In the wake of a seismic shift in global fintech dynamics, Asia has emerged as the undeniable nucleus of innovation. With its vast population share and a burgeoning user base, the region embodies the forefront of fintech evolution.

The COVID-19 pandemic has served as a catalyst, hastening digitisation throughout Asia, notably in Southeast Asia, where over 60 million people have swiftly adopted digital technologies. In addition, a significant portion of East Asia & Pacific (19 per cent) and South Asia (32 per cent) remain unbanked, indicating ample room for further growth. 

Businesses and investors seeking growth amid uncertainty gravitate toward Asia’s thriving fintech sector. Despite a global decline in fintech venture capital, Asia-Pacific stands resilient, maintaining investment levels. This resilience positions Asia at the forefront of fintech innovation, potentially surpassing North America by 2030.

BCG forecasts that by 2030, Asia will lead the global fintech revolution with an impressive 27 per cent Compound Annual Growth Rate, surpassing North America. Despite currently holding a modest two per cent share in global financial services revenue, the fintech sector is projected to reach US$1.5 trillion in annual revenue by 2030, comprising nearly 25 per cent of global banking valuations. 

Competition for dominance in the Asian fintech space intensifies, which is also seen by the example of the region’s megacities that most often appear at the top of the global fintech ratings.

Competitive landscape: Fintech megacities in Asia

China’s major cities, though diverse, collectively form a unified fintech landscape, primarily focused on the domestic market. While Chinese fintech experienced explosive growth from 2013 to 2018, recent years have slowed down, attributed to stringent national regulations and dominance by tech giants like Ant Group and Tencent.

Notably, Beijing stands out as a vibrant venture capital and startup hub, boasting top-tier talent and extensive access to capital. With its concentration of national fintechs and numerous unicorns, Beijing maintains a pivotal role in global fintech, reflected in its consistent top ranking in fintech hubs.

Also Read: Unlocking Southeast Asia’s financial potential with AI-powered fintech

Hong Kong emerged as a formidable player in the Asian fintech arena, distinguished by its robust regulatory regime, state support, and large-scale fintech events. Despite its relatively small size compared to mainland Chinese cities, Hong Kong boasts a substantial number of registered fintech companies, surpassing even Shanghai and Beijing in certain metrics. Particularly noteworthy is its remarkable post-pandemic growth.

Seoul presents a strong contender to Hong Kong, boasting a sophisticated regulatory environment, government support, and rapid industry growth. While both cities are on par in many aspects, Seoul stands out for its ability to attract larger investments, further bolstering its fintech ecosystem.

As the capital of Japan, Tokyo holds significant potential in the fintech sphere, leveraging its high-tech manufacturing expertise and widespread digitalisation. However, Japan’s already advanced digital financial landscape presents challenges for local fintechs to achieve extraordinary growth compared to neighbouring regions.

Repeatedly hailed as Asia’s premier fintech hub, Singapore stands out for its thriving fintech market, which is expected to exceed US$35 billion this year. The country is home to global fintech giants and large international events. With robust regulatory frameworks, extensive international relations, and post-pandemic growth surpassing Chinese competitors, Singapore solidifies its pivotal role in the regional fintech ecosystem.

India’s Silicon Valley, Bengaluru, emerges as a frontrunner in the Asian fintech race, boasting unparalleled growth and leadership in key metrics. Bengaluru is also considered to be the most concentrated region of fast-growing tech startups in India.

With a developed IT sector, which is evaluated at more than US$100 billion, the city is attractive for fintechs. Being not far behind, Mumbai forms a formidable fintech centre, propelled by India’s burgeoning fintech ambitions.

Dubai emerges as a significant hotspot on the Asian fintech map, leading global rankings in innovation and market size. Supported by progressive business reforms and infrastructure development, the city is one of the key players in shaping the future of fintech in the Middle East.

Also Read: Cross-border payments: Can incumbent banks compete with fintechs in Asia?

The prospects for Chinese and Indian megacities in claiming regional fintech leadership appear challenged by several factors. Despite a turn towards greater openness to foreign capital and increased local companies’ expansion into international markets, significant barriers remain unresolved at the domestic level.

These barriers necessitate comprehensive solutions that involve coordination across numerous institutions and a holistic approach. Achieving a fully-fledged resolution to these issues is likely to be a lengthy process, extending beyond a mere few years. 

Looking ahead

In the dynamic realm of Asian fintech, Singapore has long been a leader with its cohesive ecosystem, yet it may further improve its investment environment to cement its status. Meanwhile, Dubai’s rapid ascent in the global fintech arena presents a formidable challenge fueled by efforts to attract businesses and expand influence beyond the Middle East and Africa.

As the landscape evolves, the region’s diversity remains crucial, with current hubs like Singapore in Southeast Asia, Dubai in the Middle East, Bengaluru in South Asia, and Beijing in East Asia likely to share the leadership.

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This article was first published on February 22, 2024

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In her keynote speech on the first day of Echelon X, Addo AI CEO and Co-Founder Dr Ayesha Khanna discussed how artificial intelligence (AI) is being used today in businesses and how it impacts organisations.

She divided AI into three categories: One that makes humans more productive, another that makes machines more productive, and finally, one that makes AI more productive.

“If you think about any business and divide it based on how much work is done by labour, machines, and systems, then you can find the right interventions to use Generative AI,” Dr Khanna said.

In the context of AI that makes humans more productive, while the general public might be familiar with names such as ChatGPT or Gemini, according to Dr Khanna, the next big step is Enterprise GPT.

“As a niche AI consulting firm, we work with some of the world’s largest healthcare and financial services companies. We’re noticing that people don’t just want one AI assistant like ChatGPT. They want an entire Enterprise GPT stack,” she explained.

Also Read: IN PHOTOS: Highlights from the Echelon X Day 1

“They want to know how to embed Generative AI throughout the organisation. Is this happening already? Ninety-nine per cent of companies don’t do this. So, that’s a huge opportunity.”

Echelon X was held on May 15-16 at Singapore Expo Hall 2. The event aims to empower startups, investors, corporates, SMEs, government institutions, and other ecosystem stakeholders with tools and insights. This year, it features 150 speakers and four stages.

AI for inclusivity

On the first day of Echelon X, another notable session on the implementation of AI is a keynote speech by Dr. Leslie Teo, Senior Director, AI Singapore.

The organisation is a national platform whose mission is to build national AI capabilities. Dr Teo explained that there are elements to the work that AI Singapore is doing, from research to training to building AI products, including an inclusive multilingual model called the SEA-LION (Southeast Asian Languages in Just One Network).

According to Dr Teo, there are several reasons why having a localised LLM is crucial for the region. One includes the beginning of the era of Artificial General Intelligence (AGI), a type of AI that can perform a wide range of cognitive tasks at a level on par with or even better than humans. As one of the various definitions of strong AI, this ability contrasts with ‘narrow AI’ designed to perform just specific tasks.

Also Read: Senior Minister of State Tan Kiat How: Tech ecosystem can flourish with the right talents and skillsets

“We are a step closer to AGI, and it will have a huge impact; it’s foundational. One way of thinking about that foundational impact is by measuring the impact on the region’s economic activity,” Dr Teo explained.

Apart from that, there was also a problem of inclusivity and benchmarking, which is currently mostly done in English.

“We know that most models are built by teams in the US and China. Nothing is wrong with this, but there are very few teams from this part of the world. There are very few multilingual models, especially focused on Southeast Asia. This is true for both open and closed-source models,” Dr Teo said.

“Essentially, our goal and mission is not to compete, but to complement.”

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Toxic positivity? That seems a bit harsh when talking about Artificial Intelligence (AI), especially given that all modern businesses aspire to be data-driven in both strategy and execution.

Indeed, over the last decade or two, data has become almost universally regarded as a key corporate asset and an essential input to quality decision-making. And now, with the rise of Generative AI, there is an argument to be made that we’re reaching new levels of insight and productivity.

That said, the increasing importance of data as an asset has resulted in significant overheads being required for its protection. Whether we’re talking about security, regulatory obligations, or simply data integrity, it’s clear that there are plenty of risks and concerns associated with data and its downstream contribution to AI.

In recent times, the concept of data as a liability, or even “ethical AI”, has also raised its head, albeit usually in terms of its strategic value and what might happen if it was compromised in some way. The prevailing analogy here changes from “data is the new oil” to “data is like uranium”, both powerful and dangerous. Savvy data practitioners now realise that governance, while never sexy, has taken on a new and heightened importance in the age of AI.

What effective data practitioners know: Context matters

Yet that’s not quite what we’re talking about here. For me, the idea of toxic positivity being applied to data takes two forms – context and presentation. Likewise, the broader concept of toxic positivity is a social construct that appeals to popular culture and the zeitgeist of today — why wouldn’t it pertain to data and especially AI, especially given its more personal interface?

Also Read: With AI comes huge reputational risks: How businesses can navigate the ChatGPT era

Thinking firstly in terms of context, it’s easy to see how many data practitioners become enamoured with their analyses and reports and are blinded to more mundane considerations like relevance and impact. This type of toxic positivity stems from the idea that data is the sole (objective) truth and is, therefore, unassailable. Overconfidence in your data and algorithms breeds an unwarranted certainty around the insights and can yield fatally flawed decisions.

The solution to this problem is to maintain a healthy scepticism towards prima facie answers and to apply common sense and experience in equal measure. In a flashback to my management consulting days, data should be used to prove or disprove the hypothesis, not the other way around.

An AI wake-up call: always question the path of least resistance

In recent times, though, a more insidious threat to decision-making integrity has emerged in the form of Generative AI solutions and, more specifically, their user interfaces. The challenges with AI are both many and well-identified and include a lack of explainability, poor transparency, and variable data quality, to name a few.

Less obviously, a “positivity” problem now presents itself when we consider the form (or presentation) of AI’s responses – they are delivered in such a prescriptive and authoritative manner as to silence any debate on their value or correctness. Here is where the foibles of the technology tend towards positive toxicity – attractive, easy answers that are presented as compelling and “right” answers are the easy option for time-poor analysts and passive insight consumers.

Also Read: Can generative AI usher us into the gilded age of ad creativity?

This problem is much harder to solve, primarily because Generative AI has such broad applicability, with no clear signature of its usage. Likewise, without anyway of knowing if answers are right or wrong, users will naturally lean towards the path of least resistance. Unfortunately, once headed down this path, it is very hard for them to turn back.

To get the most value from AI, never forget the data fundamentals

The assertions above aren’t intended to question the value of AI, data, or data-driven decision-making for that matter. The right knowledge, thoughtfully applied, can illuminate a decision with new possibilities. Rather, it’s to highlight one of the fundamentals of analytical practice which has always existed – understand your business first, and only then seek relevant and considered insights.

Your business doesn’t exist to “consume insights” or to “leverage AI”. It exists to satisfy customer needs while simultaneously generating profits. Thus, the task of stewardship falls to the thoughtful AI and data practitioner who understands how these capabilities support the creativity, productivity, and tenacity required for business success.

To paraphrase Pablo Picasso’s famous quote from 1964 “Computers are useless, they can only give you answers”. The enlightened leader (and analyst) should, therefore, spend just as much time asking “why” the analyses matter versus “what” the AI says.

Toxic positivity comes in the form of the attractive soapbox spruiker standing on the corner, telling you they have all the beautiful answers (whatever the question may be). At Domo, we often get our customers to focus on “data curiosity” – it’s never been more important.

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Singapore-based Web3 infrastructure provider Chainstack has secured an undisclosed sum in strategic investment.

The investors are SBI Ven Capital, Sygnum, Azimut Group, Unicorn Factory Ventures, and Ventech Ventures.

Also Read: Is Web3 just another ‘hype’ or will it unlock a multi-trillion dollar opportunity in fintech?

The company will use the money to advance its product offerings, mainly focusing on white-label solutions crucial for businesses entering the blockchain landscape. These include making the platform more user-friendly and automating the processes to streamline operations and improve efficiency across its services.

Founded in 2018, Chainstack offers a suite of services connecting developers with Web3 infrastructure, powering applications in DeFi, NFT, gaming, and analytics. Chainstack enables companies (from startups to large enterprises) to cut down the time to market, costs and risks associated with creating and scaling decentralised applications.

Chainstack’s offerings encompass integrations with over 25 public blockchains, four consortium networks, four appchain protocols, and partnerships with all major cloud providers. It serves over 100,000 Web3 developers.

Also Read: The race of Web3 and crypto infrastructure vs big tech

Geographically, Chainstack operates in 12 regions and handles over 100 billion requests monthly.

“We anticipate a significant shift in the blockchain infrastructure market towards commoditisation, which we believe will lead to better price performance and enhanced accessibility, greatly benefiting users and developers alike,” Chainstack CEO Jan-Jaap Jager.

The post SBI Ven Capital joins Singapore Web3 infra startup Chainstack’s strategic round appeared first on e27.

Indonesia is at an important juncture in its electric vehicle (EV) transition, with a total addressable market already exceeding US$20 billion and an urgent need for infrastructure development to sustain rapid growth.

Despite impressive advancements, including hundreds of high-powered general charging stations, the country is still playing catch-up with ambitious targets for EV infrastructure.

That said, the nation’s strategic position is reinforced by its substantial nickel reserves, essential for EV battery production, surpassing those of other resource-rich countries and underscoring Indonesia’s global advantage in raw materials.

But to fully bring the local EV industry into the mainstream, Indonesia must craft supportive policies and strengthen its commitment to local production. It must ensure that the local ecosystem can meet the stringent component requirements and invite active participation from global investors.

Also Read: Infographic: Why the future of consumer goods lies in the use of AI

In parallel with a landmark investment into local EV two-wheeler company MAKA Motors in July 2023, AC Ventures (ACV) released a marquee report titled Indonesia’s “Electric Vehicle Outlook: Supercharging Tomorrow’s Mobility” produced in partnership with the Electric Mobility Ecosystem Association. The landscape has evolved over the past year, which is why ACV has created an easy-to-digest visualisation of where the sector stands today.

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Editor’s note: e27 aims to foster thought leadership by publishing views from the community. Share your opinion by submitting an article, video, podcast, or infographic.

Join our e27 Telegram group, FB community, or like the e27 Facebook page.

Image credit: AC Ventures

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