DBS has leapfrog the position from 44th position in 2015 to the eighth position. We are among the top 10 today in terms of ROE. If you -- and you might be wondering, so where do you place the best U.S. bank or the best European bank. In 2022, we delivered ROE of about 14%, which places them in the mid-teens. Turning to the bottom part of the chart, that is where you see total shareholder returns since 2015. And you see that DBS has delivered 16% annualized TSR, which places us fourth place among our global peers. What does this mean in concrete terms, it means that you invested $1 in the DBS stock in 2015, will be up almost 3x, 2.8x, to be exact in 2022. This annualized shareholder return is formidable. And I hope you're all shareholders -- happy shareholders, and you have invested from the investment returns that DBS provided in the last few years. The transformation has not only helped us to leap from our global peers. The transformation has helped to widen our structural ROE advantage. In this chart, you'll see DBS ROE profile from 2015 to 2022. We show on the same chart, our Singapore peer average only for the reason that we operate in very similar markets and have the same -- and face the same macro environment. You'll see from this chart that our ROE has been widening since 2017 and that we are currently at 3 to 4 percentage ROE higher than our average peers. And this has happened during a period where actually fed fund rates have been cut to almost 0 in 2020 and 2021, which had DBS net interest margin the most and yet we outperform. There is something structural that is happening here. Now this chart shows you where we have improved and what are the drivers for our structural improvement. You see that in 2015, our ROE of 11.2% has been lifted by 3-point percentage point to an ROE of 15%. Structural drivers have contributed to a 2.5 percentage point improvement in our ROE. And I'll go through point by point in the later slides. You will note that financial leverage was a drag of 0.9 percentage points. And that really means that in 2015, our CAR ratio was 12.4% and was 14.6% in 2022. So the 2.2 percentage points of capital buffer was the main reason causing the financial leverage factor, which was a drag on ROE of about 0.9 percentage points. The external drivers you are familiar with, and you have built it into your models. We did benefit from a high interest rate environment, a more benign credit cycle as well as market growth factors. Turning to the structural drivers, which have labeled A, B and C, I will unpeel the subsequent slide how these 3 drivers are quantified. The first driver is really an extending our superior deposit franchise from Sing dollars to foreign currencies and how we have been able to grow our deposits faster and to grow it more cheaply. That lifted ROE by 1.6 percentage points. The second item, which is shown as B is actually the growth in the high ROE businesses. And that would be in wealth management, in transaction services, in treasury sales income, and you see the slide of how we have outperformed and quantified the improvement at 0.6 basis -- 0.6 percentage points. The third factor is new capabilities in credit risk management, which our CRO will talk to, but we have quantified the impact of 2.3 percentage point structural improvement to ROE. The first factor, extending our superior deposit franchise to foreign currency. As you know, deposits are the crown jewel of any financial institution. I would like to make 4 points on this chart of how our digital capabilities have boosted our deposit franchise. The first thing to note is that our Sing dollar deposits market share -- savings market share has actually continued to grow. And today, our market share -- as at April 2023 is 54%. The second point I would make is that our foreign currency deposits has now been deeply entrenched, and we also have a superior deposit franchise. Foreign currency deposits now make up 60% of our total deposits of 522 billion. Foreign currency deposits are growing faster than Sing dollars. Foreign currency deposits growing at 8% CAGR over this period compared to Sing dollar deposits, which grew at 6%. What is even more pleasing is that as a proportion of total foreign currency total deposits, foreign currency, CASA accounts, cash operating accounts which we hear my colleagues talking about, the CASA operating accounts, which are very sticky, that has also grown from 35% in 2015 to 54% in 2022, a lift of 19 percentage points. Not only have we grown our deposits faster, we have grown our deposits more cheaply. You see from this point that our measurement of -- of this, which is used by the industry is deposit beta. And during this period where there's been unprecedented increase in Fed funds rate, we measure how much of increase is actually passed through to customer rates. In the case of DBS, it was 29%. For our local peers, it was 34%. And for the average of the U.S. banks, it was 43%. And again, what is more pleasing is that our CASA, our GTS CASA accounts the deposit beta is actually half the 29% at 15%. So all these drivers, the ability to grow our deposits faster to grow our deposits more cheaply and to deploy them in high-quality liquid assets, which are very capital efficient, actually have led to an ROE impact of 1.6 percentage points. Second structural driver, the growth in high ROE fee income, and here, you see we have listed wealth management, transaction services, cards. We didn't put in the some of the treasury sales income that you see under the other income line, but they have grown at a similar pace only because it's hard to compare and outstrip that component versus peers. You just look at the fee income, it has grown from $2.1 billion in 2015 to $3.5 billion in 2021. That is a CAGR growth of 9%, very impressive growth and it is actually double that of our peers. Of course, in 2022, wealth management income took a dip as customers turned more cautious and you see that even if I measure from 2015 to 2022, the CAGR growth is 5%, which is 3 percentage higher than peers' growth of 2%. So you can see that this structural improvement is how we have used to quantify the 0.6 percentage point lift in ROE. Third structural drivers. The new capabilities in credit risk management that's driving structurally lower allowances. You see from this chart that between 2015 to 2018, our credit cost was actually higher than that of our peers. From 2019 to 2022, our credit cost was about 5 basis points lower than our peers. And that is something that we have also communicated to you in our previous results briefing that with all the investments we have made in more effective credit portfolio management through AI to early warning signals, we have already quantified that there would be structurally lower through the cycle credit card that we can expect, which was also at 5 basis points. So that gives us a lift of 0.3 percentage points in ROE terms. So in total, our superior deposit franchise, being able to grow faster, grow more cheaply, deploy more profitably as well as outperformance in our fee income as well as structurally lower credit costs has led to a 2.5 percentage point structural improvement in our ROE. I'll now turn to the near-term outlook. Our fundamentals are sound. Magazine Global Finance has ranked DBS #1 or #2 in the last 2 years among the world's safest commercial banks. We have also been named Asia's Safest Bank for 14 years in a row from 2009 when it started the ranking until 2022. So I will not go through the metrics that are typical to assure you that we are a very safe bank. High capital adequacy ratio, strong liquidity position, strong asset quality position, and you can see it in our results announcement. What I would like to quickly recap is the base case for 2017 -- 2023, the ROE is likely to be above 17% from a higher net interest margin from fee growth in the high single digits, cost-to-income ratio below 40% and credit cost of around 10 to 15 basis points. That is sort of still below our through-the-cycle credit cost, which we estimate to be more in the 15 to 20 basis points range. And we have done a lot of stress testing given the external environment. We have stressed test our portfolio and our asset quality continues to be very resilient. We have set aside substantial allowance reserves. General provision allowance reserves are now at $3.8 billion, of which $2 billion are in the form of overlays. It means that we have a basic general provision model we have created a lot of stress testing and set a slight $2.2 billion of overlays that can be released in times of stress to buffer the allowance line. Our NPA coverage at very high ratios of 127% that will include collateral at 229%. Our CET1 -- we are still operating at above our guided range of 12.5% to 13.5%, and this capital buffer is expected to increase during the Basel IV transition period. We have ample liquidity to support our business operations even in stress funding conditions. We are not only a safe bank. We are a bank poised for growth, poised for scale in the new businesses that we choose to operate in. This is the guidance that we released this morning that our medium-term ROE will be in the range of 15% to 17%. So you have asked how long is this medium term. You can take it to be around 3 to 5 years. And we intend to operate at a CET1 ratio of 12.5% to 13.5%. With the 2023 ROE at above 17%, you must have built in all these external drivers. Interest rates are expected to be picking or have peaked, and therefore, there will be some downward pressure on NIM. Credit cost is expected to be higher than what we have put in -- in the 2023 of 10 to 15 basis points. The third factor, which some of you may or may not have incorporated into your valuation model is BEPS. There is G20s implementation of tax rules globally and most company -- most countries will begin to put in place a 15% minimum tax rate. Singapore is no exception. And we do have a tax rate that is slightly below 15%, and therefore, there will be some additional tax costs to be funded. If you look at the structural drivers, which I will go through in more detail, the first one is business mix, right? You'll see that we are able to grow the more profitable, low capital, high ROE businesses faster. That is the first driver. The second driver is growth markets. And here, we would show you even in subsequent presentations, of how in each of our growth markets outside Singapore and Hong Kong, in India, Indonesia, China and Taiwan, we expect to benefit from scale which would double our ROE in our growth markets. The third point is capital management. Just as in the previous period, 2015 to 2022, a higher capital ratio led to a 0.9 percentage point drag on ROE because we maintain a capital -- a higher capital ratio during this period. Likewise, as we move towards our guided management operating range of 12.5% to 13.5%, you should expect that there will be some lift to the ROE, and we'll have enough capital headroom to support profitable growth and higher distributions. The first lever, faster growth in capital-light high ROE businesses. You see that this is similar to the chart that Piyush showed you earlier in the 3 main lines of wealth management, global transaction services and treasury and markets income. In 2015, there were about 39% of group income rising to 42% in 2017 and 47% in 2022. We expect this business mix to continue to improve going forward and to exceed 50%. Second lever, increasing scale in growth markets. Just again, to repeat, in this chart, we show you the growth market outside of Singapore and Hong Kong. It will be India, Indonesia, China and Taiwan. Look at the opportunities in these countries, which you can see on this chart, in the business lines that you know we are pursuing they have extremely high CAGR growth. In transaction banking, in wealth management, in SME lending, the CAGR growth for the entire industry in these 4 markets averaging 7.5%. In unsecured retail lending, the CAGR growth is almost 10%, but we are only capturing a very small sliver of the potential banking revenue in these sectors for these countries. And therefore, we have the opportunity to scale and to grow much faster than implied by the CAGR growth you saw on this chart. So Surojit will show you how we are using our differentiated business model to deliver the scale we need for India. Piyush just showed you that India has already transformed with an ROE of minus -- from negative to a positive 5%. The business models that not only India but also the other countries will be adopting or have already been adopting to drive scale in 3 main areas. In digital ecosystem, Surojit will explain to you how our ecosystem partnerships in -- with different partners in unsecured lending, in go-loans, in co-branded credit cards will have actually led to an increase in customer acquisition. The other point to note is it is not easy to acquire these customers and originate at scale if we do not have the credit infrastructure in place. So the second factor is that we have already developed these models. The artificial intelligence, the machine learning models that our CRO will explain to you later. And that allows us not only to originate but also to originate at scale, comfortable with our risk appetite and to our own standards of effective portfolio management. The third point I would make is that we are building local depth in -- via our phygital model. Piyush has talked to you about LV Bank. We have understood how digital capabilities can be married with enhanced network to drive growth. We have already seen it in India. Taiwan consumer bank will benefit from City acquisition, which will be completed in the third quarter of this year. In the Greater Bay Area, we have an association with Shenzhen Rural Commercial bank and in collaboration with Shenzhen Rural Commercial Bank, we also see the opportunity to build local depth via this phygital model. So in all, the growth market, we believe, will lead to net profit tripling in the next few years and ROE to double to the medium term. And this is understandable given that in these markets, the ROE today are still subpar and have plenty of opportunities to actually grow to at least meet our cost of equity. We are already seeing results. The customer data in 2015 was 6 million. We had 6 million customers in 2015, and that has grown to 12 million in 2022. Third lever, capital headroom to support profitable growth and higher distributions at the AGM in March this year. Shareholders approved a special dividend of $0.50 and also an increase in the fourth quarter dividend of $0.06 from $0.36 to $0.42. So this brings the total 2023 dividend per share to $1.68. Our baseline planning assumption is that barring unforeseen circumstances, we should be able to continue to step up the dividend payout by at least $0.24 per year, and that's sustainable in the medium term, given our ROE trajectory. We also believe there would still be further upside of, say, $3 billion, that we would be able to distribute because we will still be operating in a range that is above the 12.5% to 13.5%. The distribution could be in a further step-up of more than the $0.24 in ordinary dividends or special dividends or buybacks to feature more regularly or more prominently. The pace will depend on the business conditions and the macroeconomic outlook. So to recap, I'm sure many of you and have read your analyst report that you have factored in the external drivers into DBS' ROE projections. I hope that you would also be convinced that these 3 levers that I have just laid out for you in terms of faster growth in capital-light high ROE businesses, higher ROE with scale in our growth markets and the capital headroom to support profitable growth and higher distributions will enable us to deliver ROE of 15% to 17% in the medium term. We have proven that we are able to deliver with digital transformation 1.0, which we unveiled 6 years ago. We have done it. And with digitalization -- with digital transformation 2.0, we will be able to do it again and to bring DBS to a new level.

Hello. Good morning, everyone. Very good to welcome you here again. You heard earlier on that Piyush mentioned about how we have used digital transmission to drive growth across all the business segments, across all the markets. And you heard from Sok Hui how debt has translated to our financial outcomes. And we believe that a big part of this was really about our technology capabilities. This is one of the key drivers of the entire growth. What we -- well, we also believe is that these technology capabilities have created also give us a sustainable advantage. And why is that so? One, transforming tech capabilities is not easy. It takes time. When we started our whole entire journey of digital transmission, we went down to the valley. And we actually learned from the likes of the tech giants like Google, Amazon, Netflix. And we also found that the digital transmission that makes them the tech giants today takes them about 7 to 10 years. We are in the ninth of our digital transformation, and that gave us a little bit of advantage over the peers that have just started because building technology capabilities takes time. Well, the many key takeaways that we actually have learning from these tech giants. There are quite a number of them. And Piyush mentioned briefly just now, the journey to the cloud, the massive use of data, API-driven architecture, site reliability engineering as well as experimentation with new tech. And what was really important in this one -- data transformation is the talent bench strength that they have. So what we did when we actually learned from all these tech giants, we came back and actually distill all the learnings, and we created this whole thing called Being the D in Gandolf. And you can see the whole acronym. It's actually the tech company's logo. Google, Amazon, Netflix and D is, of course, DBS, Apple, LinkedIn and Facebook. We take all this -- actually take this and run into a big program of transformation since 2015. Let me give you a very quick tour in terms of what we have done since then. Now, digital transmission is really about taking -- turning boulders into pebbles, taking big rigid systems as the likes of IBM, running a monolithic applications. Actually transform them into nimbler modern tech stack using micro services as our API architecture. We have been able to actually progress quite steadily. And today, our whole entire tech stack is about 99% running on cloud optimized. Now the thing is we still have our mainframe. I have things that we virtually get off the mainframe in the next 3 to 4 years. And this has actually translated to benefits for us. Our modern tech has enabled us to scale with agility. You can see our total deployment releases since 2017 to 2022. It actually increased 4x. If you compare ourselves to the leading banks, we are actually slightly ahead. And of course, we're actually closing the gap with our tech partners. So let me actually move on to actually look at one of the key takeaways that we have on the journey to the cloud, like all the technology companies they use massively the public cloud. And we too use a public cloud for advanced capabilities and cutting-edge technologies that they offer. But what is different from them is that we have a hybrid multi-cloud strategy that allow us to actually have on-demand computing power to be able to use on the public cloud. And what we have built in the private cloud, it's an in-house infrastructure as a service that we can achieve efficiency below the price point of AWS. And this is really important. This allows us to actually run persistent workload, as well as storage at a lower cost. And how were we able to achieve that? Well, you're using very simply capitalizing on [ muscle ]. Now when we first started our whole entire building out of VPC, which is our virtual private cloud in 2016, we have a capacity of 250 VMs, virtual machines. Think of VMs as compute power, right? And this is the 250 VMs that we have. Our cost efficiency ratio at the point of time was about $330 per VM, was above the price point of what AWS was quoting. But comes 2 years later, in Gen 1.5, we upgraded our whole entire hardware stack. We doubled the number of VMs to 500. Our cost efficiency has dropped by 1/3 -- to 1/3 -- at $120, below the price point of what AWS is offering. And in 2020, 2 years later, we upgraded our hardware again. And in this time, we actually moved from 500 VMs to 1,000 VMs. And what is really, really amazing is that the price efficiency dropped to $70 and below the price point of AWS, less than half of what AWS is offering. And what does that give us? I think that previously, I think in the previous Investor Day, we talked about having data center downsized by 75% and creating a 10x growth capacity. You look at this growth. And today, this growth continues without having even to incur additional costs on our side. And this cost efficiency is actually very important for us. If you actually look at our tech CIR, It has actually maintained quite constant at 10% over the years. Our operate CIR, which is the productivity that explains us now enable us actually marginally decreased to about 5%. And that allows us to actually put our investment and our money and dollars into the build capability. You actually build more for our -- not only just for site reliability engineering, for cybersecurity, for data and so for our customers. And you can see that in 2017, we -- our expense is about $1.1 billion in 2022, it's $1.6 billion. And the split between operate and build has actually shifted drastically. So coming back to the second key takeaways, data. This one is a more important initiative front. We have built key capabilities in ADA, our data platform. And that allow us to actually ingest data at scale and allow us to actually have instant access to permitted data. Understand data in minutes very, very quickly. And we have on-demand capacity and the state-of-the-art tools. I'm not going to go into details in that because I think later on, you will have a booth that they actually give you deeper explanation of the capabilities of ADA. But I'd like to touch on the few key points. Now, we are able to actually take quite a number of the data warehouses that we have from each of our core systems. And you can imagine with all the core systems in each of the data warehouse, you will have duplicate data. We have many, many data sets sitting in -- across the entire bank. We're able to take that and consolidate them into a single source of truth, into 1 data lake. And it is not easy to actually get data, to clean them, to actually define them in the metadata, to actually look at the data lineage, how data has been transformed and enable quick discoverability. It takes years for many of the banks and our competitors to achieve this. And we did that in the last 5 years. And this is really, really the most that peers talk about. The ability for us to actually get data and enable AI/ML at scale. And what's the other differentiator for our data platform? Now most of the data platforms that you have actually rely primarily on the public cloud. As I mentioned earlier on, our whole entire spectrum of cloud facilities from private to public cloud actually plays with the way that we architect our data platform today. We can see that in our private cloud, we have the data storage as well as our GPU farms, and persistent workload as well as data has been stored there and run there at a lower correspond. But we also make use of the entire capabilities in the public cloud with AWS, Azure as well as Google. We use the models as well as compute and the ability for us to move data from private cloud to the public cloud using one of the tools that we have built, we call Beetle, it's a data orchestration layer. And also built another tool, which is called Arculus, which provide data security across the 2 private cloud as well as the public cloud. Now this is a very unique differentiator. For most of the other banks that you think of, you're actually worried about and concerned about data security. When we actually look at this, the way they have architecture, most of the data actually reside on-prem and brought up to the cloud for us to actually do all this compute and modeling. This is very different from our other competitors. Moving on to API. Well, what really is API about. Well, API is really about taking our core systems, building what we call [ pluck-and-play of hooks ] that enable internal as well as external players to be able to actually use -- and to actually interrogate the core product systems easily. Now over here, as you can see, we have actually exposed a lot of our internal API to external API to actually create ecosystems. I will again not touch on the external API ecosystems which my colleague will actually touch on later. How they use this infrastructure to create the ecosystem play. But enabling that is really our whole entire API marketplace. It's a portal. A portal that allow us to actually publish -- to actually develop and publish and provide the API, to allow people to actually discover what APIs available and then to be able to subscribe and use it. And as you can see, all these have actually translated to actually massive use. Our external API today actually gone up 10x. Our external API volumes has also gone up about 100x. And our internal API volumes has gone up about 20x, massive increase in the use of these APIs to actually assess our core product system. What I'd like to do is actually move on to actually look at how the internal APIs has enabled us to develop our workflow and workbench. Now in the past, when staff come in to work, they have to actually log into multiple systems to get the job done. Today, what we have done is to actually create a workbench that allows the start to have a single sign-on to the particular workbench where the all the work they have to do is actually residing. And how does this workbench perform? It's actually connected to our core banking system through our whole entire API layer. That allows us to have a single point of access from anywhere. And once the work is done, they can actually flow their work seamlessly to another part of the bank, whether it's in credit or operations to be completed. And that by itself gives us the ability to actually create what we call the horizontal organization. And my colleague later will actually showcase to you how that has actually helped in the whole entire manage intrusions. We do have a booth later to actually showcase how this has been done with one of the examples that we have. Moving on to the next key takeaways and capability. It's really about maturing our site reliability engineering. Again, we went out to the valley, learned from the likes of Google, AWS, Netflix. We recruited one of the Google cloud SRE. And we created our own internal SRE framework. As you can see, it's actually very comprehensive. It starts from the way that we architect, the way we build and develop, the way we test, the way we do product launches and the way we operate, the way of observability and the way we handle incidents and so forth. Now this has actually been a key part of our whole entire building -- capability building process. We have actually started building some of these key capabilities within our whole entire organization and give us the foundation for us to actually scale this and embed it within our organization. Next. One of the key thing about all these technology companies is the ability for them to actually experiment and adopt new technologies. We are no different. We started blockchain and smart contract technologies and actually experimented with them, even when the technology was nascent. We have actually built up quite a number of foundational capabilities. We have tokenization as well as wallet management. We have compliance, legal and surveillance and we can operate more efficiently for both public and permissioned chain. And as a result, all these capabilities that we have built over time, we have been able to capture and build new business as when the business opportunities present themselves. In the area of origination as well as issuance. Now we have our Fix marketplace, tokenized digital capital market issuance. For example, trading and execution. We have our Climate Impact Exchange. It's a tokenized carbon trading exchange. And the area of clearing, settlement and custody, we also have our Digital Custody servicing platform. Now there are more of that. The point I've been trying to make is that because we are already playing in these new technologies when they were nascent in building capabilities, when the opportunities presented itself, we were able to actually build all these new technologies to enable these new businesses. Last but not least, I'd like to come back to this. All these capabilities can only be built when you actually have the talent. And today, we have about 12,000 technologies. We have people mainly based in Singapore and Hyderabad. And we are now also looking into China, which we will establish in 2024. We're also hiring from all the big tech companies from the likes of Google, Apple, Huawei, AWS, it is all the tech companies that actually join us because of our whole entire DNA. We also have more technologies than bankers. I also have the breadth of talent and skill sets and all from data and the depth of them in terms of analytics, data technology, to deep tech, the likes of cloud, infra, SRE Engineer, cybersecurity and so forth and as well as in the area of design. And we are also attracting 1,000 young talents from the polytechnics and the universities as well. Today we have a pipeline of our young talents and are coming through this university. So in summary, I've actually gone through quite a number of technology capabilities with you. And it just showcase some of the things that we have done in the past, 8 to 9 years of transformation. But these technology capabilities remain only as technology capabilities. This only becomes real when we actually be able to exploit these technology capabilities by the new way of working.

Good morning, ladies and gentlemen. My name is Kwee Juan. I am responsible for DBS Singapore as a Country Head. Jimmy has just shared our 9-year journey in building these technology capabilities, as you have seen on the screen. I'm excited to share with you 3 new ways of working that leverages on this technology to lift the trajectory of our growth. Managing through journeys is a permanent shift in the way we manage and work within our organization. focusing on customer journey pretty much like how the big tech companies would do it. Second, industrializing and infusing AI/ML across the entire bank. And third, in 2017, we shared with you our ecosystem approach on acquiring, transact and engage at scale. And today, I'm delighted to share with you the progress that we have made and share with you some of the proof points on how this is now very effective for us to launch a different growth that we will see through ecosystem partnership. These are the 3 new ways of working that we will embark on going forward. Managing through journeys, you may wonder and say, what is managing through journeys. In managing through journeys, multifunctional teams come together working as one with one single focus, increasing customer satisfaction with a differentiated customer experience. It is a shift from vertical siloed organization, as Piyush described, to an integrated horizontal organization, all working together with one main ultimate goal of delivering that differentiated customer experience, we believe we have achieved agile at scale with this approach. As MtJ now covers more than 61% of all of our CBG and IBG revenues in DBS. And finally, we are seeing impact of managing through journeys in our operations. It will drive revenue growth and productivity gains. Let me just share with you -- sorry. All of these are enabled and anchored on what you see here on performance cells and how the teams are organized and as well as the Workbench/Workflow or Workflow/Workbench at the heart of the flywheel, which I will explain. These are the secret sauce towards how we organize ourselves and get the impact of revenue growth and productivity gains. Let me start with performance cells and give you an understanding of how these multifunctional teams are organized. Within the performance cells, it is led by 2 co-leads: one, a business lead and the other support unit lead. They come together as a multifunctional team focusing on the original journey -- origination journey, engagement journey or service journey where the team members comprised of product specialties operation or technology specialists as well as bringing in expertise such as design experts or data scientists into the entire multifunctional team to deliver the experience for our customers, and how they will come together for targeting the improvements and what we have is through the performance management architecture, what we call PMA, looking at customer outcomes such as system availability and customer satisfaction, business outcomes and financials and as well as acquisition and many more. And finally, on the employee metrics on how the experience would be from employees, and how they're working in this new environment. Workbench/Workflow or Workflow/Workbench is the heart of MtJ. This is where the magic happens. we will stitch together the work and orchestrate it from end to end from a customer journey perspective and allow the teams to collaborate and work together. This is best illustrated through a video that I will now play. The video, please. [Presentation]

I would encourage all of you to visit the showcase right at the back here to really see the power of how Workflow/Workbench delivers the promise of a better customer experience for our customers. Value map and control tower are the brains of MtJ. And let me share with you on their definitions. When we look at a value map, we often start with the outcome, the customer experience. And in there, we determine what are the drivers that would deliver that differentiated customer experience and what are the different levers that we can pull to make sure that we can deliver that. We believe that a differentiated customer experience we want customers to keep coming back for more, and that results in better financial outcome for ourselves. I'll use an example of the everyday MtJ that we have within the consumer bank in Singapore. These are the control towers that you see online. In everyday banking PC we look at the interaction that we see with customers at the branches, at the call center and digitally. One of the main things that we would like to achieve is to get customers to experience the superior digital experience that we have from all of our services and work to move them from off-line to online. These are the burn-down charts that you see from the branches and call center and digital, down to the branch, down to specific activity, in this case, account opening. We looked at a metric called negative customer impact. The definition of that would be, when a customer goes through digitally, they are dropped off. We saw 40% of our application dropped off, and that is not good. So what we did was the team focus on bringing this down and happy to share with you is now 20% dropped off and has led to a higher number of applications being processed through the bank and the lift on digital adoption for account opening to now 94%. This is the power of how a control tower helps focus the teams to deliver a differentiated customer experience. And now this is the exciting part where I'll share with you on the whole flywheel effect that you will see using these various elements. Through the flywheel, we will be able to generate positive impact through continuous listening, getting insights employing behavioral science techniques and using AI/ML and experimentation to innovate new products. Let's see what they all mean. Continuous learning is a ritual of interviewing customers, determining their experiencing -- experiences with DBS. And second, they are all trained in behavioral science and observation techniques, and we've done more than 346 immersion last year. With the insights that they gain, we will start develop the hypothesis on what we could do to deliver the better customer experience, come out with experiments and then go through the whole cycle of observation, experiments, results to fine-tune the outcome. Here is an example of what we have in transactional FX that focuses on corporate cross-border payment with FX embedded in it and with messages such as, we missed you, on top of a price change actually gives a far better response compared to just pure price changes. What an interesting discovery that we had through experimentation. Satisfaction has also gone up as a result of that. And we have now embedded innovation at scale within the MtJ, where through discovery or pinpoints, we begin to innovate on what we can do with our services and products. This has led to more than 600 new ideas being generated and these are 2 examples that we have launched in the TFX and as well as consumer bank space in Hong Kong. Next up is on AI/ML where we will industrialize AI/ML across the bank. These are the use cases that we have now used right across the entire bank. Everyday Banking and Wealth Management and Consumer Banking and in Institutional Banking, we apply AI/ML in SME lending and as well as early warning for large corporates. This has also been applied into our T&M business, on algo trading and sales, and in audit, we have used AI/ML to enable always on audit and NLPs to generate the audit reports that we have at the end of the audit. Generating that out much earlier than the previous way of doing it. And Kian Tiong will share on how credit risk now is powered by AI/ML on the back of how we do credit valuations and in operations, we use it for demand management, in HR for recruitment and career development and in finance for outlier detection and financial forecasting. These lists are not exhaustive. In actual fact, we have more than 600 models and 300-plus use cases right across the entire bank. And therefore, when we evaluated the economic value from AI/ML, we were very disciplined to look at a control group and compare that to those where we apply AI/ML and determine that we have now gained $178 million of incremental economic benefits, either revenue growth or expense saves in 2022. These are 2 examples that I'm going to go through with you first up on digital payment fraud. As you know, real-time fraud prevention is critical. And to win the war against the scammers, what we have done is we've deployed AI/ML models on the back of it. Looking at more than 300 data features that includes the customers' behavior that we will see when they use their account together with financial and nonfinancial transaction information to enable us to launch an AI/ML model at the back of every transaction that we process. In less than 10 milliseconds, we would be able to determine an outlier in a particular payment that our customers initiate. And this has resulted in a lift of more than 24% of customers save in transactions. And this model is actually far more effective than the rule-based by more than 5x. We've also gained productivity as a result of it and received more than 10x compliments from customers as a result of this change 5 months ago. In CBG, through cognitive banking, we have applied AI/ML right across the entire business. As consumers, you would demand your bank to be able to speak to you as and when you want us to. And through AI/ML models, more than 200-plus of them looking at 16,000 data points, we're able to speak to customers through nudges, giving them the right information. Be it for investment or the next best restaurant they should dine in whenever they're near a particular neighborhood. This has resulted in an uplift for us in the consumer bank from AI/ML models being launched. We are looking at doubling that to $200 million this year. It is implemented right across all 6 markets, covering 7.5 million customers. And last year alone, we generated more than 344 million of such nudges to both the RM and as well as to the customers. Lastly, on ecosystem as a third new way of working. I'm delighted to share with you the progress that we have made. As you know, in ecosystem, we have 3 key objectives. We have now achieved acquiring customers at scale through ecosystem and acquiring those customers in the partners platform that we work with. Secondly, we have leveraged the data to enable us to be able to develop good credit models. But more importantly, we have used that for credit monitoring to enhance the risk management that we have in lending within ecosystem. And finally, the AI/ML models that we have are now embedded to engage the customers very differently as we work with them in those platforms. Our strategy remains the same, for CBG, it's about where consumers work, live and play. And we embed solutions such as lending, wealth management and payment in those platforms. In IBG, it's about the procure to pay and as well as the cash to order cycle, embedding supply chain financing solutions and as well as cash management and FX into these platforms. Let me share with you 2 examples on how we differentiate ourselves in ecosystem partnership against the rest of the banks. CRED is a leading platform -- payment platform in India for credit cards. More than 1/3 of the credit card population in India used CRED to pay their credit card bills across India. So it is a very important platform in India. What we have worked with them is to look at the customer base that they have to preapprove the list of customers with their data and our model. And with that preapprove, when the customers are making payment, we will prompt them on a potential loan that they could take up. And when they decide to pick up the loan, we will do KYC, AI/ML and fraud checks immediately on the fly through the API connectivity. So within minutes, the customers will be approved and onboarded. And when they take up the loans, it will be dispersed through our API connectivity into API -- into UPI payment infrastructure in India and they receive the money in another bank's account. The credit monitoring that we would do is by looking at a payment behavior throughout the whole loan period that they have. And we will detect that there are any potential delinquencies that could come up because of smaller amounts that he pay or delay in payment, we will use that to be able to talk to the customer and help us to mitigate the potential losses that could come because of weaknesses that we see. These APIs are implemented right across all other partners that we work with in our 6 markets. The second example is on supply chain financing partnerships, and this is where we work with JD Logistics in China and Hong Kong. I would point out some of the cool features that were deployed in this ecosystem. Within this platform, we are supplying financing for both AR and as well as inventory financing to customers of JD Logistics. So what we do is we would use that information that they have on the transactions that they are doing on the logistics platform. And there are banner ads that we would serve using our AI/ML models to target the right customers for financing. And when they're interested in taking up the loan, we will use the information within their platform such as accounts receivable and inventory levels to determine the right size loans to be given to them. And once they agree to pick it up, we would credit it into their account. The other cool feature that exists in this structure is we can actually see the inventory level and AR of each of their customers. And in the event that we realize that their credit are deteriorating, we have the ability to call JD Logistics to not allow them to pull out this inventory until they pay down the loan. So this is something that is really quite powerful to the API connectivity that we do and as well as the live interaction that we get out of it. This is also being implemented across all other partners for supply chain. The impact from ecosystem has been tremendous. The number of customers that we have acquired through ecosystem has grown up by 8x for Consumer Bank. And today, it contributes to 30% of new customers that we acquire outside of Singapore and in IBG, it's about 2x over the last 3 years. On the balance sheet side, it has grown by 8x now contributing to 65% of all new secured and unsecured loans that we generate outside of Singapore for unsecured and secured assets. And it's a supply chain financing assets that we generate more than 30% of new bookings are now being pushed through from ecosystem. The AI/ML models that we put into the platform allows us to engage the customers quite differently. So on our own marketplace PayLah! which is everyday app, we are now the #1 bank wallet that would use with the highest NPS score and as well as highest share of wallet from the customers and in addition to just providing supply chain financing to SME, we're able to now do cross-buy right across broader set of customers and thereby getting greater value from ecosystem partnership. So looking ahead, managing through journeys covers more than 61% of CBG and IBG revenues. It is pervasive across the entire bank with 69 MtJs live, covering more than 6,000 customers -- more than 6,000 employees and $8 billion worth of revenue. More importantly, the new way of working with PCs, the Workflow/Workbench at the heart and the whole flywheel will enable us to drive growth through MtJ. Secondly, the data and AI business impact has been tremendous. We've been able to double every single year since 2020 when we started to measure. And now it is pervasive across the entire bank and with the ADA and as well as Allen architecture that is being set up, which you will see in the showcases, it will give us a very good platform to incorporate any new generative AI models that are coming through. And we believe that AI will help generate an incremental of $1 billion of economic value for us over the next 3 to 5 years. And finally, on ecosystem, you have seen the financial impact that we have achieved over the last 3 years. And more importantly, we are growing the number of partnerships, increasing the number of products that we will infuse into these partnerships. And this is also pretty much a BAU in the way we run our businesses in the country as what Shee will share and as well as in CBG and IBG. Ecosystem partnerships will also give us a lift of $1 billion in the next 3 to 5 years. So in conclusion, these 3 new ways of working, leveraging technology that we have will result in the uplift of our trajectory in both revenue growth and as well as productivity gains. Thank you.

Hi. Good morning, everybody. Today, I'm here to share with you how we have transformed credit risk management. In a typical credit process, it usually starts with a customer requesting for a credit facility. And the credit facility is usually processed internally via a credit memo. So once this credit memo is approved, it will actually be activated and then available for use by the customer. So that oppose disbursement, what we will see is that the bank will monitor their performance. This is the typical origination, underwriting and portfolio management aspects of credit risk management. So how have we reimagined credit risk management. The enablers are the cloud-native architecture, nontraditional data and AI/ML. And what are the outcomes that we have achieved from all these enablers. First, we have customers increasing by 11%, from 11 million to 12.3 million from 2019 to 2022. So 2019 being the time that we embarked on this journey. Second, loans increased by 16% from SGD 362 billion to SGD 420 billion and NPL rate has improved from 1.5% to 1.1%. Next, let me share with you how cloud-native architecture has given us efficiencies at scale. So what we are able to build is a unified platform for which we can define 17 unique personas. For example, relationship managers, credit risk managers as well as credit control personnel. And we are able to integrate all these roles across the entire platform. So we are able to generate flexible and collaborative workflows, resulting in 48% reduction in the time taken to prepare memo and we are also able to automate financial spreading and financial analysis. And this has given us a 30% reduction in the preparation time for financial analysis. And because we have this unified platform, we also have digital connectivity from the front to the back. And so the back end has also benefited from this. So what we are seeing is a 71% STP for limit creation at the back end. Another added advantage of having this unified platform is that all the data that we have collected during the analysis phase whether these are the nontraditional data or the traditional data, they are then able to be used in digital format. So this data tends to be well defined, well organized and ready for use. And in this case, they actually give us a lot of advantages in origination such as underwriting new segments and markets as well as strengthening our fraud detection for credit applications. And also in portfolio management, where we are able to deploy advanced analytics to drive early warning. Let me now share how we have powered new originations using data and analytics. In some of these new markets, we do have customers who have inadequate traditional credit data. So for example, customers who lack a credit history but have a very, very rich digital footprint. Now -- and customers who are also having untimely financial information, for example, as well as new economy workers who are most likely freelancers and not full-time employees, and therefore, they like full-time employment data. What we are able to do is we're able to then combine traditional data such as payslips, credit bureau data, tax information, together with bank transactional data to create credit scoring models and we are also able to use buyer information and lifestyle information to create income estimation models. And we can also use supply chain transactional data as well as inventory information to, in fact, drawdown transaction validation. By drawdown transaction validation, what I mean is that we are able to assess the inventory level before we have to disburse the loan. And so this creates a very, very significant credit control for us when we are disbursing loans. So how has this model helped us? It has created the capacity for growth as we access new segments. So in the consumer banking ecosystems, we have instant credit decisioning via real-time APIs and we are able to scale consumer lending with minimal incremental cost. So what we have seen is the number of applications approved has gone up by 16x from 2020 to 2022. And we have seen new volumes increasing by 28x. In the corporate banking ecosystems, we now have the ability to onboard thousands of suppliers within minutes. And we are able to effect end-to-end digital design with very minimal manual intervention. And we see the number of anchors and platforms increasing by 1.8x and we have seen the book size grow by 2.5x. Amidst all this business growth, we also recognize the need for us to strengthen our fraud management for new credit applications and so what we have done is exactly the same thing. We basically continue to leverage on traditional data such as credit bureau as well as the rule-based detection mechanism, but we supplemented it with nontraditional data such as the device ID and facial recognition, and we're able to deploy new tech to do electronic verification. So we are able to detect bot attacks and we are able to identify multiple applications and geo-location spamming. What we then do is we overlay with AI/ML models that are capable of detecting false positives. And what we have seen is a 12% reduction in false positive and a reduced identity theft by syndicates. Let me now share how we have done the same thing in the area of portfolio management. Our earning warning models are able to predictively identify cases for early warning. So we use big data, more than 700,000 network linkages are traced, more than 13 million payments and remittances are examined. And we combine that with our internal early warning model called CRANE, which is able to iterate and learn with additional factors. For example, macroeconomic factors and industry indicators. And this has given us timely alerts for more than 73,000 borrowers. And with all these timely alerts and coupled with our internal monitoring, we are able to reduce instances of sudden death from 1% in 2019 to 0.4% in 2022. By sudden deaths what I mean is a case that goes directly from performance status into NPLs, without going through a watchlist process. Now what we have also found is that we are able to improve with the industrialization of the model development. So this one Kwee Juan just now talked about it. And what -- what I can do is to show you an example. In the case of the COVID-19 moratorium because the SME's cash flows were very adversely affected, we were actually able to enhance the existing CRANE model with a cash flow model that was developed within 3 months and that can achieve a 95% accuracy in flagging potential NPAs as well as 60 days delinquent customers. And what we have done is we have identified more than SGD 80 million of at-risk exposures. So in the previous slide, the question will be how do we develop all these early warning models. So the models that were developed for proactive monitoring, first leverage on the ADA that Jimmy talked about this morning, whereby it is filled with and ingested with traditional data and nontraditional data. And this is a very rich database for which we can extract features that are predictive for early warning. And by use -- deploying risk analytics methodologies, we are able to produce scoring models that are granular and fragmented. So we can produce models for small enterprises, we can produce models for medium enterprises. And what we do then is we overlay it with customer linkages to produce a list of at-risk customers. And these at-risk customers are then subject to a more deep dive and internal credit review process. So in the previous slide, what do I mean by customer linkages that refers to network-based analytics that captures risk that are very difficult to identify manually. So in the left-hand side of the slide, you can see that what we do is we use transactional data together with the risk factors from the models and then we overlay it with network-based analytics to flat at risk entities that provide sharper insights. So as an illustration, if you look at the diagram in the middle, you can see that auditor A serve multiple borrowers with high and medium risk. What this tells us is that potentially even some of the existing low-risk customers may actually be at-risk borrowers. Similarly, if you look at PQR Private Limited, you can see that it has a high supplier concentration from APC Private Limited and XYZ Private Limited, which are high risk borrowers. So what this tells is that potentially PQR can be susceptible to the failures of ABC or XYZ. And so through this network-based analytics, we are able to identify 44 instances of potential round-tripping financing. So in the last 10 minutes or so, I have said with you all, how we have transformed the credit risk management. So what we will do looking ahead is to continue to power productivity through our cloud-native architecture and to continue to penetrate new markets through our scalable origination capabilities and to sharpen tools to drive portfolio effectiveness through advanced risk and analytics. With that, I thank you.