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Tag: Fortune Innovation Forum

  • Syfe CEO: Fintech founders need to focus on trust if the sector is to reach its full potential | Fortune

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    The fintech industry moved into the modern era from something deeper than just better technology. The Global Financial Crisis of 2008 triggered a crisis of trust. For millions of consumers and businesses, the crisis revealed a need for greater transparency. A new generation of financial services companies–fintechs–stepped into the gap promoting not just efficiency and lower costs, but transparency and accessibility as well.

    This approach has delivered real results: The International Monetary Fund finds that digital finance not only increases financial inclusion, but is also associated with higher GDP growth and, in turn, helps create a more equitable global financial system.

    The fintech industry has now matured, as shown by successful industry forums like the Singapore Fintech Festival and Hong Kong Fintech Week. The question has changed: It’s no longer whether fintech can disrupt; it’s whether fintech can build enough trust to manage and move the world’s money, and achieve the sector’s full potential? 

    I believe we’re at a crucial inflection point. Fintech’s potential—business, social and economic—depends entirely on earning people’s trust to bring more of them, and their finances, into the system. 

    Now is the greatest opportunity

    Fintech is in the middle of a turbo-charged era: AI-driven efficiencies and personalization, instant decentralized settlements, and a fully digital wealth management experience, all unthinkable a decade ago, are now on the way. 

    Basic trust has already been established. One example: across age groups, new technologies have significantly reduced the need for physical cash, if not made it near-nonexistent, in many economies. 

    Yet it’s a substantial leap to go from trusting a platform to make a simple payment to trusting it to manage your retirement savings. As technologies grow more powerful and personal, trust is increasingly the gatekeeper to further adoption. The greater responsibility raises the bar for trust in complex financial systems and puts pressure on companies to demonstrate transparency. 

    As algorithms and technology become more sophisticated, customers must understand exactly how decisions are made, where their money is held, and how their data is used. If fintechs cannot bridge the gap between these rapid advancements and clear, jargon-free information and education, mass adoption will falter. 

    The limitation won’t be the technology itself, but the lack of public trust, which ultimately constrains the industry’s potential to improve financial health and inclusion. 

    After all, a crisis of confidence can erase decades of work in mere days—just think back to 2023 and the Silicon Valley Bank crisis. Trust has to be consciously engineered into every platform layer.

    Engineering trust into the business model

    In an industry where relationships with users are largely digital, trust must be engineered through design. This requires modern fintech platforms to be built on three non-negotiable pillars:

    First, fintechs must continue to open up access to their services. Platforms must lower traditional barriers to entry—high minimums, complex processes, early redemption fees and the like—to ensure that no one is excluded from wealth creation. 

    Second, platforms must offer their users guidance. Financial confidence comes from clarity, not endless choice. Platforms must combine digital simplicity with human reassurance and expertise when needed. 

    At Syfe, we’ve tried to put human expertise front and center, such as by offering discretionary management by our in-house experts on Managed Portfolios, but scaling it with technology for maximum reach. The personalized stock updates, powered by AI, are a good example of that process in action. 

    Fintechs also need to build financial literacy, which remains a significant challenge even in advanced markets. Take Singapore: A Fidelity International found that just 22% of its residents felt confident about their ability to invest money. Education and jargon-free information are essential ingredients to empower people to build a better financial future.

    Finally, fintech platforms must be affordable. It sends a clear signal: That they succeed only when their customers do. In an industry where hidden fees can erode confidence, cost efficiency ensures that technology can scale access without exploiting customers. 

    Putting trust at the center of a business is the only sustainable growth strategy, and not just a moral stance. Customers who feel empowered and secure are more likely to recommend a service to others, stay through market volatility, and continue to adopt new products.

    The imperative over the next decade is clear. If fintech is to fulfil its promise of democratizing access to better financial outcomes, it must make trust the organizing principle of its business. This requires investment, patience, and the courage to trade short-term disruption for long-term credibility. Trust will be the hardest metric to win, but it’ll be the one that will matter most.

    The opinions expressed in Fortune.com commentary pieces are solely the views of their authors and do not necessarily reflect the opinions and beliefs of Fortune.

    Fortune just hosted the Fortune Innovation Forum in Kuala Lumpur, Malaysia, where business leaders and policymakers from around the region debated and discussed strategies for a world marked by AI, protectionism, and geopolitical tensions. Check out our mainstrage sessions here and oureditorial coverage here!

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    Dhruv Arora

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  • Jefferies’ Chris Wood called Japan’s crash and the U.S. housing bubble. He’s now warning of an ‘AI capex arms race’ | Fortune

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    Christopher Wood has a track record of spotting speculative bubbles. He called the dotcom boom, Japan’s credit bubble and the U.S. housing bubble before many of his contemporaries. So when he warned of an “AI capex arms race” at the Fortune Innovation Forum in Kuala Lumpur, Malaysia on Tuesday, the audience paid attention.

    Wood, now the global head of equity strategy at Jefferies Hong Kong, said that the arms race began in 2023 when Microsoft invested in OpenAI. He argued that investors are missing a crucial point: That nearly all the money made so far is accruing not to the companies building AI products, but to those selling the infrastructure behind them.

    “You want to own what I call the picks and shovels of AI,” Wood said. It’s companies like Nvidia, those producing semiconductors and building data centers, that have made real profits from the AI boom. 

    “But it’s completely unclear to me who’s going to monetize and make money out of all this capex,” Wood continued. 

    This sets up what he views as an almost-inevitable over-investment bust—though when markets finally lose patience with ballooning spending without results is unknown. 

    Wood’s already repositioned his own portfolio. He recently sold his Nvidia holdings, not necessarily because he believed shares have picked, but because their five-fold gains already priced in extraordinary expectations.

    His AI exposure is now concentrated in China, where he believes companies are approaching the technology more pragmatically. “You need two things to do AI: compute and energy,” he said. “The Chinese are far more ahead in energy than the U.S. is ahead in compute.”

    While the U.S. still leads in terms of the power of its advanced chips, Washington’s semiconductor export controls, in place since late 2022, may have inadvertently strengthened China’s position. By cutting Chinese firms off from U.S. chips, the policy both deprived American tech companies of their biggest customers and jolted Beijing into accelerating its domestic semiconductor ecosystem.

    “[Nvidia CEO Jensen Huang] has made it quite clear that Huawei is a much more formidable competitor than was the case three years ago,” Wood noted, adding that controlled Nvidia chips had made their way to China anyway through secondary channels, despite U.S. controls. “It’s a massive own goal.”

    Huang has repeatedly praised Chinese chipmakers, including Huawei. He called the Chinese tech giant “one of the most formidable technology companies in the world” in April.

    China’s AI strategy is also diverging from the U.S. Rather than chase the elusive goal of artificial general intelligence, Chinese firms, spurred by successes like DeepSeek, are channeling resources toward practical, commercially viable applications, many built on open-source models. “They’re not trying to build the perfect LLM,” Wood said. “It’s all about applications.”

    U.S. tech giants, by contrast, are pouring money into parallel efforts to build proprietary frontier models, a shift that is fundamentally altering their economics. For years, Big Tech companies rested on “asset-light” business models, each in their own space. Now, Wood said, the hyperscalers are competing in the same AI space while moving to “asset-heavy” models.

    Other panelists at the Fortune Innovation Forum echoed Wood’s comments on China’s AI strategy. “China is focused a bit more on diffusion, while the U.S. focuses more on perfection,” Chan Yip Pang, executive director at Vertex Ventures SEA and India, said on Monday during a discussion on the competition between open-source and closed-source models.

    Why are U.S. tech giants spending so much? Opportunity is one answer. Fear is the other. “They’re terrified of being disrupted,” Wood said. “There’s massive FOMO. That’s what’s driving this arms race.”

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    David Austin

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  • AI’s power and water consumption is worrying the agriculture sector: ‘Don’t forget that it is also required for us to grow food’ | Fortune

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    Nations around the world are rapidly building out the infrastructure needed to take part in the AI boom–including massive, multibillion dollar investments in data centers, which house and manage the servers needed to process, store and share information.

    Yet data centers guzzle up energy and water, needed to power servers and cool systems. And that may end up putting strain on another industry that’s just as important for a country’s future: Agriculture.

    “The electricity that we’re using for our data centers and AI chips? Don’t forget that it is also required for us to grow food,” said Gerard Lim, CEO of Agroz, a vertical farming startup, at the Fortune Innovation Forum in Kuala Lumpur, Malaysia, on Tuesday.

    Singapore, for example, briefly paused data center investments in 2019 due to concerns about electricity use and water consumption. And in the U.S., electricity prices are rising in states with greater data center construction, like Virginia.

    “Don’t forget the humans in the equation—because the energy all these data centers are utilizing is going to leave the human sectors out at some point,” Lim warned.

    Food security

    On top of resource competition, burgeoning populations and rising wealth also means higher demand for good quality food.

    “What’s driving the rapid demand for food is our changing eating habits. As we become richer, we want more protein,” said Richard Skinner, a partner in private capital from Olivia Wyman.

    Lensey Chen, Asia-Pacific president at Novonesis, a biosolutions company, echoed these concerns. “By 2050, there will be an additional 50% [increase] of demand to feed the world’s population, and it’s critically important to increase the yield, increase output from existing resources,” she said. 

    New technologies could help to fill the gap. Lim claimed that Agroz had been able to use technology and controlled environments to increase yields by as much as 500% while using 20 times less water compared to traditional open-field farming. “Technology and innovation are very important for us to grow in less land and use less resources,” Lim said.

    Yet Skinner said that state-of-the-art innovation might not be the only, or easiest, way to boost agriculture productivity.

    “We want to have to have technologies we can deploy today,” Skinner argued, citing greenhouses, irrigation techniques, fermentation, and better data monitoring for livestock as well-understood technologies that have yet to be widely adopted in Asia. 

    Rice farming, for example, contributes 8% of the world’s carbon emissions, due to how farmers flood rice fields, Skinner added.  The water in these rice fields creates a low-oxygen environment which kills most weeds and keeps pests away. But the anaerobic conditions cause microorganisms to produce and release methane, a greenhouse gas.

    Instead, Skinner suggested that farmers can use drip irrigation, an efficient method of applying water slowly and directly to the soil around the roots of plants. This would reduce water consumption and cut greenhouse gas emissions. 

    Tastier food

    While it’s easy to focus on producing more food, or more sustainable food, when talking about the agricultural sector, panelists noted that it was just as important to discuss making food healthier, more nutritious, or just tastier.

    “We go food shopping not just because it’s sustainable. It’s because it’s tasty, it’s nutritious, it’s healthy, right?” Chen said. She continued that the company was now working with the food industry–including Noma, a three-Michelin-star Copenhagen-based restaurant, to develop new ways to develop food. “They are masters of taste, and we are masters of fermentation,” she said.

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    Angelica Ang

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  • Younger customers are venturing back to real-world stores, says AS Watson CEO Malina Ngai: ‘They want to be able to touch the product’ | Fortune

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    AS Watson was established in 1841 in Hong Kong, the year the British took over the territory. Almost 185 years later, the brand is now a health and beauty retail giant, with close to 17,000 outlets across 31 markets, including mainland China, Malaysia, the UK, Turkey and even Ukraine.

    “We are a people company,” Malina Ngai, group CEO of AS Watson, said at the Fortune Innovation Forum in Kuala Lumpur, Malaysia, on Monday. Ngai acknowleged the company’s long history–including how the company endowed Sun Yat-sen, who later led the 1911 revolution agaisnt the Qing dynasty, with a medical scolarship–yet argued that AS Watson had to remain forward-thinking.

    “Heritage gives us credibility, so people trust us, but only if we stay relevant [will we] be able to stay alive,” Ngai said.

    The secret sauce to successfully operating in so many markets, Ngai argued, came from understanding their customers. In Southeast Asia—which Ngai described as one of AS Watson’s “growth engines”— consumers are young, digitally-savvy and conscious about health and beauty. They also love new campaigns and product launches. As such, Watsons, AS Watson’s main drugstore brand, has rolled out campaigns such as “Kaw Kaw Deals” in Malaysia, replete with a catchy jingle of the same name by local personalities Jinnyboy and Ayda Jebat.

    Through market surveys, Ngai also found that many young customers in the region enjoy shopping at brick-and-mortar stores, despite a variety of online shopping options. “For younger customers, they want to be in the store, they want to get consultancy, they want to be able to touch the product—and this is what we can offer,” she said. 

    Aside from popular J-beauty and K-beauty products, Watsons also offers an array of halal-certified skincare and beauty items for Muslim consumers in markets like Malaysia and Indonesia.

    C-beauty has also seen a spike in popularity among Southeast Asian consumers. Chinese beauty brands are “strong in technology and social media, and they get engagement and popularity within Southeast Asia very quickly,” Ngai explained.

    ‘People-first’

    Ngai emphasized the importance of empowering employees. “In the company, if everyone is a leader, it will be a very powerful company. This means they know exactly the [company’s] purpose, they know how to collaborate, and they care for each other,” Ngai said.

    Still, AS Watson is moving to adopt new technologies across its team, including launching a company-wide generative AI protocol in September. “AI used to be just with my data team, the programmers—but now Gen AI is for everyone,” Ngai said.

    As the company approaches its 185-year milestone in 2026, Ngai shared her hopes for AS Watson’s future. “I don’t normally dream about work over the years. I sleep quite well, but recently, I dream a lot about 185 years,” Ngai said. “[I want AS Watson to] be an organization that can stay fit for the future, the next 180 years.”

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    Angelica Ang

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  • Leading China VC Kai-Fu Lee warns an investor reckoning is coming for unprofitable AI companies

    Leading China VC Kai-Fu Lee warns an investor reckoning is coming for unprofitable AI companies

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    The halcyon days where venture capitalists were content forking over billions to the latest AI startup, as researchers burned through cash with little to show for it, may be all but over. A “reckoning” is coming soon for AI companies that fail to turn a profit as the new technology matures, Kai-Fu Lee, chairman and chief executive of Sinovation Ventures, said at the Fortune Innovation forum in Hong Kong on Wednesday.

    Lee said too many large language model (LLM) startups focus on striving for breakthrough advances and too little on commercializing their work. “A lot of the LLM companies out there are run by researchers who care only about making a great model,” he said in a conversation with Fortune editor-in-chief Alyson Shontell. “That science fair phase needs to end.”

    If there’s one aspect the three leading U.S. megacap tech stocks all have in common, it’s that they successfully monetized an emerging technology—Microsoft with the personal computer, Apple and Google with the smartphone.

    A former Google China president and himself a researcher in the field, Lee founded his own AI startup in March 2023. The firm, named 01.AI, was valued at more than $1 billion in less than eight months.

    Lee said his own former employer Google serves as a cautionary tale. Even with the densest network of AI talent found in the world to this day, he argued that Google lost its lead to OpenAI because it squandered time and resources indulging all of its employees’ competing plans.

    “If you have too many researchers and a culture where everybody can try their ideas, you’ll quickly run out of money as a startup,” he said. 

    Huawei’s focus vs Google’s ‘let one hundred flowers bloom’

    Lee argued that in order for his company to one day count among the world leaders in the field, it needs to be brutally efficient with every dollar it spends.

    On Wednesday, the AI expert pointed to Huawei as an example of how such focus might work in practice. China’s leading telecom equipment maker seized on an obscure advance by Turkish IT researcher Erdal Arıkan, investing its efforts almost exclusively in commercializing his polar code breakthrough. This allowed them to eventually surpass larger western competitors like Ericsson and go on to control the bulk of the 5G mobile networking market.

    “That made all the difference,” Lee said. “We’re taking that same approach to be very, very diligent to save GPU [costs].”

    Thanks to its focus on efficient execution, he believes 01.AI—which publishes all its research on open sites like Hugging Face—has narrowed the gap to American companies like OpenAI from eight years to less than twelve months in just a year’s time.

    AI rivals that instead embrace Google’s strategy of “let one hundred flowers bloom”, as Lee phrased it, would by comparison struggle to reach profitability. 

    “There is a point of reckoning when investors are going to say: What do you have to show for yourself?” said Lee. “What’s your P&L? What’s your revenue? What’s your growth? When do you break even?” 

    If an AI startup doesn’t have a convincing answer, then its “science fair” days are over.

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    Christiaan Hetzner

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  • India speaks over 100 languages. Microsoft wants AI to bridge its linguistic gaps

    India speaks over 100 languages. Microsoft wants AI to bridge its linguistic gaps

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    Depending on how you count, India has at least 120 languages, and another 1,300 “mother tongues,” an Indian term that refers to local dialects. The country’s government recognizes 22 languages but primarily operates in just two: Hindi, mostly spoken in India’s north, and English. That excludes tens of thousands of Indians who speak neither.

    Enter Microsoft’s AI for Good initiative—the tech giant’s umbrella program that tries to use AI to solve problems in health, environmental protection, and human development. The U.S. company has used India to pilot several novel uses of the new technology, such as an app that uses AI to tell farmers the best time to sow seeds or a model that uses satellite images to forecast how a natural disaster might hurt a vulnerable population. 

    But Microsoft and its AI researchers are particularly interested in navigating India’s linguistic challenges, hoping it might unlock breakthroughs elsewhere. “India’s complexity makes it a test bed for multilingual settings everywhere,” says Ahmed Mazhari, Asia president for Microsoft. “If you can solve and build for India, then you can solve and build for the world.”

    Small languages and large language models

    The Jugalbandi chatbot, which Microsoft debuted in May 2023, is one of AI for Good’s flagship projects. The chatbot is targeted to rural farmers—specifically those who live in areas that don’t speak India’s more popular languages—who want to learn about or access public services, such as applying for a scholarship.

    Jugalbandi uses a large language model, developed with local research lab AI4Bharat, to parse a query, uncover the relevant information, then generate an easy-to-understand answer in the user’s local tongue. (Currently, Jugalbandi can translate 10 of India’s 22 official languages.)

    (Fortune earlier featured Microsoft’s work with AI and Jugalbandi on its 2023’s “Change the World” list.)

    Another Microsoft initiative called VeLLM, or “Universal Empowerment with Large Language Models,” aims to improve how GPT, the OpenAI-developed model that underpins ChatGPT, works when using less-popular languages. Most of today’s large language models work best in a handful of major global languages—primarily English and Chinese—because so much data are in those two languages. It’s harder to train AI on so-called low-resource languages, where data is scarce or non-existent.

    VeLLM is the foundation for other experiments with AI, like Shiksha, a generative AI bot that helps teachers create new curricula in non-English languages quickly, freeing up more to be spent on teaching. 

    ‘Participatory’ design

    Microsoft engineers like Kalika Bali, principal researcher for Microsoft Research India, are wary of cutesy technology solutions that don’t reflect how rural Indians live their lives.

    Technologists have long tried to use the South Asian country as a testing ground to prove that digital technologies—cheap laptops, affordable internet, and smartphone apps—can improve quality of life in rural India.

    Yet not every initiative was a success, Bali notes dryly. She remembers one project in which designers from a development organization tried to create a game to help women farmers in India access important information.

    “The women gave that person such a disdainful look,” she said. “They said ‘Do you think we have time for playing games?’”

    Instead, Bali says she and her team pursue a “participatory” design process. “We spend a lot of time with the communities that we are working for, trying to have them say what they want out of a technology, or how they want to solve a problem,” she says. 

    Not just social good

    Microsoft, of course, isn’t just interested in AI for its potential for social good. The U.S. tech giant is developing its own AI products, hosted on its Azure cloud computing system. It’s also a key backer of ChatGPT developer OpenAI. The hype around AI has helped lift Microsoft’s stock by 65% over the past year, pushing its market value to $3 trillion, making it the U.S.’s most valuable company. 

    Mahzhari sees a lot of opportunity for Microsoft in Asia, where there is “an incredible pace of change and transformation across industries and geographies.” He points to several examples where Asian companies have turned to Microsoft’s generative AI services: Lazada, the Southeast Asian e-commerce platform owned by Alibaba, used Microsoft tools to create the first e-commerce chatbot in Southeast Asia. 

    Still, even if Microsoft’s experiments in India don’t do much for the company’s bottom line directly, they provide important lessons for the company going forward.

    “Our partnerships under AI for Good and other pilot initiatives enable us to pick up early signals for advancing AI security and safety,” Mahzhari says. Those lessons are then used to develop “policies for much-needed guardrails” on the new technology. 

    Bali knows that you can’t separate her work from Microsoft’s overall business interest in AI. 

    “These are early forays in terms of how to make people who do not have access to technology get on the technology wagon,” she says. “Then they will become, hopefully, future technology users who would, amongst other things, also use Microsoft products.”

    Fortune is hosting the inaugural Fortune Innovation Forum in Hong Kong on March 27-28. Experts, investors, and leaders of the world’s largest companies will come together to discuss “New Strategies for Growth,” or how companies can best seize opportunities in a fast-changing world.

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    Nicholas Gordon

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