FIs (financial institutions) are typically considered to be accountable for the behaviour of AI that they use, irrespective of whether it was built or procured. -Mindforge AI Risk Management: Operationalisation Handbook Somewhere in an institution’s software stack, there might just be an AI model running on an update they did not approve. Think about the patch to your AI product that was rolled out automatically last quarter. Without you knowing, it may be posing cybersecurity, technology and possibly even reputational risks. Yet the contract with your vendor says nothing specific about it. This challenge is precisely what the MindForge AI Risk Management Operationalisation Handbook was created to address. Published as a collaborative effort by a consortium of 24 primary members and led by the Monetary Authority of Singapore, the handbook is a practical guide for how financial institutions can operationalise AI risk management, including specific risks that arise when vendors update or modify the AI they supply. When third-party vendors update their products, they may add AI features to non-AI products and services that didn’t previously have them, or change AI products or services that the financial institution is already using. This can bring AI into the organisation’s ecosystem without proper oversight and controls in place to manage the risks that come with it. These unvetted AI additions are a way shadow AI creeps into an organisation. The crux of the problem is the fact that contracts signed by financial institutions were written for software that tends to be static, predictable, and tracked through methods like release notes and change logs. AI behaves differently; it updates and evolves after you’ve officially deployed it. Accountability for that behaviour, however, sits firmly with the institution, including in scenarios like hallucinations or the exposure of customer data. Yet many contract clauses for Singapore fintechs and financial institutions have yet to address this reality. There’s no trigger in their agreements to notify when, say, an AI component is added or modified. Source: MAS   According to the handbook, requests for training data disclosures tend to get declined by vendors due to factors like data being commercially sensitive. Meanwhile, most organisations do not have a documented process to decide whether to pursue the matter further or not. Why Existing Vendor Frameworks Fall Short for AI The principle of accountability in financial services has been around for quite a while. Financial institutions have always been responsible for the conduct of their vendors. AI, however, throws a unique wildcard into the mix. It creates a specific version of exposure that existing vendor management frameworks aren’t built to handle. The handbook states, “The use of AI products or services from third-party vendors, service providers, and contractors may introduce new AI-specific risks, especially as FIs shift towards using AI as Saas.” The issue has two roots, and they compound each other. The first is opacity at the point of procurement. When you buy traditional software, you can test it and reasonably expect that what you evaluated is what you deployed. AI products, particularly foundation models accessed as a service, don’t work that way. You often have no visibility into the underlying model and no reliable way to know how vendor updates will affect your specific use cases. The handbook is direct about this: some AI products or services “may not be fully transparent to the FI.” The second problem is that AI’s opacity moves. A model you evaluated six months ago may behave differently today because the vendor retrained it or modified its guardrails. Unless your contract requires notification of material changes, you will not know this has happened until something goes wrong. None of this is bad intent on a vendor’s part, but rather reflects how AI products and services are built and maintained as live systems. The combination of opacity and continuous change means that traditional procurement due diligence is structurally insufficient for AI. Assuming the product remains stable leaves a meaningful and growing gap in your institution’s risk posture. How to Manage AI Risk in Third-Party Vendor Contracts The handbook shares that institutions can consider several factors when disclosures by third-party vendors are deemed incomplete. Indemnification As A Limited Line of Defence If a third-party vendor refuses to share details about how their AI model was trained, they may instead offer a contractual indemnification, a legal promise to cover costs if an Intellectual Property (IP) violation occurs. This can push third parties to take risk more seriously and give institutions a way to recover financial losses if something goes wrong. That said, indemnification only kicks in after the act. It does little to stop problems from happening in the first place. Institutions should also keep in mind that some AI-related harms, like risks to customer relationships or reputation, cannot be fixed with a mere payout. Testing Third-Party AI Before You Buy As part of their procurement process, institutions can test third-party AI products and services against key risk-related performance metrics. This is known as compensatory testing. It helps fill knowledge gaps about how an AI model or system actually behaves by putting it through a range of scenarios and observing where risks may emerge. In short, it can be a practical way to learn what a vendor may not tell you upfront. Getting an Outside Expert to Verify What Third Parties Won’t Show You When a third party is unwilling to share details about how their AI system is controlled or safeguarded, institutions can opt to bring in a trusted external body like an auditor to independently review and verify those elements on the financial institution’s behalf. This external attestation can confirm, for example, that the third party is meeting relevant regulatory requirements or has properly implemented recognised standards. While institutions may not get direct visibility into the third party’s systems, a credible independent sign-off can still provide meaningful assurance. Embedding AI Risk Checks Into Every Procurement Stage Managing third-party AI risk needs to be embedded across the entire lifecycle, from initial procurement through to ongoing use. When evaluating AI products and services, institutions should address any gaps in their entire procurement and risk management processes. Consider looking into information disclosures, legal review, vendor assessments, compensatory testing, and other relevant mitigating factors, including whether the third party’s AI aligns with the institution’s values and principles. Source: MAS Once a product or service is in use, financial institutions should continuously monitor its performance and periodically reassess whether its risks are still being managed effectively. If an AI product ends up being used in ways that go beyond its original scope, institutions should consider revisiting or supplementing the initial evaluation. Building on Existing Cybersecurity and Procurement Frameworks Financial institutions do not need to build their AI risk management approach from scratch. Most already have procurement and third-party risk management practices in place, including cybersecurity assessments, defined accountability structures, and processes for identifying, reviewing, mitigating and accepting risks. These existing frameworks, including legal and cybersecurity reviews, can continue to be applied when assessing AI products and services. Before creating an entirely new AI-specific function, institutions should first ask where their current processes fall short and address those gaps through targeted improvements. The Easy Starting Point The handbook suggests a sequenced approach that begins with identification, building a clear picture of which vendors in your current stack supply AI products or services, including embedded AI in non-AI-primary products. It recommends asking vendors directly to disclose whether a product includes or is connected to AI components, particularly at renewal or renegotiation points. This is a simple question that creates clarity and is an appropriate ask at any stage of a vendor relationship. The second step is standardising disclosure requests. The MindForge consortium has published an AI Card template in the handbook’s appendix. This is a structured disclosure document covering model description, intended use, technical limitations, monitoring capabilities, and training data information, as showcased below: MAS AI Card Template The AI Card Template gives financial institutions a useful starting point for gathering information about AI products and services from their vendors. Institutions are encouraged to tailor it to suit their own needs and the specific context of their third-party relationships. Source: MAS Using a standard template creates consistency and gives vendors a clear brief for what you need, making it more likely you will receive usable responses. The third step is developing a defined decision process for incomplete disclosures. Rather than making case-by-case calls without documented rationale, fintechs should establish a policy that sets out what information they require, what mitigations (indemnification, attestation, testing) they will accept in lieu of direct disclosure, and what the approval pathway looks like for products where disclosure is incomplete. This does not need to be complex. A one-page decision framework, owned by risk and signed off by legal, creates far more defensibility than the current informal approach most fintechs are using. The final step is updating contracts with existing vendors to include AI notification provisions. These may even be notification obligations tied to material changes: new AI features, significant model retraining, changes to data handling practices. This is a clause that most vendors will accept on request, and it provides the early warning system that currently does not exist. The handbook makes one thing very clear: AI changes over time, and vendors are not obligated to tell you every time it does. That means the responsibility falls on the institution to put the right processes and checks in place so that when something shifts, you find out before it becomes a problem. Featured image edited by Fintech News Singapore based on an image by on Freepik The post Singapore’s Financial Institutions Now Have a Playbook for Managing AI Vendor Risk appeared first on Fintech Singapore.

HSBC has appointed David Rice as its first Chief AI Officer amid a wider review that could lead to major job cuts in the coming years. The appointment takes effect on 1 April. Rice was previously Chief Operating Officer for HSBC’s Corporate and Institutional Banking business. The new role gives AI a dedicated leadership position at the bank as HSBC expands its use of the technology across the group. The bank plans to make generative AI tools available to all staff to simplify processes, procedures and policies, while equipping customer-facing employees with tools to deliver more personalised services. David Rice David Rice, HSBC’s new Chief AI Officer, said: “AI is going to play an ever-increasing role in HSBC’s future plans, so I am thrilled to take on this new role to help us drive forward our transformation agenda.” The appointment comes as HSBC reviews how AI could reshape parts of its operations. Bloomberg previously reported that the HSBC could eventually cut around 20,000 roles over the next several years, although the review remains at an early stage and no final decisions have been made. Some of the reductions could come from not replacing departing staff, while other changes may result from business sales or exits. Non-client-facing roles in global service centres are seen as among the most exposed, with the reported plan expected to unfold over three to five years. Georges Elhedery Georges Elhedery, Group CEO, HSBC, said: “Our customers increasingly expect their bank to deliver services uniquely aligned to their specific needs, and fast. That’s why we’re building a bank that is designed for the future. AI plays a key role in how we get there. Our ambition here is simple: we will empower our colleagues to use AI to create a personalised experience for each customer, deliver it safely, in real time and at scale, while keeping human judgement, decision-making and accountability at the core. David will be instrumental in helping us realise our ambition in this area.” HSBC also said it is expanding the remit of Chief Technology Officer Mario Shamtani as it strengthens the technology foundations needed to deploy AI at scale. This includes modernising core platforms, building a central AI platform colleagues can use to access a range of models, and leading key strategic partnerships.     Featured image: Edited by Fintech News Singapore, based on image by HSBC The post HSBC Names David Rice as First Chief AI Officer as It Weighs Job Cuts appeared first on Fintech Singapore.

Digital assets were designed around decentralisation, yet the responsibility for securing them increasingly sits with institutions. Banks, fintechs, and specialised platforms now safeguard billions of dollars in cryptocurrencies, stablecoins, and tokenised assets on behalf of customers. As digital asset markets mature, conversation is shifting from innovation to infrastructure, and, more importantly, security. Yet the biggest risks rarely originate from the blockchain itself. Most major breaches stem not from flaws in blockchain protocols but from the surrounding infrastructure, particularly the systems responsible for managing private keys. Recent data illustrate the scale of the problem. According to Chainalysis, more than US$2.2 billion worth of cryptocurrency was stolen through hacks in 2024, a 21% increase from the previous year. Nearly 44% of those losses were linked to compromised private keys, making it the single largest attack vector in the industry. The trend continued into 2025. By mid-year, more than US$2.17 billion had already been stolen from crypto services, much of it tied to compromised wallets and infrastructure attacks. A separate analysis from CertiK found that US$1.71 billion in losses during the first half of 2025 resulted from wallet compromises. The reason is simple. In digital asset finance, the private key is the ultimate credential. Whoever controls the key controls the asset. As institutions increasingly hold those keys on behalf of clients, protecting them has become one of the most critical challenges in digital asset security. When the Weakest Link Is the Private Key Many high-profile crypto thefts share a common pattern. Attackers rarely break the blockchain itself. Instead, they gain access to the private keys that unlock them. Industry reports estimate that nearly half of digital asset losses are linked to private key compromises or insider threats, elevating key management from a technical concern to a board-level issue for financial institutions. Richard Chiu, Head of Sales Engineering (Hong Kong and Taiwan) at Thales, says the core problem often lies in where keys are stored and managed. Richard Chiu “Nearly half of all digital asset losses result from private-key compromise or insider threats. A hardware root of trust moves the security boundary from vulnerable human-operated software to a hardened cryptographic environment where keys never exist in clear form.” Software-based environments remain exposed to common attack paths, including phishing, privilege abuse, and insider threats. Moving key operations into dedicated hardware changes that boundary entirely. Hardware Security Modules (HSMs) generate and store cryptographic keys within tamper-resistant hardware, ensuring they never appear in plain form outside the device. Richard says the design also addresses insider threats. “In the HSM environment, it mitigates insider threats through rigorous physical controls that offer a high standard of data access governance as well as multi-layer authentication.” Establishing a Hardware Root of Trust Institutional security rarely relies on a single control. Strong custody infrastructure combines multiple safeguards designed to eliminate single points of failure. HSM-based systems allow organisations to enforce strict governance over sensitive operations such as transaction signing or policy changes. Critical actions may adopt quorum-based authentication, meaning multiple authorised personnel must approve a request before it proceeds. “No single administrator can execute a critical operation. It requires a predefined quorum of personnel to proceed with the operation, with identity authenticated and authorized,” Richard explains. Some environments also require physical authentication devices, such as PED keys connected to dedicated PIN entry devices. These tokens provide an additional safeguard against stolen credentials. Together, these mechanisms shift trust away from passwords and administrative privileges toward hardware-enforced security policies. MPC Alone May Not Be Enough While hardware-based controls form the foundation of many custody architectures, institutions are also exploring additional cryptographic safeguards. Multi-Party Computation (MPC) has become one of the most widely discussed technologies in digital asset custody. By distributing key shares across multiple systems, MPC reduces the risk of a single point of compromise. However, purely software-based implementation introduces new operational concerns. “MPC in a purely software environment results in fragmented accountability. While mathematically sound, software-based MPC shares are still hosted on vulnerable servers and lack a verifiable audit trail.” Combining MPC with HSM infrastructure introduces a hardware-backed layer of assurance. Key shares anchored in HSMs benefit from secure storage, hardware isolation, and an auditable signing process, together with temper detection and resistance. “HSMs serve as the trusted foundation that transforms MPC into a tangible security standard capable of meeting the high-assurance expectations of regulators.” This hybrid approach allows institutions to maintain flexibility while meeting stricter expectations around governance and accountability. Security at the Speed of Modern Finance Beyond security architecture, digital asset infrastructure must also keep pace with the development of modern financial systems. Emerging use cases, including tokenised deposits, blockchain settlement networks, and digital securities now require ever-faster transaction processing than traditional custody models were designed to handle. Speed. Financial institutions must now maintain strict security controls while enabling near-instant transaction execution. “Authorised institutions can scale-out with performance demand by high-availability architectures using HSMs with load balancing and hardware-enforced partitioning,” Richard says. Even as transaction volumes rise, private keys remain confined within FIPS-certified tamper-resistant hardware, preserving security guarantees. Preparing for the Quantum Era Security planning is also beginning to consider longer-term threats. One growing concern is the “Harvest Now, Decrypt Later” scenario, where attackers collect encrypted data today in hopes of decrypting it once quantum computing becomes viable. Richard believes institutions managing long-term financial assets must prepare early. “With 61% of organisations citing ‘Harvest Now, Decrypt Later’ as a leading threat, any institution managing long-life assets has a fiduciary duty to protect that data against future quantum decryption.” The industry’s response lies in Post-Quantum Cryptography (PQC), a new set of algorithms designed to resist quantum attacks. HSM platforms that support PQC provide the cryptographic agility needed to introduce quantum-resistant signatures without replacing existing hardware. Early preparation helps ensure assets issued today remain secure in the future. The Convergence of Crypto and Banking Infrastructure As digital assets integrate with mainstream finance, the line between traditional banking systems and blockchain infrastructure continues to blur. Capabilities once considered specialised are increasingly becoming part of the core security stack used by financial institutions. Richard says the shift is already visible. “The convergence is already an operational reality. Blockchain-specific capabilities such as BIP32, SLIP-010, and support for curves like Ed25519 have transitioned from niche requirements to standard features in our HSMs.” Whether processing traditional payments, tokenised deposits, or stablecoins, the underlying requirement remains the same. Everyone needs to start protecting cryptographic keys. Hardware-based key protection therefore serves as a common security foundation for both conventional and blockchain-based financial systems. Protecting the Infrastructure Behind Digital Value Digital assets are steadily evolving from experimental technology into regulated financial infrastructure. Banks, fintech firms, and digital asset platforms now face the same challenge: safeguarding the keys that control billions of dollars in digital value. The focus has shifted from questioning whether digital assets should be part of financial services to figuring out how institutions can protect them efficiently on a larger scale. Solutions such as Thales Luna HSM aim to provide that foundation by combining tamper-resistant hardware, policy-driven transaction controls, and support for emerging cryptographic standards. In a financial system powered by cryptography, the private key remains the ultimate gatekeeper. Get it right, and the system works. Get it wrong, and the headlines write themselves. Featured image: Edited by Fintech News Singapore based on an image by Juan J. J. Labrador via Freepik. The post Private Keys Are Becoming the Biggest Risk in Digital Asset Finance appeared first on Fintech Singapore.

Alibaba and Tencent lost US$66 billion in market value as investors questioned how their AI spending could generate returns, according to Bloomberg. The sell-off came after recent earnings and strategy updates failed to give markets a clear near-term path for monetising AI. Tencent lost about US$43 billion in value, while Alibaba’s US-listed shares shed roughly US$23 billion overnight. The reversal followed a rally in Chinese AI-linked stocks, driven by excitement over agentic AI products and recent launches across the sector. That optimism faded as investors shifted focus to whether rising spending on infrastructure, talent and model development would translate into meaningful revenue. Alibaba’s latest results added to the pressure. The group is targeting US$100 billion in annual cloud and AI revenue within five years, even as investor concerns over profitability persisted. Tencent is also increasing its AI spending, adding to concerns that heavier investment could weigh on margins before returns become clearer. The sharp market reaction suggests investors are no longer rewarding AI spending alone. Attention has shifted instead to whether China’s largest tech firms can show a clearer commercial payoff from their AI push.       Featured image: Edited by Fintech News Singapore, based on image by mizkit via Freepik The post China Tech Giants Lose US$66B in Market Value Amid AI Profitability Concerns appeared first on Fintech Singapore.

UOB deputy chairman and CEO Wee Ee Cheong received S$12 million in total remuneration for 2025, The Straits Times reported citing the bank’s annual report. The package was down from S$15 million in 2024 and S$15.9 million in 2023, mainly due to a lower bonus. His base salary was unchanged at S$1.44 million, while his bonus fell to S$10.6 million from S$13.6 million a year earlier. Benefits, including transport- and event-related expenses, totalled S$42,629, down from S$46,944 in 2024. UOB said 60 percent of Wee’s variable pay will be deferred over the next three years, with 40 percent of that paid in cash and the rest in share-linked units. The lower payout came as UOB reported weaker earnings. Full-year net profit for 2025 fell 23 percent to S$4.7 billion, while fourth-quarter net profit declined 7 percent to S$1.41 billion. The bank attributed the drop in annual profit to general allowances set aside earlier in the year to strengthen provision coverage amid macroeconomic uncertainty. Credit and other loss allowances for the quarter reached S$1.36 billion. Wee said UOB will continue supporting customers through tougher conditions while investing in people, capabilities and technology. He added that the bank is focused on strengthening its ASEAN trade banking franchise, growing its consumer business and delivering sustainable returns over time.     Featured image: Edited by Fintech News Singapore, based on image by UOB The post UOB CEO Wee Ee Cheong’s Pay Falls to S$12 Million Amid 23% Profit Dip appeared first on Fintech Singapore.

The Infocomm Media Development Authority (IMDA) has launched a new bootcamp to help local enterprises turn AI plans into practical projects and digital roadmaps. The Digital Leaders Accelerator Bootcamp was announced by Minister for Digital Development and Information Josephine Teo at the IMDA DLAB Launch Reception 2026. It is part of the National AI Impact Programme and builds on IMDA’s Digital Leaders Programme, which started in 2021. Aimed at business leaders from digitally progressive enterprises, the bootcamp will run several times a year. Participants will work on AI projects tied to real business challenges, with the aim of creating immediate value and building confidence for wider adoption. IMDA said the programme will help enterprises build both technical expertise and the organisational readiness needed to deploy AI across teams, processes and operations. Participants are also expected to leave with actionable digital roadmaps and measurable business outcomes. From AI pilots to wider rollout IMDA is launching the programme with Boston Consulting Group and EY-Parthenon. The firms will support participants through workshops and project sessions focused on high-impact use cases, workflow reviews and viable AI solutions to address rising costs and productivity pressures. During the bootcamp, companies will identify business problems, set measurable goals, assess digital tools, weigh costs and benefits, and develop implementation plans. They will also build and test small-scale AI confidence projects that can be deployed in under three months to demonstrate early value before wider rollout. By the end of the programme, enterprises are expected to gain practical experience in deploying AI and a better understanding of process redesign, data management, infrastructure, AI applications and cybersecurity. They will also develop roadmaps with milestones, performance indicators and business outcomes. As part of the final stage, participants will hold structured discussions with IMDA on support for setting up in-house digital teams to sustain and scale their AI transformation. IMDA said the programme supports its goal of helping 2,000 digital leaders across sectors harness AI over the next three years. The first run will begin on 26 March and will be conducted by EY-Parthenon. Boston Consulting Group will begin its sessions in the second quarter, with IMDA planning to add more industry partners over time.     Featured image: Edited by Fintech News Singapore, based on image by Who is Danny via Freepik   The post IMDA Launches AI Bootcamp to Help Local Firms Move Beyond Pilot Projects appeared first on Fintech Singapore.

Crypto.com CEO Kris Marszalek said the company has cut about 12 percent of its workforce as part of an enterprise-wide AI shift. Kris Marszalek Marszalek said, “Companies that do not make this pivot immediately will fail. Companies that move slowly will be left behind. Companies that move immediately and pair the best AI tools with top-performers will achieve a level of scale and precision that was previously impossible.” He added the reduction was targeted at roles that do not adapt to the company’s new direction in an AI-led environment. Affected employees have reportedly been notified and are receiving support as they transition out of the company. The move follows Crypto.com’s 20 percent workforce cut in early 2023. By April 2024, the company said it was hiring again, describing its expansion plans as more measured after the earlier layoffs.     The post Crypto.com Cuts About 12% of Workforce Citing AI Shift appeared first on Fintech Singapore.

The Monetary Authority of Singapore (MAS) has worked with 24 financial institutions, alongside other industry partners, to develop a toolkit for managing AI risks across the financial sector. The toolkit marks the conclusion of phase two of Project MindForge and is intended to help financial institutions manage risks linked to traditional AI, generative AI and emerging agentic AI technologies. Members of the MindForge consortium At the centre of the toolkit is an AI Risk Management Operationalisation Handbook, which provides detailed, practical guidance on how firms can implement AI risk management frameworks. It is accompanied by a supplement featuring case studies from financial institutions, outlining their experiences, lessons learned and approaches to managing AI risks in different organisational settings. The handbook is organised into four sections aligned with MAS’ proposed Guidelines on AI Risk Management. These cover scope and oversight, AI risk management, AI lifecycle management, and the capabilities and resources needed to support responsible AI use. MAS said it is still reviewing responses to its earlier public consultation on the proposed guidelines. It added that the handbook will be updated over time as industry use of AI matures and as supervisory expectations evolve. The regulator also plans to set up an AI risk management workgroup under its BuildFin.ai initiative to develop implementation resources, facilitate knowledge sharing, and build capabilities and frameworks for managing risks from newer AI technologies such as agentic AI. BuildFin.ai brings together technology providers, research institutes and financial institutions to tackle shared industry challenges. Kenneth Gay Kenneth Gay, Chief FinTech Officer at MAS, said, “The development of the MindForge AI Risk Management Toolkit, including the release of the Operationalisation Handbook, marks a major step forward in our journey to ensure the responsible adoption of AI in finance. We are committed to fostering a culture of continuous engagement and strengthening of AI governance and risk management practices across the industry.” Project MindForge was launched in mid-2023 to strengthen AI risk management for financial institutions using AI in their services and operations.     Featured image: Edited by Fintech News Singapore, based on image by MAS The post MAS Releases AI Risk Toolkit as Generative and Agentic AI Gain Ground appeared first on Fintech Singapore.

The digital asset conversation in Southeast Asia has taken a fascinating turn. If you look back just a couple of years, the headlines were dominated by retail frenzy and “get rich quick” stories. But walk into any fintech hub in Singapore or Kuala Lumpur today, and you’ll find a much more serious atmosphere. In 2026, the noise has been replaced by a quiet, determined focus on building the “architecture of trust”—the boring, essential plumbing that allows digital finance to actually work for everyone. Moving Beyond the Hype We are witnessing a fundamental shift from speculation to utility. It’s no longer about whether a token’s price will go up; it’s about whether a business can settle a cross-border invoice in seconds rather than days. This “institutional pivot” is the most significant trend of the year. Digital payment volumes across the ASEAN region are on track to hit staggering new highs, but the real story isn’t the volume—it’s the participants. Traditional banks and global payment networks are no longer just “exploring” blockchain; they are integrating it into their core DNA. We’re seeing a new breed of partner programs where the speed of digital assets is being merged with the reliability of existing global card rails. For a corporate treasurer, this means the friction of the old world—the endless middleman fees and “lost in transit” wire transfers—is finally starting to evaporate. The Search for Standards Fragmentation has been one of the largest challenges as an industry. Various blockchain protocols enjoyed an insular existence where they could not communicate with one another. The industry has eventually come to the realization that in order to scale digital assets, they need to be interoperable in 2026. This has led to a surge in cross-border payment linkages that feel as seamless as scanning a QR code at a local market, yet operate on highly sophisticated, secure rails. This drive for standardization isn’t just about code; it’s about security. Institutional investors have brought with them a “no-nonsense” approach to risk. They demand qualified custody and cybersecurity frameworks that can stand up to the most rigorous audits. We are moving toward a “zero-trust” environment where compliance is baked into the software itself. This proactive risk management is what will eventually separate the sustainable platforms from the ones that can’t handle the pressure of a global market. Local Expertise in a Global Market While the technology is global, the implementation is always local. Regional hubs have found success by creating “sandboxes” where innovation can happen safely without breaking the broader financial system. By focusing on consumer protection and market integrity, these jurisdictions have become magnets for global capital. For anyone trying to navigate this landscape, the challenge is often finding the right entry points. It’s not just about finding a platform; it’s about finding a partner that understands the nuances of the region. This is why many institutional allocators and tech-savvy investors rely on curated industry resources. For example, staying informed on the reliability and service standards of  Malaysia’s crypto exchanges is now a standard part of the due diligence process for anyone serious about the Southeast Asian corridor. The Next Frontier: Real Assets Perhaps the most exciting development we’re seeing is the tokenization of Real-World Assets (RWAs). We are finally moving past “digital-only” assets and starting to put real things on the blockchain—private equity, real estate, and even carbon credits. Imagine being able to trade a fraction of a commercial building or a high-quality treasury product with the same ease you’d trade a stock. This isn’t a futuristic dream; it’s happening now. Asset managers are increasingly using these tools to offer 24/7 liquidity and transparency that was previously impossible. It’s making the world of high-finance more accessible and efficient, one block at a time. Why the “Invisible” Layer Wins If we do our jobs right, the blockchain will eventually become invisible. The average person shouldn’t have to understand how a distributed ledger works any more than they need to understand how TCP/IP makes their email work. They just want their money to move fast, safely, and at a low cost. As we look toward the future, the winners in the fintech space won’t be the ones with the loudest marketing; they’ll be the ones who provide the smoothest, most reliable experience. The goal is to build a financial system that supports e-commerce, logistics, and global trade without the user ever realizing they are interacting with a revolutionary technology. A New Trajectory The history of the development of digital assets in Southeast Asia is a lesson in the power of persistent development. Having gone beyond the hype and prioritizing useful and utility-oriented applications, the region has laid a ground that is prepared to face whatever the future holds. The architecture of trust will be nearly complete, the resulting financial ecosystem will be more inclusive, efficient and resilient than anything we have ever viewed. It is a transition from a wild frontier to a polished, professional infrastructure that serves the real economy.   Featured image by Who is Danny on Freepik The post The Architecture of Trust: How Southeast Asia is Quietly Rebuilding Finance appeared first on Fintech Singapore.

Matrixport has rebranded as BIT, reflecting the firm’s continued development in digital asset financial infrastructure and services. Alongside the rebrand, BIT published its BIT 2026 Trust Whitepaper, outlining the governance, risk management and operational frameworks supporting its services. The paper provides a structured overview of the firm’s governance, compliance and operational foundations. John Ge CEO John Ge said, “Digital asset markets are entering a phase in which governance, transparency and operational discipline are increasingly important. BIT reflects the continued evolution of our business and our commitment to building trusted digital asset financial infrastructure.” The firm said the rebrand will not affect existing client accounts, products or services, while its legal entities and contractual arrangements will remain unchanged. BIT is also exploring potential capital markets opportunities in the United States, including a possible public listing. Founded in 2019, the company, previously known as Matrixport, offers services including custody, trading, asset and wealth management, liquidity and financing solutions, as well as tokenised real-world assets. Its entities maintain a licensed and regulated presence across Singapore, Hong Kong, Switzerland, the United Kingdom, the United States and Bhutan. This includes a Major Payment Institution licence in Singapore and a FINMA-licensed Manager of Collective Assets in Switzerland.     Featured image: Edited by Fintech News Singapore, based on image by HobieArt via Freepik The post Matrixport Rebrands as BIT as It Explores Possible U.S. Public Listing appeared first on Fintech Singapore.

GrabInsure, the insurance arm of Grab, has rolled out a motor insurance product for private-hire drivers in Singapore. The product is available to Grab driver-partners who use their own vehicles and is aimed at making coverage more affordable and easier to access. The policy was designed for private-hire drivers and includes instalment payment options, 24/7 emergency assistance and personalised pricing. The company described it as a first-of-its-kind product that uses historical platform insights to tailor premiums. According to GrabInsure, drivers can pay premiums through the Grab Driver App Wallet without needing a credit card. Premiums can be broken into smaller payments, which could help turn insurance into a more manageable operating cost rather than a large upfront expense. Iwan Juwono Iwan Juwono, Head of GrabInsure, said, “Private-hire drivers have different needs from traditional motorists as they rely on their vehicles as their source of livelihood, and face seasonal fluctuations in earnings. With this launch, we are rethinking motor insurance from the ground up. By leveraging insights on a driver’s track record on Grab, we can offer more competitive pricing to reward safer driving and better service.” The launch adds to GrabInsure’s broader set of protection products for driver-partners. These include its Earnings Protection Policy, which provides additional support on top of Grab’s existing complimentary coverage. The policy covers compassionate leave, booking cancellations or no-shows, and downtime caused by vehicle cleaning after passenger-related incidents.     Featured image: Edited by Fintech News Singapore, based on image by topntp26 via Freepik The post Grab Offers Motor Insurance for Singapore Private-Hire Drivers appeared first on Fintech Singapore.

DBS and POSB digital banking services were restored this afternoon on 19 March 2026 after some customers faced difficulties accessing certain digital services earlier in the day. The bank said its digibank mobile and online services, along with DBS PayLah!, had returned to normal as of 1:19pm. Earlier, the bank said it was working to fully recover services. During the disruption, DBS said customers could still make payments using DBS and POSB cards, check account balances through DBS and POSB ATMs and digiBot, and withdraw cash from DBS and POSB ATMs as well as POSB Cash-Points. Wealth clients were also told to contact their Relationship Manager to place trades. The bank said customers’ monies and deposits remained safe. The latest disruption follows earlier service issues at DBS. In June 2025, DBS and POSB customers again reported problems accessing mobile banking services, marking the second such outage for the bank that year. Another disruption affected digital banking and ATM services in Singapore in March 2025. Those earlier outages had already drawn regulatory action from the Monetary Authority of Singapore. In May 2023, MAS raised DBS’ additional capital requirement for operational risk to 1.8 times its risk-weighted assets for that category. In November 2023, MAS also imposed a six-month pause on the bank’s non-essential IT changes and new business acquisitions to keep it focused on improving the resilience of its digital banking services. The restriction was lifted at the end of April 2024, though the additional capital requirement remained in place.     Featured image: Edited by Fintech News Singapore, based on image by DBS The post DBS Restores Digital Banking Services After First Outage of 2026 appeared first on Fintech Singapore.

The fintech sector continues to be one of the most dynamic forces reshaping financial services across Asia-Pacific. This ranking, drawn from the FT-Statista High-Growth Companies Asia-Pacific 2026 list, spotlights the region’s fastest-growing fintech companies based on revenue growth between 2021 and 2024. From digital banks and payment infrastructure to insurtech and wealth management platforms, these companies reflect the breadth and ambition of Asian fintech innovation. Singapore leads the fintech pack with 12 entrants, followed by India with 11, underscoring both markets’ reputations as regional fintech powerhouses. Standout performers include Singapore’s Aspire (1772%) and Storepay (1722%), Indonesia’s DurianPay (1626%), and Malaysia’s PolicyStreet (1311%). Last updated: 19 March 2026 Source: Financial Times analysis 12 Fastest-Growing Singapore Fintechs The top three fastest-growing Singapore fintechs in 2026 are Aspire, Storepay and Syfe, with the first two hitting 1700+% in their absolute growth rates. Aspire Absolute growth rate: 1772.43% Revenue (2024): $44.72 million Founded in 2018, Aspire is an integrated financial operating system designed for modern enterprises. Trusted by over 50,000 companies, the platform offers a unified interface to streamline international payments, treasury operations, and end-to-end expense and cash flow management. Storepay Absolute growth rate: 1722.18% Revenue (2024): $8.75 million Storepay provides a BNPL service designed to make purchases, regardless of size,  a budget-friendly and accessible affair. Headquartered in Singapore, the business also operated in Mongolia, Indonesia and Vietnam. Syfe Absolute growth rate: 632.62% Revenue (2024): $9.59 million Syfe functions as a digital wealth platform and manages $10+ billion in client assets. The platform provides a range of investing solutions, including cash management, managed portfolios, brokerage, private wealth, and Syfe for Business. Nium Absolute growth rate: 266.67% Revenue (2024): $90.55 million Founded in 2014 to simplify the complexities of cross-border payments, Nium has evolved into a diverse team of over 750 professionals across 10+ global offices. The company provides infrastructure for banks, money transfer operators, and enterprises looking to optimise matters like payroll, spend management, and more. CoverGo Absolute growth rate: 261.06% Revenue (2024): $3.9 million CoverGo is an insurtech company that delivers a no-code core insurance platform for clients globally. Solutions provided include CoverGo for Health, CoverGo for Life, and CoverGo for P&C. Spark Systems Absolute growth rate: 233.33% Revenue (2024): $5.12 million Spark Systems is an eFX platform which is built entirely in-house with a suite of advanced technologies to provide a holistic eFX solution. It runs on open architecture CEP technology, which allows plug-and-play algorithm trading strategies, with a built-in risk control system. Lighthouse Canton Absolute growth rate: 176.95% Revenue (2024): $26.34 million Lighthouse Canton is a global investment institution providing wealth and asset management services, working with clients across geographies across offices in four countries. The business uses integrated tech systems with the purpose of delivering quality client experiences, including digitised services, automated construction of complex portfolios, and real-time information access from partner banks. Funding Societies Absolute growth rate: 173.60% Revenue (2024): $54.36 million Launched in 2015, Funding Societies’ purpose is to create financial opportunities for every person, and in doing so, uplift societies across SEA. SMEs are a specific focus, and Funding Societies aims to provide accessible, reliable business financing to individuals and institutions alike. iFast Corporation Absolute growth rate: 119.38% Revenue (2024): $185.88 million iFast Corporation is a global digital banking and wealth management platform, delivering a suite of investment products and financial services to financial advisory platforms, banks, multinational companies, internet companies, and retail and high-net-worth investors in Asia. The group offers 28,300+ investment products, with presence in Hong Kong, Malaysia, China, and the UK. Una Financial Absolute growth rate: 55.14% Revenue (2024): $202.35 million Una Financial delivers financial services such as short-term lending and instalment loans, while also operating an investment platform. The company deploys machine learning and data-driven and is represented in several markets in Europe and Asia. M-Daq Global Absolute growth rate: 51.94% Revenue (2024): $42.54 million M-Daq Global specialises in FX and payment solutions, delivering cross-border transactions for businesses globally. The fintech operates across 7 countries, including Indonesia, China, Hong Kong, and the UK. Solutions provided include CheckGPT, which makes onboarding faster with AI-powered KYB for compliance. Choco Up Absolute growth rate: 49.29% Revenue (2024): $5.14 million Choco Up is a platform which provides revenue-based financing and business growth solutions to Asia-Pacific digital merchants and SMEs. According to its website, it has reached 1000+ funding rounds. The company offers a range of flexible financing solutions, namely Upstart, Upstart Plus, and Upfront.   11 Fastest-Growing Indian Fintechs India’s Credgenics tops this list of fastest-growing Indian fintechs in 2026 with 596.99% in its absolute growth rate, followed closely by Svamaan Financial Services at 535.15%. Credgenics Absolute growth rate: 596.99% Revenue (2024): $22.71 million Credgenics provides a loan collection and debt resolution tech platform for banks, non-banking finance companies, fintech and more worldwide. It runs an AI-powered SaaS-based platform. The company has handled 98+ million retail loan accounts over US$250 billion in FY2024 for collections, according to its website. Svamaan Financial Services Absolute growth rate: 535.15% Revenue (2024): $28.71 million Svamaan Financial Services deploys a data-based approach to hit two goals: financial inclusion while driving impact for its customers. The company’s products and services, including loan amounts, are tailored to suit their customer’s needs and requirements. Svamaan applies a fully paperless and cashless approach from inception to loan disbursement. Juspay Absolute growth rate: 356.15% Revenue (2024): $61.47 million Juspay’s goal is to simplify payment orchestration and global coverage. Headquartered in Bangalore, the company’s global network spans 1500+ payment experts across Dubai, San Francisco, Singapore and more. Juspay secured $50 million in funding in January, which will support its international expansion and product development plans. Vyapar Absolute growth rate: 350.64% Revenue (2024): $10.79 million Vyapar is a free business accounting software that indian SMEs can use for their invoicing, inventory, and accounting needs. The company shares that it has 10+ million downloads and runs in English and Hindi. Scripbox Absolute growth rate: 340.91% Revenue (2024): $13.06 million Scripbox aims to help individuals reach their financial goals, comprising wealth plans, goal-based plans, mutual funds, fixed deposits and more. The company applies recommendations by advisors and data-backed algorithms. Aye Finance Absolute growth rate: 239.33% Revenue (2024): $179.86 million Aye Finance provides business loans to SMEs across India, with fully digital loan applications, including loan decisioning via its data science model. Altius Investech Absolute growth rate: 206.45% Revenue (2024): $30.53 million Altius Investech is a data-driven intelligence platform which democratises access to information on alternative investment opportunities. It provides comprehensive data and insights on pre-IPO and late-stage businesses by exploring trends, assessing market dynamics, and deploying strong intelligence tools. Angel One Absolute growth rate: 131.93% Revenue (2024): $626.08 million Angel One provides a suite of services, including brokering, margin trading, depository services, investment education and the distribution of third-party financial products. The company provides a wide array of investment options, including stocks, IPOs, mutual funds and more. Blacksoil Absolute growth rate: 114.52% Revenue (2024): $22.72 million Blacksoil functions as an alternative credit platform which delivers alternative credit products and solutions to growing companies. It expanded into supply chain finance with SaralSCF, a B2B fintech platform that partners with mid-size enterprises to navigate the working capital needs in their supply chain. Vayana Absolute growth rate: 113.95% Revenue (2024): $11.44 million Vayana is a supply chain finance platform that offers numerous trade credit and trade enablement solutions across 600+ cities in India. According to its website, it has facilitated $55+ billion in financing with over 3000+ supply chains covered. LenDenClub Absolute growth rate: 60.73% Revenue (2024): $28.26 million LenDenClub is a peer-to-peer lending platform with a fully digital process for lending, where every borrower is said to be screened across 670+ parameters.   4 Fastest-Growing Hong Kong Fintechs Hong Kong is home to four of the fastest-growing fintechs in the Asia Pacific, which are Bowtie, Statrys, HashKey Group and WeLab Bank. Bowtie Life Insurance Company Absolute growth rate: 328.50% Revenue (2024): $35.25 million Bowtie is one of Hong Kong’s first virtual insurers. It offers a platform which delivers medical insurance plans directly to customers, achieving $100+ billion in total amount in insurance coverage. Statrys Absolute growth rate: 255.29% Revenue (2024): $7.20 million Statrys provides tailored payment, corporate and accounting solutions to SMEs, entrepreneurs, as well as startups through its platform. The company operates in Hong Kong, Singapore and the European Union. HashKey Group Absolute growth rate: 230.66% Revenue (2024): $92.36 million HashKey Group is a digital asset company in Asia, operating in regions like Hong Kong, Singapore, and Japan. The group has a global Web3 ecosystem spanning across HashKey Exchange, HashKey Global, HashKey Capital, HashKey OTC, HashKey Cloud, and HashKey Tokenisation. The group also has a listed HashKey platform token, HSK. WeLab Bank Absolute growth rate: 88.10% Revenue (2024): $88.11 million WeLab Bank is a digital bank licensed by the Hong Kong Monetary Authority. The company provides personalised customer experiences using GenAI and AI agents, and has established an AI-first partnership with Google.   3 Fastest-Growing South Korean Fintechs South Korean fintechs Toss, TheCheat and Wadiz enter the list as the country’s fastest-growing fintechs in 2026 in APAC. Toss Absolute growth rate: 160.75% Revenue (2024): $1434.39 million Toss launched in 2015 as a money transfer service, and has since expanded into a superapp, delivering everything from digital banking to a financial marketplace, credit scores, money transfers and more. As of December 2025, Toss has 100,000+ business customers. TheCheat Corporation Absolute growth rate: 83.34% Revenue (2024): $1.52 million TheCheat Corporation is a fraud prevention fintech established in 2006, and is an information-sharing site for fraud victims, including cryptocurrency damages. Wadiz Absolute growth rate: 82.57% Revenue (2024): $31.72 million Wadiz is a crowdfunding platform that handles rewards and equity-based crowdfunding. According to its website, the company has funded 83k+ projects and has 17+ million supporters.   2 Fastest-Growing Australian Fintechs This year, Beforepay Group and iPartners are in the list of the fastest-growing Asia-Pacific fintechs from Australia. Beforepay Group Absolute growth rate: 162.93% Revenue (2024): $26.51 million Founded in 2019, Beforepay Group uses AI, machine learning and analytics to deliver affordable and secure financial products. The group delivers its solutions through Beforepay, a DTC personal finance platform and Carrington Labs, which is an “enterprise provider of cash flow underwriting and credit risk analytics. iPartners Absolute growth rate: 122.58% Revenue (2024): $13.98 million iPartners runs a digital platform which makes it easy for investors to discover, access, and invest. Its platform is said to ensure an intuitive digital investment process, which is paperless and a 5-click investment process.   2 Fastest-Growing Malaysian Fintechs PolicyStreet makes it into the list as one of the fastest-growing Malaysian fintechs with a 1311+% in absolute growth rate, and is accompanied by CapBay. PolicyStreet Absolute growth rate: 1311.27% Revenue (2024): $30.41 million PolicyStreet is a digital insurance platform that compares prices across insurers, aiming to provide personalised coverage for every life stage. Its group of companies operated across Southeast Asia and Australia, working with 40+ life, general and takaful providers globally to offer a wide range of products and services. CapBay Absolute growth rate: 248.19% Revenue (2024): $13.61 million CapBay is a supply chain finance and P2P platform that helps SMEs with financing solutions. The company deploys its proprietary credit-decisioning model, enabling businesses of every size to obtain financing, while banks and investors are able to participate in financing deals.   Fastest-Growing Taiwanese Fintech Taiwan’s OBOOK Holdings, also known as OwlTing Group, makes it into the list as the fastest-growing Taiwanese fintech in the Asia Pacific. Obook Holdings Absolute growth rate: 188.78% Revenue (2024): $7.57 million OBOOK Holdings operates as OwlTing Group worldwide, which is a blockchain tech company founded in Taiwan with subsidiaries across the US, Japan, Singapore, Hong Kong and more. The company aims to leverage blockchain tech to provide businesses with reliable and transparent data management, with a hybrid Web2-Web3 payment suite to help businesses operate in the growing stablecoin economy.   Fastest-Growing Filipino Fintech Paynamics is the sole Filipino fintech company among the fastest-growing APAC fintechs in 2026, hitting an absolute growth rate of 161.21%. Paynamics Absolute growth rate: 161.21% Revenue (2024): $10.93 million Paynamics delivers a comprehensive payment infrastructure that empowers SMEs, conglomerates, financial institutions and government agencies. It provides access to 50+ payment channels, and also delivers checkout, payout and business wallet solutions.   Fastest-Growing Indonesian Fintech Indonesian fintech DurianPay holds the third place as the fastest-growing fintech in the APAC region, with a 1625.85% in absolute growth rate. DurianPay Absolute growth rate: 1625.85% Revenue (2024): $9.07 million Durianpay is a B2B payments infrastructure that aims to streamline transactions across Indonesia and the rest of Southeast Asia. The business offers a full-stack platform for payment acceptance, payout, reconciliation and reporting.   Frequently Asked Questions (FAQs) How were the fintech companies selected for this ranking? Companies applied for or were identified through research between July and December 2025. To qualify, each company needed at least $100,000 in 2021 revenue, at least $1 million in 2024 revenue, and had to be an independent, Asia-Pacific headquartered business. Revenue growth had to be primarily organic. There were also other factors meh considered during the ranking process. What does “absolute growth rate” mean in this context? The absolute growth rate reflects the total percentage increase in revenue between 2021 and 2024. The ranking uses compound annual growth rate (CAGR) for ordering, calculated from revenue figures submitted in local currencies and converted to USD using World Bank annual average exchange rates. Which country has the most fintech companies in the ranking? Singapore is at the top, with 12 fintech entrants, followed by India with 11 entrants. Is this ranking exhaustive of all fintechs in the region? No. As noted in the methodology by the Financial Times, the ranking does not claim to be complete. Some companies chose not to participate or declined to make their financials public. Featured image edited by Fintech News Singapore based on an image by freepik on Freepik The post Fastest-Growing Asia Pacific Fintechs, According to the Financial Times (2026) appeared first on Fintech Singapore.

2C2P has been engaged by M-PAY to provide technical payment services for Sun PhuQuoc Airways in Vietnam, with other Asian markets set to follow. The partnership will allow customers booking Sun PhuQuoc Airways flights online in Vietnam to access a broader range of payment options. Other markets in the pipeline include China, Malaysia, India, Singapore, South Korea and Thailand. M-PAY will provide the airline with Payment Air Controller, or PACO, a payment orchestration system for airlines. The platform supports payment methods including cards, digital wallets, QR payments and direct debit. Through a single API integration, the system can route payments to different acquirers and includes retry logic aimed at improving cost efficiency. It is also PCI DSS Level 1-certified and integrated with global distribution systems such as Amadeus and Sabre. Worachat Luxkanalode Worachat Luxkanalode, Group CEO of 2C2P, said, “Today’s travellers expect instant and localised booking experiences. As the go-to solutions provider for airlines operating into and within Asia, we are excited to partner with M-PAY and Sun PhuQuoc Airways to introduce Phu Quoc to more Vietnamese and Asian travellers.” Nguyen Manh Quan Nguyen Manh Quan, CEO of Sun PhuQuoc Airways, said, “As Sun PhuQuoc Airways expands from Phu Quoc to key destinations in the region, seamless and localised payment experiences are essential to making travel easier and more intuitive. This collaboration is a key part of our commitment to delivering a connected ‘resort-in-the-sky’ journey. Together with our partners, we look forward to contributing to better customer experience and greater accessibility across the region.”     Featured image: Edited by Fintech News Singapore, based on image by Sun PhuQuoc Airways The post 2C2P and M-PAY to Expand Digital Payment Options for Sun PhuQuoc Airways appeared first on Fintech Singapore.

HSBC is weighing deeper workforce cuts as it explores how artificial intelligence could reshape parts of its operations, Bloomberg reported. The review is still at an early stage, with no final decision made on the scale or structure of any reductions. The bank could eventually cut around 20,000 roles over the next several years, according to people familiar with the matter. Some of the reduction may come from not replacing departing staff, while other changes could result from business sales or exits. Non-client-facing roles in global service centres are seen as among the most exposed. The plan, if carried out, would unfold over a three- to five-year period as HSBC reviews how AI could reduce work across parts of its middle and back office functions. The review comes as Chief Executive Officer Georges Elhedery continues a broader overhaul of the bank. Since taking over in 2024, he has already cut thousands of jobs while also selling, merging or shutting some businesses. HSBC had around 210,000 employees at the end of 2025. The reported move also reflects a wider shift across global banking. Bloomberg Intelligence said last year that banks worldwide could eliminate as many as 200,000 jobs over the next three to five years as AI takes on more tasks now handled by employees. Chief information and technology officers surveyed by the research unit expected an average net workforce reduction of 3 percent. At HSBC, the potential cuts would come alongside a broader push to lower costs and improve productivity. HSBC said recently that it expects to achieve its US$1.5 billion cost-savings target in the first half of the year, six months ahead of schedule. Speaking at a Morgan Stanley conference on Wednesday, Chief Financial Officer Pam Kaur said the bank sees room to use AI to reduce costs and improve employee productivity. She pointed to customer service centres, know-your-customer teams and transaction monitoring as areas where the technology could make operations more efficient. HSBC declined to comment.     Featured image: Edited by Fintech News Singapore, based on image by smth.design via Freepik The post HSBC Weighs Around 20,000 Job Cuts in Multiyear AI Review appeared first on Fintech Singapore.

Snowflake is extending its enterprise AI strategy with Project SnowWork, a platform designed for autonomous task execution. Launched in research preview for a limited set of customers, Project SnowWork is designed to help business users complete multi-step tasks through conversational prompts across planning, analysis and execution. Snowflake said the platform can handle tasks such as preparing forecast presentations, identifying churn risks and uncovering supply chain bottlenecks, executing workflows from start to finish and delivering structured outputs based on business needs. The launch is part of Snowflake’s broader push into what it calls the agentic enterprise. Sridhar Ramaswamy “Project SnowWork looks to put secure, data-grounded AI agents on every surface, so business leaders and operators can move from question to action instantly. By elevating AI from experimentation to enterprise-grade autonomous execution, Project SnowWork serves as the secure foundation for how modern enterprises will get work done in the AI era.” said Sridhar Ramaswamy, Chief Executive Officer, Snowflake. Built on Snowflake’s data platform, Project SnowWork is designed to connect enterprise data, AI capabilities and business systems in a more coordinated way. Snowflake said this allows users to generate analysis, receive recommended next steps and complete tasks with less reliance on analysts or technical teams. Snowflake said the platform includes pre-configured AI profiles for roles such as finance, sales, marketing and operations. It can query data, apply analysis, summarise insights, generate structured deliverables and prepare follow-up actions within a single workflow. The company added that Project SnowWork applies existing platform controls including role-based access, masking policies, audit logging and governance rules. The launch also expands Snowflake’s wider AI portfolio. The company said Project SnowWork builds on Snowflake Intelligence, which answers business questions using natural language, by adding the ability to act on those insights. It also sits alongside Cortex Code, Snowflake’s AI coding agent for data engineering, analytics and development tasks.     Featured image: Edited by Fintech News Singapore, based on image by DC Studio via Freepik The post Snowflake Debuts AI Platform to Automate Tasks for Business Users appeared first on Fintech Singapore.

Five companies are in the running to set up Vietnam’s first licensed crypto exchanges, Reuters reported, citing a Finance Ministry document. Those named include affiliates linked to Techcombank, VPBank and LPBank, alongside VIX Securities and Sun Group. Sun Group and VPBank said they had submitted applications, while the Finance Ministry did not comment on the list. The applications come as Vietnam moves to test a domestic crypto exchange model and considers new restrictions on trading through foreign platforms. The proposed changes would mark a significant shift for a market where many users still trade through offshore exchanges. Vietnam placed fourth in Chainalysis’ 2025 Global Crypto Adoption Index. Reuters also reported that trading tied to Vietnamese users topped US$200 billion in the 12 months to June. Crypto is not accepted as legal payment in Vietnam, but trading activity remains strong. Market participants say overseas platforms such as Binance, OKX and Bybit continue to dominate, while industry representatives argue that local exchanges could help build a more regulated domestic crypto market.     Featured image: Edited by Fintech News Singapore, based on images by suriyawutsuriya and boggy via Freepik The post Five Firms in the Running to Launch Vietnam’s First Licensed Crypto Exchanges appeared first on Fintech Singapore.

David Hardoon is departing Standard Chartered less than a year after joining the bank as Global Head of AI Enablement, according to Bloomberg. Hardoon, who is based in Singapore, is on gardening leave, the report said. Standard Chartered declined to comment on the departure. He joined the bank in April 2025 to support its broader AI ambitions as lenders step up efforts to embed the technology across core business functions. Hardoon brought experience across banking, regulation, academia and AI startups. His earlier roles included serving as the first Chief Data Officer at the Monetary Authority of Singapore. He also held senior data and AI positions at UnionBank and UnionDigital in the Philippines before leading Aboitiz Data Innovation, the conglomerate’s data science and AI venture. The departure comes as banks continue investing in AI talent, governance and deployment. In the 2025 Evident AI Index, Standard Chartered ranked 26th globally for AI maturity, based on factors such as talent, innovation, leadership and transparency.     Featured image: Edited by Fintech News Singapore, based on image by ghiska via Freepik The post David Hardoon Reportedly Departs StanChart After Brief Stint as Global AI Lead appeared first on Fintech Singapore.

Singapore businesses are among the latest users to gain access to PayPal USD as PayPal expands the stablecoin to 70 markets. The stablecoin will not be available to retail users in Singapore. PYUSD, PayPal’s US dollar-backed stablecoin, is being made available through PayPal accounts across Asia-Pacific, Europe, Latin America and North America. PayPal said users in newly supported markets can buy, hold, send and receive PYUSD directly from their PayPal accounts, subject to local regulations and product availability. Eligible users can also transfer PYUSD to friends and family through PayPal or third-party digital wallets, and convert it into local currency when withdrawing funds. For businesses that accept PYUSD, PayPal said proceeds can be used in minutes rather than days or weeks, helping improve liquidity and support working capital needs. May Zabaneh May Zabaneh, Senior Vice President and General Manager of Crypto at PayPal, said, “Enabling PYUSD in users’ accounts across 70 markets gives people faster access to their funds, lower-cost ways to send money across borders, and a more direct path to participating in the global economy, and that is what drives commerce forward for everyone.” PYUSD was launched in the United States in 2023. PayPal said the expansion is part of its broader push to grow the stablecoin’s use in global commerce. Available markets include Colombia, Costa Rica, the Dominican Republic, the Faroe Islands, Greenland, Guatemala, Honduras, Panama, Peru, Singapore, the United Kingdom and the United States. PayPal said users in the remaining markets will gain access to PYUSD in the coming weeks. Rewards on PYUSD holdings will not be available to users in Singapore or the United Kingdom.     Featured image: Edited by Fintech News Singapore, based on image by jannoon028 via Freepik The post PayPal Offers Stablecoin Access to Singapore Businesses in 70-Market Expansion appeared first on Fintech Singapore.

Mastercard is building a new generative AI model using anonymised transaction data, with cybersecurity and fraud detection among its first planned uses. The company said the model is designed as an insights engine for payments and commerce rather than a chatbot. It described the system as a large tabular model trained on structured data. Over time, the model could also support services such as loyalty and rewards programmes, personalisation, portfolio optimisation and analytics. Mastercard said it is training the system on billions of anonymised transactions and may later expand it to include other datasets such as merchant location, fraud, authorisation, chargeback and loyalty programme data. The company said the model can learn patterns from data with less manual input than its existing systems, which often rely on data scientists to add features that help flag suspicious activity. In early testing, Mastercard said the model outperformed standard machine learning techniques in some cases, including showing better ability to identify legitimate high-value purchases that might otherwise be flagged as suspicious. Steve Flinter Steve Flinter, Distinguished Engineer at Mastercard, said, “We plan to build hybrid cybersecurity systems that combine the best of both our current AI models and this new LTM. This should help us build up and futureproof our cyber defenses.” Mastercard said the model could eventually help reduce the need to build and maintain thousands of separate AI models across different markets, customers and use cases. The project is being developed with Nvidia and Databricks, and Mastercard plans to share more about the work at Nvidia GTC 2026.       Featured image: Edited by Fintech News Singapore, based on image by Frolopiaton Palm via Freepik The post Mastercard Builds Generative AI Model for Payment Insights, Fraud Detection appeared first on Fintech Singapore.