SCOR

The European edition of the Fortune 500, ranking companies by revenue.

Fortune 500 Europe

The first-ever European edition of the Fortune 500, ranking companies by revenue. 

F500 Europe 2023 SCOR_London_Asia_House_5_Luca_Piffaretti-Ooshot

SCOR ranks 186 with $20.8 billion in revenue (down 1.2%). The France-headquartered life and health (stock) insurance company has 3,522 employees and made a loss of $317 million (down 158.7%).

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Get insights into SCOR including business profile, stock information, news, and rankings from Fortune.

SCOR (SCRYY): Company Profile, Stock Price, News, Rankings

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SCOR | Fortune

SCOR (SCRYY): Company Profile, Stock Price, News, Rankings | Fortune

DBS, Southeast Asia’s largest and most profitable bank, is betting big on artificial intelligence to define the next era of global banking. From algorithmic credit scoring and AI-enabled fraud detection to hyper-personalized customer engagement, the bank is embedding intelligence across its platforms to drive both efficiency and growth. With regional competition heating up and digital expectations rising, the challenge is no longer whether to adopt AI—but how to do so responsibly, securely, and at scale. CEO Tan Su Shan shares how the bank is navigating that challenge, what being AI-fueled means in practice, and how institutions across Asia can turn automation and analytics into real strategic advantage.

The Intelligence Dividend: How DBS Is Deploying AI To Reshape Regional Finance

Conferences

Artificial intelligence is transforming the foundations of global finance, accelerating innovation and challenging the way financial systems are built, regulated, and accessed. In this new landscape, the future of fintech must be global, inclusive, and collaborative by design. From real-time credit scoring for the unbanked to AI-driven regulatory sandboxes, the true promise of fintech lies not just in what it can build—but in who it can reach. How can we ensure fintech becomes a force for equity rather than division? And what steps can we take to invest in interoperable systems, embrace distributed intelligence, and embed ethics at the core of AI-driven finance?  

The Infrastructure Of Inclusion: AI, Fintech, And The Power Of Global Collaboration

We're going to turn to a conversation about how AI and global collaboration are reshaping the finance industry to be more inclusive and resilient. From expanding access to credit to rethinking regulation, we want to know more about building fintech systems that serve people, not just profits. Please welcome Global Finance and Technology Network co-founder and group CEO Satanhu Mohanty and Fortune's Clay Chandler. Thanks Andrew, um. So it's a real privilege to have Fernando here with us this afternoon. This is a man with a rare career and and a remarkable set of insights into how the world is organizing, you know, when we talk about AI and technology, we often are talking about uh developed economies. We're talking about Silicon Valley, we're talking about what's going on uh in uh in China, but there's a whole big world out there. There and a lot of people don't have access to this technology and I want to talk a little bit to Subundo uh about that but first I wonder if we could uh just have you explain a little bit about uh the global fintech uh network. This is for those of you who don't know who spent many years in the monetary Authority of Singapore and then it was uh in charge of uh Fintech for the central bank at Singapore and then. Uh, very entrepreneurial, helped the central bank develop this entity called Elivandi. Which launched the Singapore Fintech Festival. This is, I would say, probably the most successful Fintech festival in the world. It's been going on, how many years now? 10th annual. So 60,000 people descend on Singapore from all over the world for this festival and discuss every aspect. We went last year and we're thrilled to be a part of that, but it's it's. It's blockchain. It's talking about, you know, different forms of finance, but it's also made a real effort to look into the developing world, you know, the global South, and how FinTech can help people that are unbanked, gain greater access to financial markets. So I hope we can talk a little bit about that, but talk to us about uh. You know, the, the global fintech network and what it's evolved to be because it has 4 different functions, right? Oh yeah. Well, um, it's kind of an extension of my last 10 years in MAS because we are, uh, If you take the last 10 years in Singapore, we built a fintech hub, uh, which kind of expanded beyond the Singapore mandate and we went to the global ecosystem. We influenced a lot of the choices financial sector are making. So we decided that to really super scale that idea, uh, MS created this GFTN. Um, and, and the, and the core idea behind this is to create this global network of things what we are doing here, primary information, right, talking to each other at a scale so that we can capture around the world conversation around. The innovation and financial services. Not in isolation, but in partnership with the regulators, investors, founders, fintech CEOs and all. And to do at a scale is the first mandate we thought, uh, do as part of GFTN. Which is an Eliandi extension. Then we added, OK, now we have done this. Let's add the advisory piece. How do we advise low income, middle income, emerging market on a strategic policy, uh, for innovation and financial services, uh, almost replicating the Singapore success in many emerging markets. And then we bring the platforms, the public good platforms to the market, create a more connected equitable system around the world. And then we thought, OK, now we've done the first three pieces. Let's put some venture money to boost innovation to upcoming startups. This is a comprehensive ecosystem building framework. So this is really a unique entity that's part think tank, part advisor, part investor, part investor, um. And has this tremendous global reach. Now the uh Syntech festival here extremely successful, but you've extended it. You now have a version in Japan and you've also brought a version to Kigali, is that right? Tell us about that and why you've done that. Well, we wanted to take the narrative to the emerging market because it Good to have a program in Singapore or in Hong Kong or in Tokyo, but how do we take this program at this scale to emerging markets, to Africa, to Latin America, right, to deep in ASEAN, our desire is to take this conversation to every hotspot in the world because we know the future of financial services are not going to be. Created out of developed market, it will come from emerging markets. It is going to come from low income countries. They're going to redefine the future of finance with better innovation, better technology. We got to go there and have this conversation. That drove that whole network build up. So tell us where do you see some of the greatest, you know, opportunities for bringing AI and FinTech to uh empower uh the developing world. I mean, is it in India? Is it in Africa? Well, where are the kind of urgent opportunities? Well, I'm going to be a little more uh provocative here, OK, today, if you take every history of technology, we have seen different tech stack coming and solving certain piece of financial services. Now, financial sector. Historically, is the biggest paymaster for technology. Even today, look at the AI revenue breakdown. Almost 40% or 50% goes to the financial sector, but we are, but when we see our, our design, we are archaic. We are not the best. Tech tech tech stack in the world, right? So we pay the bill, but we get the bad technology. So where is the issue? The core to the issue of, of AI or any technology solving financial sector challenges is there's an elephant in the room. It is the trade market now. If you, if you say to somebody, I'm a bank, one expectation is they lend you money. Yeah. Now, when you are borrowing money from a bank, the banks ask for you from your collateral, right? Right. That's the standard process of lending. That model cannot be solving the global need for credit, right? The financial inclusion challenge is the lack of banks' ability to extend credit to low income segment, right? The low income segment has no collateral, right? What they have behavioral data, right, intend to pay back, right? They can if you give them money, they will do something about it and they'll pay you back. To me, that's the. Problem AI should solve for create credible, predictive golden source behavior data which will replace the need for a collateral for a bank to lend. If you don't solve the problem, AI is still solving the classic bank problem which is make our productivity go up. We can fire hundreds of people. I think that's not what we want AI to do. We want AI to solve the foundational credit challenge banks have. That's very interesting. So when you, when you talk about, uh, you know, solving. I mean there are two ways to see the behavioral data and I've talked to companies that are kind of viewing it both ways, but there's a set of companies who are saying, oh look, this is just about risk analysis. If we know that we're gonna get paid back our risk is 0% the lending to low income. Uh, uh, you know, uh, people, then it means that we don't have to worry about it. We can set a fair rate and, and we can lend it, but there's another category of people that I've talked to that say actually we want that behavioral data because it's valuable to us. We can use it to make a bunch of predictions. Uh, we can use it to kind of gain people's behavior. We can use it to sell it to other people. So I mean, do, are you advocating both of those things or just but I think, I think that's less of a problem today. If you ask a credit officer, they want to establish two things ability to pay, uh, intend to pay in, OK. Collaterals gives the ability to pay matrices, behavioral data gives the intent to pay matrices because the way we lend today, you go back to the default side, the non-profitting loan, all our intent, yeah, largely intent, right? So we are denying people because we don't understand the intent and at the same time we, we, we, we give people money and so that they have a bad intent later on. Now the gaming behavior comes. Also for the same segment of people who have collateral, you want them to use more of the collateral to borrow more, but banks will never lend to people who have no collateral. So my sense is that there's a two sets of problems. The bad use of data, I think we can't control because regulators have enough protections in place, but what regulators cannot. Is the bank's inability to lend to people who don't have collateral that has to come from technology that has to come from a different set of business models which I hope this AI revolution can get us there. It's really interesting. So to anchor this evaluation of behavior though, you've also got to be able to establish some firm. Identity matrix for the uh uh you know, the borrowers and, and, and consumers in, in low income countries. Now I know this because I spent a spent a fair amount of time in India and I watched Nandan Neilani build the, the Adhar biometric identity system and It's fascinating because I had several conversations with Naan about this, and he explained to me that look, you're all hung up in the developed markets about privacy. You want to protect your privacy, but you don't understand that if you're somebody out of a village, uh, that's come into the big city looking for a job in India. You don't care about privacy as much as you care about getting your identity on the grid so that you can be paid, so that you can receive government benefits, so you don't have to deal with all these middlemen and and money change money changers, uh, to get what's, what do you. Africa must be the same, right? How do we Well, if you define the last 10 years of financial sector, I say DPI, digital public infrastructure, API, how to abstract complex system and connect to third party value providers, and then comes the front end user experience, apps, the super apps, that's how defined the last 10 years, the code to. FinTech revolution was the digital public infrastructure which people like London design which took the burden of identity from corporates individuals to the state. Now the question is, do many countries trust that state to hold the identity? So the first single biggest friction to replicate the India success is the. for a state to hold the data of identity and determining your your transaction at a national infrastructure, state infrastructure sovereign level. But what is going to happen for the next 10 years is an interesting shift with the coming of the tokenization and the blockchains and the digital asset piece, we are, we are decentralizing ideas now. I think if there is a there's a mechanism of of able to take the text stack of tokenization and the ethereums of the world and create a decentralized ID on those networks, you don't need a state to control and deliver that trusted ID. So there is a hope 10 years from in the next decade to shift identity from a single single state controlled mechanism to a decentralized design, you know, in addition. Another big problem for for people from these uh emerging markets is is cross border remittances, moving money, right? They're not they they don't have bank accounts. It's not sort of simple, uh, to do, and especially when it involves going across border very challenges challenging lots of people kind of get in the middle of that and extract fees. You've had some recent success just for working with that problem. You wanna talk a little bit. I think this is the first time globally yesterday. Somebody from Singapore can use pay now, right? Go to a Fintech app, but we have now a thresh called Liquid Pay or one of them. Send money to India with a UPI ID from here with no bank detail to be to be no banks in the middle of that in the system in the user perspective, put the money put the UPI ID in a fraction of a second money goes to other side. Of course, the bank rails are behind, but the consumer experience able to send the money at a full price transparency. You know exactly what you're getting the other side with the price being displayed with a very attractive. Cost of transaction. The target is to make it below 3%, including FX, yeah, so you can send the money. It took us 3 years to build it, and it requires a great amount of regulatory policy synchronized, yeah, yes, and that that is now going to be the global template of how to connect cross-border payment across different banks using national infrastructure with regulatory policy synchron. Multiple jurisdictions Project Nexus, which BIS was heading in, it's actually going to happen in Asia. 5 Asian countries have come together, are taking this model of India, Singapore, India, Malaysia, and Singapore, Malaysia, Singapore, Thailand and creating a multilateral connectivity architecture called Project Nexus which will go live hopefully next year to do replicate at a multilateral level this whole experience of connecting. National IDs or identity reflected to different IDs to send money to each other without the complexity of banking systems. That's a huge issue. I mean, particularly within this region, right, especially emerging low income migrant workers sending money back home, right? They can now send small ticket size money without without a huge cost on the top of those transfers. Wow. So, uh, what's next for you in terms of priorities then? My biggest. Priority now is going to be upskilling. One of the single biggest challenge in our economy will be lack of job right. I think killing for the future is is an acute crisis now with AI coming, the number of jobs in the market is going to dramatically go down. If we don't upskill our people, I think we are heading to a massive economic disaster. It is already real in many countries, unofficially. 2 out of 32 out of 3 don't have a job or will not have a job, and especially for a young workforce, there's a very little hope for a job in the job market now. We got to get it right. So upskilling for the future will be my single. Biggest priority for the next 2 or 3 years. People often say AI is a very democratizing technology, but it's only democratizing if you've got skills and and I think AI can be a great tooling for our new future upskilling designs. That's fascinating. So, uh, the next, uh, FinTech festival is in November. Yes, and it's the 10th anniversary. We're going to celebrate last 10 years of super success. We're going to talk about the future 1010 years of possibility. I strongly encourage your audience to come and join us at Singapore 10th anniversary. It's very exciting. Thank you for joining us and sharing you. We really appreciate it.

Gillian Zucker, master operator at the L.A. Clippers, discussed her unique relationship with owner Steve Ballmer, emphasizing his genuine love for the game. She detailed her career journey, from Hamilton College to roles in PR, sales, and operations. Zucker highlighted the transformation of the Clippers’ fan base and the development of Intuit Dome, focusing on frictionless technology and fan engagement. She shared insights on leveraging data for personalized experiences, such as rewarding loud fans and using facial recognition. Zucker also touched on the Clippers’ commitment to sustainability and efforts to enhance the fan experience through innovative features like the Halo scoreboard and the Wall. 

Gillian Zucker's Blueprint for Modern Sports Entertainment

Photo Courtesy of Gillian Zucker; Graphic by Fortune

Leadership

Presenter: Serena CESAREO, Senior Researcher, Tortoise Media

Brainstorm AI Singapore 2024: A Global Scorecard

Hello everyone. So the Global A I Index first launched in 2019 and has been updated four times since then. And it's essentially a big data led exercise that ultimately ranks over 60 countries based on artificial intelligence capacity. And before I go into the findings, uh I just want to say that since I've been working on it with brilliant uh data scientist, Joe White on the project, it's been just wonderful to see the amount of interest that this project gets from both academia and policymakers around the world who we know use our index to inform their national A I strategies and decision, which is amazing for us. And so in terms of its structure, we collect indicators uh data sorry, over 111 different indicators that we organize across three pillars and seven pillars that cover everything from research to development, talent, infrastructure, operating environment, government strategy and commercial ecosystem. In terms of the ranking uh for the latest iteration of the index, these are the top 10 nations and we see that the US ranks first on all pillars of the index and really leads by a strong margin compared to everyone else China comes second and it's the only country to get close to challenging the US in some areas. And Singapore comes third and Singapore ranks really well on all capita indicators. So all indicators um that kind of measure A I capacity uh in relation to the country's population and and uh economy size. And this is a good example for how a country that is perhaps smaller in terms of population and economy um can really outperform on A I and is uh a really strong and dynamic A I hub like Singapore is and talking about smaller economies, we are able to differentiate between intensity and scale as part of our index analysis. And we're able to do so by isolating per capita indicators. So like I said earlier, we don't just look at for example, the sheer number of data scientists in our country, but we also look at the number of data scientists in relation to the country's population. And by doing this, we see that uh Singapore tops the list when it comes to intensity. Uh but there are other countries like Israel, Switzerland, Sweden, Korea, Finland, and a few others that really outperform on A I. Despite being smaller countries, when we look at scale, obviously the US and China lead the rankings and I know I have to wrap up soon. But given that the 2024 edition of the index will launch in less than two months. I thought I'd give some preliminary findings from the the new iteration. And I've selected a couple of indicators that I thought were most interesting uh also make it regionally relevant to Asia given the opportunity today. And so this is the first one and this is from our com uh commercial ecosystem sub pillar. Um And this is looking at private investment in A I and we can see that Asia excluding China makes up 2.6% of global private investment in A I, which is very much dominated by the US as we can see here, which I think uh makes up around 66%. Uh then China is around 9%. Uh And the rest of Asia is 2.6% and it has been declining uh slightly over the past couple of years, whereas China and the US have been growing and so zooming in on uh Asia. Um this is uh a private investment in A I in the region. Again, excluding China is dominated by Singapore, Korea and India and Japan to a lesser extent. Um although yes, it has been declining over the past couple of years as you can see more clearly here. And then lastly, in terms of talent, this is a new indicator that we have in the index which is looking at the retention rate. Uh so looking at talent retention and not just talent growth, um and we're able to access data from a company called Dey Uh and this is showing that Singapore's capacity for retaining talent in A I has remained relatively stable over the past few years compared to um I guess other countries in the region like Korea, Japan and Taiwan, although its overall capacity, despite being quite high, around 70% is a little bit lower than that of other countries in the region which gets gets closer to 8 80%. Sorry. And so this is it for me, stay tuned for the September 2024 launch with more and improved indicators with an expanded list of countries as well. Um And yeah, look out for the new index on the Tortas media website and I'll hand over that to Ellie. Thank you so much.

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