1 00:00:02,520 --> 00:00:07,040 Speaker 1: Bloomberg Audio Studios, Podcasts, radio News. 2 00:00:11,160 --> 00:00:14,920 Speaker 2: Welcome to the Daybreak Asia podcast. I'm Doug Chrisner. In 3 00:00:14,960 --> 00:00:18,200 Speaker 2: the States, risk assets were sold down, with big cap 4 00:00:18,239 --> 00:00:21,120 Speaker 2: tech and cryptocurrencies bearing the brunt of the selling. 5 00:00:21,440 --> 00:00:21,560 Speaker 3: Now. 6 00:00:21,600 --> 00:00:24,400 Speaker 2: That drop came after a number of Wall Street executives 7 00:00:24,480 --> 00:00:27,159 Speaker 2: warned of a pullback in the equity market. At the 8 00:00:27,200 --> 00:00:30,240 Speaker 2: same time, the hedge fund manager Michael Burry placed a 9 00:00:30,360 --> 00:00:34,920 Speaker 2: one point one billion dollar bet against leading artificial intelligence 10 00:00:34,920 --> 00:00:38,120 Speaker 2: related stocks. For more on the market action, we caught 11 00:00:38,200 --> 00:00:41,840 Speaker 2: up with Anna Wou. She is cross asset investment specialist 12 00:00:42,120 --> 00:00:45,800 Speaker 2: at Vanek who spoke with Bloomberg TV host April Hong 13 00:00:45,960 --> 00:00:47,400 Speaker 2: and shry On and I. 14 00:00:47,479 --> 00:00:49,159 Speaker 1: Great to have you with us as we get the 15 00:00:49,159 --> 00:00:52,639 Speaker 1: Asian session started. We have already seen significant pressure over 16 00:00:52,680 --> 00:00:55,560 Speaker 1: in South Korea, for example, because of the Career Exchange 17 00:00:55,920 --> 00:00:59,680 Speaker 1: warning about s k Heinix, because of that incredible AI rolly. 18 00:01:00,080 --> 00:01:02,600 Speaker 1: Where are we in Asia when it comes to these 19 00:01:02,680 --> 00:01:05,080 Speaker 1: valuations of these high flying tech stocks. 20 00:01:08,000 --> 00:01:10,679 Speaker 3: Hello from Sydney and good to see you. I think 21 00:01:10,800 --> 00:01:13,800 Speaker 3: very much to your point. We had a five month 22 00:01:13,920 --> 00:01:18,000 Speaker 3: rally in AI thematic in the US and cross the board, 23 00:01:18,440 --> 00:01:21,280 Speaker 3: so the bar is simply just getting higher. So now 24 00:01:21,360 --> 00:01:25,640 Speaker 3: a modest earning speed does not translate into price reaction anymore. 25 00:01:26,480 --> 00:01:30,640 Speaker 3: To that point, the similar sentiment, I guess it's flowing 26 00:01:30,680 --> 00:01:33,520 Speaker 3: into the Asia market as well. After such a rally 27 00:01:33,560 --> 00:01:37,360 Speaker 3: that we have seen in South Korea, China, arguably in Japan, 28 00:01:37,760 --> 00:01:40,960 Speaker 3: I think that bar right now is getting higher as well. However, 29 00:01:41,200 --> 00:01:45,039 Speaker 3: I want to bring your attention to the valuation landscape. 30 00:01:45,120 --> 00:01:48,920 Speaker 3: Right even after the broader rally in Asia tech that 31 00:01:48,960 --> 00:01:52,480 Speaker 3: we have seen so far, it's still valued much lower 32 00:01:52,520 --> 00:01:55,560 Speaker 3: than the US tech and which makes it really a 33 00:01:55,680 --> 00:01:58,640 Speaker 3: value and a growth play in the long term. And 34 00:01:58,760 --> 00:02:01,680 Speaker 3: if we look at the EPs growth, it's not great, 35 00:02:01,720 --> 00:02:06,240 Speaker 3: but it's improving sectors sector for the sector quarters after quarter. 36 00:02:06,400 --> 00:02:09,720 Speaker 3: So I think the long term story for this sector 37 00:02:09,880 --> 00:02:12,240 Speaker 3: in Asia is still constructive. 38 00:02:15,280 --> 00:02:18,239 Speaker 1: One of all, not necessarily the direct the AI please, 39 00:02:18,320 --> 00:02:20,880 Speaker 1: but the indirect ones because we know that in order 40 00:02:20,919 --> 00:02:24,639 Speaker 1: to power artificial intelligence will need the energy for example. 41 00:02:26,800 --> 00:02:28,120 Speaker 1: That that's a great question. 42 00:02:28,320 --> 00:02:32,840 Speaker 3: I really love that because exactly the global AI industry 43 00:02:33,120 --> 00:02:36,320 Speaker 3: is maturing over the last couple of years, so it's 44 00:02:36,360 --> 00:02:39,520 Speaker 3: gone from you know, this idea generation phase who has 45 00:02:39,560 --> 00:02:44,120 Speaker 3: the best model really to an operational intelligence phase where 46 00:02:44,160 --> 00:02:50,840 Speaker 3: we need to see actual monetization an operational AI ecosystem. 47 00:02:50,960 --> 00:02:56,880 Speaker 3: And in that sense, the supplementary roles into the AI 48 00:02:57,400 --> 00:03:01,760 Speaker 3: rally right now are benefiting and also positioned to benefit 49 00:03:02,400 --> 00:03:05,520 Speaker 3: in the coming quarters as the margin expansion goes in. 50 00:03:06,320 --> 00:03:09,320 Speaker 3: To your point, energy play is one of the one 51 00:03:09,360 --> 00:03:13,200 Speaker 3: of the pockets of opportunities that's getting a lot more 52 00:03:13,320 --> 00:03:18,520 Speaker 3: attention compared to the previous quarters because AI after the 53 00:03:18,720 --> 00:03:24,320 Speaker 3: record amount of AI capex energy and electricity demand in specific, 54 00:03:24,440 --> 00:03:28,600 Speaker 3: it's rallying two decade high and it's positioned to go 55 00:03:28,800 --> 00:03:32,480 Speaker 3: ten x in by twenty thirty. So that demand gap 56 00:03:32,560 --> 00:03:37,960 Speaker 3: needs all sorts of energy play. So you know, one 57 00:03:38,040 --> 00:03:41,600 Speaker 3: of the more prominent play right now is the nuclear 58 00:03:41,880 --> 00:03:45,360 Speaker 3: It gives twenty four to seven clean non emission play 59 00:03:45,560 --> 00:03:48,760 Speaker 3: from that part and benefiting the uranium minus as well, 60 00:03:48,840 --> 00:03:52,080 Speaker 3: and to a certain extent, the renewable other renewable energy 61 00:03:52,120 --> 00:03:56,440 Speaker 3: sources companies have been growing very fast in the second 62 00:03:56,440 --> 00:03:59,240 Speaker 3: half of the year. Also look at the valuation side 63 00:03:59,280 --> 00:04:02,440 Speaker 3: as well, and pointing to that growth and value play, 64 00:04:02,720 --> 00:04:06,720 Speaker 3: they are very attractively valued comparing to the other pockets 65 00:04:06,720 --> 00:04:07,080 Speaker 3: of AI. 66 00:04:08,720 --> 00:04:11,400 Speaker 4: With that in mind, which market do you think will 67 00:04:11,520 --> 00:04:13,520 Speaker 4: lead the way for the rest of US year and 68 00:04:13,600 --> 00:04:17,120 Speaker 4: into the first quarter of next year. Is it still 69 00:04:17,160 --> 00:04:20,600 Speaker 4: going to be perhaps South Korea for the region, especially 70 00:04:20,600 --> 00:04:22,480 Speaker 4: given how we're seeing a resurgent dollar. 71 00:04:24,880 --> 00:04:28,680 Speaker 3: Yeah, okay. I think that question really goes into two parts. 72 00:04:28,800 --> 00:04:33,320 Speaker 3: I think in terms of markets that is positioned well 73 00:04:34,360 --> 00:04:37,039 Speaker 3: towards the end of the year to next year, Korea 74 00:04:37,440 --> 00:04:40,080 Speaker 3: is one of the more high conviction market because it's 75 00:04:40,080 --> 00:04:43,919 Speaker 3: got the cleanest growth play right now and also translating 76 00:04:43,960 --> 00:04:48,080 Speaker 3: into the latest earning season while it's still quite early days, 77 00:04:48,080 --> 00:04:51,480 Speaker 3: but we can still see that over half of the 78 00:04:51,520 --> 00:04:55,520 Speaker 3: companies are reporting surprising to the upside. Also, it's got 79 00:04:55,600 --> 00:04:58,799 Speaker 3: two cleanest play in terms of growth. One is AI. 80 00:04:59,400 --> 00:05:04,240 Speaker 3: It's strategic position in the high member chip specialist role 81 00:05:04,320 --> 00:05:07,000 Speaker 3: in in the global AI supply chain is giving it 82 00:05:07,120 --> 00:05:10,040 Speaker 3: a long term tailwind and long term contracts as well 83 00:05:10,560 --> 00:05:14,520 Speaker 3: with margin expansion possibilities. But also it has a very 84 00:05:14,640 --> 00:05:19,600 Speaker 3: unique role in the global defense sector and also that 85 00:05:19,680 --> 00:05:22,880 Speaker 3: has an AI play to it as well. So these 86 00:05:22,920 --> 00:05:28,839 Speaker 3: two catalysts, I guess is driving the career market to 87 00:05:28,920 --> 00:05:32,840 Speaker 3: a broader growth play. Outside of that, I think China, 88 00:05:32,960 --> 00:05:36,159 Speaker 3: even though right now the the rally has stoled a 89 00:05:36,160 --> 00:05:39,120 Speaker 3: little bit, and I think investors are waiting for a 90 00:05:39,240 --> 00:05:45,120 Speaker 3: more pronounced and substantial policy stimulus to to you know, 91 00:05:45,240 --> 00:05:49,000 Speaker 3: pick on that rally again. And but also AI sector 92 00:05:49,080 --> 00:05:53,360 Speaker 3: in that country can still defy gravity as the broader 93 00:05:53,920 --> 00:05:57,479 Speaker 3: I guess hardware makers rally and race to to to 94 00:05:57,560 --> 00:06:01,720 Speaker 3: fight for the role for China's the domestic Navidia. 95 00:06:02,040 --> 00:06:06,080 Speaker 2: That was ANAWU Cross Asset investment specialist at Vanek speaking 96 00:06:06,080 --> 00:06:09,839 Speaker 2: to Bloomberg TV host April Hong and shrry On here 97 00:06:09,880 --> 00:06:21,279 Speaker 2: on the Daybreak Asia podcast. Welcome back to the Daybreak 98 00:06:21,320 --> 00:06:25,360 Speaker 2: Asia Podcast. I'm Doug Chrisner. Economies across Asia are being 99 00:06:25,400 --> 00:06:29,720 Speaker 2: reshaped by a new reality or realities plural. We've got 100 00:06:29,800 --> 00:06:34,000 Speaker 2: higher US tariffs, softer Chinese demand, and the growing impact 101 00:06:34,000 --> 00:06:37,200 Speaker 2: of artificial intelligence. And in the midst of it all, 102 00:06:37,440 --> 00:06:41,440 Speaker 2: money moving faster and more securely across borders. Joining me 103 00:06:41,520 --> 00:06:44,200 Speaker 2: now for a closer look is Sandeep Mahultra. He is 104 00:06:44,279 --> 00:06:49,680 Speaker 2: Executive VP of Core Payments for the Asia Pacific at MasterCard. Sandeep, 105 00:06:49,680 --> 00:06:51,440 Speaker 2: thank you so much for making time to chat with 106 00:06:51,480 --> 00:06:54,520 Speaker 2: me lately. I think we can agree on this much. 107 00:06:54,560 --> 00:06:57,400 Speaker 2: There has been a tremendous amount of focus on the 108 00:06:57,480 --> 00:07:01,159 Speaker 2: use of artificial intelligence. Give me a sense right now 109 00:07:01,320 --> 00:07:06,279 Speaker 2: best you can on how MasterCard is using AI, especially 110 00:07:06,320 --> 00:07:07,400 Speaker 2: in the APEC region. 111 00:07:09,360 --> 00:07:11,600 Speaker 5: Yeah, well, first of all, thank you for having me on. 112 00:07:11,840 --> 00:07:14,640 Speaker 5: And you know AI is the is the tok of 113 00:07:14,680 --> 00:07:15,000 Speaker 5: the town. 114 00:07:15,160 --> 00:07:18,200 Speaker 6: So if you look at MasterCard, you know our big 115 00:07:18,240 --> 00:07:22,480 Speaker 6: focus used to be converting cash to digital and then 116 00:07:22,680 --> 00:07:25,360 Speaker 6: over the last you know, one year or so, we 117 00:07:25,400 --> 00:07:28,720 Speaker 6: are actually taking this to the next level, so taking 118 00:07:28,880 --> 00:07:34,000 Speaker 6: digital to intelligent and this is where AI plays a 119 00:07:34,000 --> 00:07:37,920 Speaker 6: big role, where we are looking at intelligent transactions just 120 00:07:37,960 --> 00:07:41,280 Speaker 6: not digital, and we are actually changing our network to 121 00:07:41,360 --> 00:07:44,760 Speaker 6: be ready for this connected commerce, which is our vision 122 00:07:44,800 --> 00:07:45,480 Speaker 6: for twenty. 123 00:07:45,280 --> 00:07:48,920 Speaker 5: Thirty driven by AI. So what is AI going to do? 124 00:07:48,960 --> 00:07:51,960 Speaker 6: We want to make sure that consumers, when they do 125 00:07:52,160 --> 00:07:55,040 Speaker 6: discovery of the products or search the products on an 126 00:07:55,040 --> 00:07:59,920 Speaker 6: AI agent, are able to even do a purchase or 127 00:08:00,160 --> 00:08:04,920 Speaker 6: that without leaving that agent. Sounds very simple, but behind 128 00:08:04,920 --> 00:08:06,240 Speaker 6: the scenes, it's very complex. 129 00:08:06,320 --> 00:08:06,480 Speaker 3: Right. 130 00:08:06,880 --> 00:08:11,080 Speaker 6: What happens if you ordered green pair of socks and 131 00:08:11,160 --> 00:08:15,240 Speaker 6: red rive, who takes care of that? What happens if 132 00:08:15,280 --> 00:08:19,160 Speaker 6: a fraudulent transaction happens? How do you take care of that. 133 00:08:19,840 --> 00:08:22,880 Speaker 6: So what we are trying to ensure is that we're 134 00:08:22,880 --> 00:08:26,120 Speaker 6: trying to create a very safe, secure, and a transparent 135 00:08:26,760 --> 00:08:31,000 Speaker 6: kind of an environment for these agents to perform the transaction. 136 00:08:31,600 --> 00:08:33,880 Speaker 2: I'm wondering now on the degree to which you are 137 00:08:33,920 --> 00:08:37,880 Speaker 2: collaborating with other software developers over or whether this is 138 00:08:38,000 --> 00:08:42,120 Speaker 2: primarily something that is proprietary to the extent that you 139 00:08:42,280 --> 00:08:46,120 Speaker 2: need to employ a number of software engineers to help 140 00:08:46,200 --> 00:08:50,760 Speaker 2: facilitate this goal. What's the balance between collaboration and kind 141 00:08:50,760 --> 00:08:52,600 Speaker 2: of going alone in house. 142 00:08:54,600 --> 00:08:56,760 Speaker 5: It's all collaborative, it's all partnership. 143 00:08:56,840 --> 00:09:01,080 Speaker 6: It's all based on standards because you cannot anything propriety 144 00:09:01,160 --> 00:09:04,040 Speaker 6: because it won't scale. And if it doesn't scale, it 145 00:09:04,080 --> 00:09:06,760 Speaker 6: doesn't matter. So what we're trying to do is we're 146 00:09:06,800 --> 00:09:09,840 Speaker 6: working with the fidos of the world, which is the 147 00:09:09,840 --> 00:09:13,640 Speaker 6: standard community. We're working with cloud Flare and I'll tell 148 00:09:13,640 --> 00:09:16,520 Speaker 6: you what that does. We're working with PayPal, We're working 149 00:09:16,559 --> 00:09:19,760 Speaker 6: with many other partners to make sure that the transaction 150 00:09:19,960 --> 00:09:21,520 Speaker 6: happens in a safe, secure fashion. 151 00:09:22,160 --> 00:09:22,360 Speaker 4: You know. 152 00:09:22,559 --> 00:09:24,920 Speaker 6: One example is you want to make sure that when 153 00:09:24,920 --> 00:09:28,160 Speaker 6: the merchant accept a transaction, that agent is a good agent. 154 00:09:28,480 --> 00:09:29,240 Speaker 5: How do you do that? 155 00:09:29,520 --> 00:09:32,720 Speaker 6: And that's where cloud Flare club comes into picture, which 156 00:09:32,760 --> 00:09:36,440 Speaker 6: basically will block unit agent which is not a good agent, 157 00:09:37,160 --> 00:09:39,400 Speaker 6: and that provides, you know, comfort to the merchant who's 158 00:09:39,440 --> 00:09:40,719 Speaker 6: accepting those transactions. 159 00:09:41,760 --> 00:09:43,559 Speaker 2: So in the last two week here in the States, 160 00:09:43,640 --> 00:09:46,760 Speaker 2: we heard from a number of those big hyper scalers 161 00:09:47,320 --> 00:09:50,560 Speaker 2: on their AI caps spend. And I'm curious about the 162 00:09:50,559 --> 00:09:53,560 Speaker 2: degree to which you feel, maybe not you personally, but 163 00:09:53,679 --> 00:09:59,120 Speaker 2: MasterCard as a company feels compelled to lay out vast 164 00:09:59,160 --> 00:10:02,440 Speaker 2: sums of money in the capex realm in order to 165 00:10:02,480 --> 00:10:06,079 Speaker 2: be ready for this kind of change that you're describing. 166 00:10:08,120 --> 00:10:10,679 Speaker 6: Look, I think the hyperskillers are doing what they are 167 00:10:10,720 --> 00:10:14,320 Speaker 6: best in in terms of creating models, in terms of 168 00:10:14,480 --> 00:10:19,400 Speaker 6: providing the computing data to make sure that that is done. 169 00:10:19,800 --> 00:10:22,199 Speaker 6: What we are doing is we are basically saying, if 170 00:10:22,240 --> 00:10:25,840 Speaker 6: you search using that data to find an item you like, 171 00:10:26,360 --> 00:10:29,520 Speaker 6: we will make sure that that transaction which is done 172 00:10:29,880 --> 00:10:33,320 Speaker 6: within that AI interface, whether it's an agent, whether it's 173 00:10:33,360 --> 00:10:36,880 Speaker 6: some other protocol which the consumer is using, or if 174 00:10:36,880 --> 00:10:39,360 Speaker 6: the merchant has made a change, we will make that 175 00:10:39,520 --> 00:10:45,360 Speaker 6: commerce become safe, secure and intelligent and give comfort to 176 00:10:45,360 --> 00:10:48,560 Speaker 6: the consumer without leaving that agent, you know, domain. 177 00:10:48,720 --> 00:10:51,640 Speaker 2: San Deepe I'm curious as to whether there are certain 178 00:10:51,760 --> 00:10:55,920 Speaker 2: areas of the digital payment space that you're particularly concerned about, 179 00:10:55,920 --> 00:11:00,000 Speaker 2: perhaps something that you have to almost counter program again 180 00:11:00,000 --> 00:11:02,760 Speaker 2: anst whether there is a level of risk for your 181 00:11:02,800 --> 00:11:05,640 Speaker 2: business or the businesses of your customers. What are the 182 00:11:05,679 --> 00:11:07,400 Speaker 2: areas most concerning to you? 183 00:11:07,800 --> 00:11:09,800 Speaker 6: It is it is a big concern that if you 184 00:11:09,840 --> 00:11:13,240 Speaker 6: look at just Asia loan Asia lost about close to 185 00:11:13,440 --> 00:11:17,200 Speaker 6: six and seventy billion dollars of money due to fraud 186 00:11:17,360 --> 00:11:21,640 Speaker 6: in thus last year. So sixty percent of the banks 187 00:11:21,640 --> 00:11:25,680 Speaker 6: are brightticing AI driven fraud prevention and identity verification. So 188 00:11:25,720 --> 00:11:28,200 Speaker 6: that's a big focus for us. How we're going to 189 00:11:28,280 --> 00:11:31,080 Speaker 6: do that is we want to make sure that the 190 00:11:31,120 --> 00:11:35,199 Speaker 6: card numbers which you have don't exist anymore. So, whether 191 00:11:35,240 --> 00:11:38,600 Speaker 6: you save a card on file at Macy's dot Com, 192 00:11:38,679 --> 00:11:41,120 Speaker 6: we're going to replace it with a token, whether you 193 00:11:41,240 --> 00:11:44,720 Speaker 6: basically have a Apple Pay transaction that replaced by a 194 00:11:44,760 --> 00:11:45,640 Speaker 6: token even today. 195 00:11:46,320 --> 00:11:47,480 Speaker 5: And then even the. 196 00:11:47,360 --> 00:11:50,040 Speaker 6: Cards which are on the physical card, the card numbers, 197 00:11:50,040 --> 00:11:52,440 Speaker 6: we're going to make them numberless as well. So the 198 00:11:52,480 --> 00:11:56,520 Speaker 6: big focus is make that tokenized. No more card numbers 199 00:11:56,640 --> 00:11:59,360 Speaker 6: anywhere on the planet, and that's our goal for twenty 200 00:11:59,440 --> 00:12:02,880 Speaker 6: thirty and we must verify the user. We will make 201 00:12:02,880 --> 00:12:06,319 Speaker 6: sure that you are who you are for every transaction. 202 00:12:06,800 --> 00:12:12,040 Speaker 6: So fraud is the risk. But this tokenization and authentication, 203 00:12:12,120 --> 00:12:15,320 Speaker 6: which is verifying every user for every transaction, that's the 204 00:12:15,360 --> 00:12:17,840 Speaker 6: next step which we are moving towards and made a 205 00:12:17,840 --> 00:12:18,880 Speaker 6: big progress around that. 206 00:12:19,520 --> 00:12:23,000 Speaker 2: So when you're in conversation with your colleagues at MasterCard, 207 00:12:23,120 --> 00:12:26,280 Speaker 2: talk to me a little bit about aspirationally what the 208 00:12:26,280 --> 00:12:30,280 Speaker 2: world in the future looks like when we introduce quantum 209 00:12:30,320 --> 00:12:32,120 Speaker 2: computing to the payment system. 210 00:12:33,920 --> 00:12:37,440 Speaker 6: Yeah, so first, what quantum brings to the table is 211 00:12:37,559 --> 00:12:40,200 Speaker 6: it brings huge amount of computing in a different fashion, 212 00:12:40,760 --> 00:12:44,200 Speaker 6: it actually gets into the realm of even you know, 213 00:12:44,320 --> 00:12:49,280 Speaker 6: challenging today's cryptography and encryption, which is where the trust 214 00:12:49,360 --> 00:12:52,440 Speaker 6: is based on. So what we are working on is 215 00:12:52,480 --> 00:12:56,480 Speaker 6: we even created a crypto resistant cryptogram, you know, which 216 00:12:56,520 --> 00:12:59,520 Speaker 6: means a quantum resistant cryptrogram, which means that even a 217 00:12:59,600 --> 00:13:04,560 Speaker 6: quantum computer cannot actually decrypt that cryptogram or when the 218 00:13:04,600 --> 00:13:08,120 Speaker 6: transaction happens, it actually is very safe in nature. So 219 00:13:08,160 --> 00:13:11,360 Speaker 6: as the technology advances, you have to also advance in 220 00:13:11,400 --> 00:13:15,880 Speaker 6: this fraud prevention area because trust is the essence. The 221 00:13:16,000 --> 00:13:18,240 Speaker 6: day you break the trust of the consumer, they will 222 00:13:18,280 --> 00:13:20,960 Speaker 6: never transact and then you know, we would have a 223 00:13:21,000 --> 00:13:23,200 Speaker 6: tough time, you know, convincing the consumer and to do 224 00:13:23,240 --> 00:13:24,160 Speaker 6: these transactions. 225 00:13:24,600 --> 00:13:26,440 Speaker 5: So quantum does make a difference. 226 00:13:26,440 --> 00:13:28,319 Speaker 6: But we're looking into ways on how do you make 227 00:13:28,360 --> 00:13:31,360 Speaker 6: sure that these technologies are safe and secure? 228 00:13:31,679 --> 00:13:34,839 Speaker 2: To what extent are you using AI to actually help 229 00:13:34,920 --> 00:13:38,160 Speaker 2: build these platforms, which is to say, maybe you're relying 230 00:13:38,240 --> 00:13:42,120 Speaker 2: on it somewhat as a partner or a copilot or 231 00:13:42,120 --> 00:13:46,599 Speaker 2: a collaborator when your programmers are setting about developing software programs. 232 00:13:48,040 --> 00:13:50,400 Speaker 6: So AI is not new for us, right, We've used 233 00:13:50,440 --> 00:13:53,720 Speaker 6: AI for more than a decade. One of our three 234 00:13:53,760 --> 00:13:56,800 Speaker 6: of our services, one in three of our services today 235 00:13:56,880 --> 00:14:01,400 Speaker 6: leverages AI for insights and protection. And then we have 236 00:14:01,480 --> 00:14:04,960 Speaker 6: secured about one hundred and sixty billion transactions annually. And 237 00:14:05,000 --> 00:14:07,720 Speaker 6: then we have prevented over twenty billions of fraud every 238 00:14:07,800 --> 00:14:10,760 Speaker 6: year using AI. Now what's next is the next is 239 00:14:10,800 --> 00:14:14,440 Speaker 6: around this agent pay agent commerce. How do you make 240 00:14:14,480 --> 00:14:16,840 Speaker 6: sure that agent is a good agent? How do you 241 00:14:16,880 --> 00:14:19,600 Speaker 6: make sure that the user is present or not present 242 00:14:19,640 --> 00:14:22,040 Speaker 6: when they do the AI transaction? Because you can have 243 00:14:22,080 --> 00:14:25,160 Speaker 6: an autonomous transaction where the AI agent wakes up and 244 00:14:25,200 --> 00:14:27,040 Speaker 6: buys a ticket for you when the ticket price is 245 00:14:27,080 --> 00:14:29,640 Speaker 6: less than three hundred dollars. And the third thing is 246 00:14:29,880 --> 00:14:33,280 Speaker 6: the merchant may not be technologically sophisticated or not. How 247 00:14:33,280 --> 00:14:38,040 Speaker 6: do you make sure that this technologically unsophisticated merchant is 248 00:14:38,120 --> 00:14:41,200 Speaker 6: also part of this AI era. So that's what we 249 00:14:41,240 --> 00:14:46,360 Speaker 6: are working on. Prevent fraud, verify the consumer, make sure 250 00:14:46,360 --> 00:14:49,600 Speaker 6: the agent is good and it actually goes down to 251 00:14:50,680 --> 00:14:53,880 Speaker 6: a consumer who may not be AI sophisticated or a 252 00:14:53,920 --> 00:14:56,920 Speaker 6: merchant who may not be technologically sophisticated. That's what we're 253 00:14:56,960 --> 00:14:59,880 Speaker 6: working on by making one network do a lot of 254 00:15:00,040 --> 00:15:03,479 Speaker 6: heavy lifting and making more intelligent and more interoperable. 255 00:15:04,000 --> 00:15:06,880 Speaker 2: Sandy, before I let you go, describe for me the 256 00:15:06,960 --> 00:15:12,360 Speaker 2: current market dynamics in the APEC and your understanding about 257 00:15:12,400 --> 00:15:16,800 Speaker 2: the growth outlook for consumers and businesses in the region. 258 00:15:17,360 --> 00:15:21,200 Speaker 2: Is there a degree of optimism here or given some 259 00:15:21,240 --> 00:15:23,240 Speaker 2: of the volatility that we have seen not only in 260 00:15:23,320 --> 00:15:27,200 Speaker 2: markets but economies as well, are you a little maybe cautious? 261 00:15:29,200 --> 00:15:34,880 Speaker 6: I believe that Asia is leading in payments. It's not 262 00:15:35,080 --> 00:15:39,720 Speaker 6: the adopter of payment technology, it's the originator of that. 263 00:15:40,160 --> 00:15:44,360 Speaker 6: I personally see that the payment innovation is traveling from 264 00:15:44,520 --> 00:15:47,640 Speaker 6: east to west, where the other innovation might be traveling 265 00:15:47,680 --> 00:15:50,760 Speaker 6: from west to east. So I'm very optimistic. Seventy percent 266 00:15:50,760 --> 00:15:54,480 Speaker 6: of the real time payment transactions happening in Asia, and 267 00:15:54,760 --> 00:15:58,600 Speaker 6: there are wallets in China, there Alipay, v chat pay, 268 00:15:58,680 --> 00:16:01,160 Speaker 6: you have g cash and Philippine means they are just 269 00:16:01,560 --> 00:16:06,200 Speaker 6: buzzing driving electronic and digital transactions. What we're doing is 270 00:16:06,520 --> 00:16:11,040 Speaker 6: we are trying to create interoperability with these other ecosystems, 271 00:16:11,440 --> 00:16:14,840 Speaker 6: so which means you could be a consumer from the 272 00:16:14,960 --> 00:16:18,120 Speaker 6: US traveling to China. You can download an Alipay app, 273 00:16:18,280 --> 00:16:20,680 Speaker 6: you can put your card in there, and you can 274 00:16:20,720 --> 00:16:24,480 Speaker 6: transact wherever Alipay is accepted with no changes to the merchant. 275 00:16:24,680 --> 00:16:27,200 Speaker 6: That's just brilliant. This is where you brought in a 276 00:16:27,200 --> 00:16:32,440 Speaker 6: card ecosystem and a quality ecosystem talk to each other. That's, 277 00:16:32,480 --> 00:16:35,520 Speaker 6: in simple words, in properability. And wouldn't be cool that 278 00:16:35,600 --> 00:16:38,640 Speaker 6: somebody from Philippines using a g cash app goes to 279 00:16:38,680 --> 00:16:41,680 Speaker 6: the US, taps on a terminal and New York City 280 00:16:41,800 --> 00:16:44,920 Speaker 6: in New York City transit and that works with no changes. 281 00:16:45,200 --> 00:16:47,640 Speaker 6: I think that's introberability which we are seeing, and that's 282 00:16:47,680 --> 00:16:50,400 Speaker 6: where I'm very happy about you know, Asia is leading 283 00:16:50,400 --> 00:16:53,440 Speaker 6: the edge in this digital payments which is safe and secure. 284 00:16:53,840 --> 00:16:57,200 Speaker 2: So does it make sense to continue to cooperate with 285 00:16:57,360 --> 00:17:02,000 Speaker 2: these competing platforms or maybe at some point to become acquisitive. 286 00:17:02,640 --> 00:17:05,160 Speaker 6: Absolutely, I mean the whole idea is to partner because 287 00:17:05,280 --> 00:17:07,359 Speaker 6: we will never win the game alone. We have to 288 00:17:07,400 --> 00:17:10,719 Speaker 6: go together. So the wallets bring in the consumers. They 289 00:17:10,760 --> 00:17:13,680 Speaker 6: bring in an amazing consumer experience. We bring in acceptance, 290 00:17:13,680 --> 00:17:16,080 Speaker 6: which is one hundred and fifty plus million locations around 291 00:17:16,119 --> 00:17:18,199 Speaker 6: the world. We'll bring in trust, we bring in you know, 292 00:17:18,240 --> 00:17:21,040 Speaker 6: dispute resolution and things go wrong. So the whole idea 293 00:17:21,080 --> 00:17:24,760 Speaker 6: is to partner and basically leverage the strengths of what 294 00:17:24,880 --> 00:17:27,760 Speaker 6: each of these entities bring together. And that's how we 295 00:17:27,800 --> 00:17:29,639 Speaker 6: have grown over the last sixty years plus. 296 00:17:30,119 --> 00:17:33,520 Speaker 2: So you wouldn't buy a platform outright, I. 297 00:17:33,520 --> 00:17:36,120 Speaker 6: Mean built by partners. Our strategy so where it makes 298 00:17:36,160 --> 00:17:38,919 Speaker 6: sense we would build, whether we buy or whether we partner. 299 00:17:39,640 --> 00:17:42,880 Speaker 6: Partnership seems to be one of the best strategies so far, 300 00:17:43,880 --> 00:17:46,880 Speaker 6: so that's what we focus on. But when it makes sense, 301 00:17:46,960 --> 00:17:50,000 Speaker 6: we have bought companies, We've bought Recorded Future, you know, 302 00:17:50,040 --> 00:17:54,560 Speaker 6: which tracks fraud around the globe. We've done a corporative 303 00:17:54,600 --> 00:17:56,240 Speaker 6: exercise with Corpe which. 304 00:17:56,080 --> 00:17:58,160 Speaker 5: Actually drives forth business to business payments. 305 00:17:58,480 --> 00:18:00,960 Speaker 6: So we look at well where it makes sense to 306 00:18:00,960 --> 00:18:03,040 Speaker 6: build by a partner and be adop that strategy. 307 00:18:03,320 --> 00:18:05,320 Speaker 2: Sandai believe it there. Thank you so much for making 308 00:18:05,359 --> 00:18:08,320 Speaker 2: time to chat with me. Sandeep Maholtra. He is Executive 309 00:18:08,359 --> 00:18:12,240 Speaker 2: VP of Core Payments for the Apac Region at MasterCard. 310 00:18:15,320 --> 00:18:18,680 Speaker 2: Thanks for listening to today's episode of the Bloomberg Daybreak 311 00:18:18,840 --> 00:18:22,200 Speaker 2: Asia Edition podcast. Each weekday, we look at the story 312 00:18:22,280 --> 00:18:26,639 Speaker 2: shaping markets, finance, and geopolitics in the Asia Pacific. You 313 00:18:26,640 --> 00:18:30,760 Speaker 2: can find us on Apple, Spotify, the Bloomberg Podcast YouTube channel, 314 00:18:30,880 --> 00:18:33,879 Speaker 2: or anywhere else you listen. Join us again tomorrow for 315 00:18:34,040 --> 00:18:37,520 Speaker 2: insight on the market moves from Hong Kong to Singapore 316 00:18:37,920 --> 00:18:41,680 Speaker 2: and Australia. I'm Doug Chrisner, and this is Bloomberg