Discussions about the future of banking often revolve around digital channels, cloud migration and mobile apps. At Mobile World Congress 2026 in Barcelona, Huawei placed the spotlight on what comes next. During its Digital Finance session, the company gathered financial institutions and technology partners to discuss how artificial intelligence is beginning to reshape the foundations of modern banking. The event carried the theme “Powering Resilient Intelligence, Co-creating Finance Future” and served as the backdrop for Huawei to introduce upgrades to its Banking AI and Foundation Model Solutions aimed at supporting the next phase of industry transformation. Attention quickly turned to the keynote delivered by Alvin Feng, President of International Financial Business at Huawei’s Digital Finance division. His presentation explored the growing role of AI in banking operations and why many financial institutions are now rethinking how technology fits into their long-term strategy. According to Alvin, the industry has spent the past two decades focused on digital optimisation. Online banking and mobile services changed how customers interact with financial institutions while data platforms helped banks improve operational efficiency. Artificial intelligence now opens the door to a deeper transformation, one that is beginning to influence how banks operate at every level. “AI is becoming the defining force reshaping the global financial industry,” Alvin said during his speech, noting that intelligence is starting to influence everything from customer engagement to risk management and internal decision making. Banking Begins Another Technology Transition Banks have moved through several waves of technological change. Early systems focused on automating back office processes and digitising records. Internet banking expanded customer access. Mobile technology later made financial services available almost anywhere. Another transition is beginning to take shape. Growing adoption of artificial intelligence is pushing banks to reconsider how services are delivered and how internal workflows operate. Customer interaction already offers a clear example. Instead of navigating menus and structured forms, users increasingly interact through conversational interfaces where systems interpret requests expressed in everyday language. Personalisation also begins to operate at a different scale. In the past, tailored financial advice often remained limited to high value customers. AI systems now analyse patterns across large datasets which allows banks to deliver personalised insights and recommendations to far wider segments of their customer base. Inside financial institutions, work patterns are also changing. Many teams already rely on automated tools for data analysis and reporting. AI agents add another layer by assisting staff in tasks such as reviewing applications, analysing documents or identifying unusual transaction activity. Alvin described the shift as one that extends across several dimensions of banking operations including customer engagement, decision making processes and the technology architecture supporting financial services. As he put it: “The transition from traditional banks to AI-driven banks brings profound changes in customer interactions, human-machine collaboration, decision-making approaches, system architecture, and customer experience.” Linking Business Strategy With Technology Execution A recurring theme throughout the session centred on how technology is gradually moving closer to the heart of business strategy. For a long time, banks viewed technology primarily as infrastructure that enabled services or reduced operational costs. Increasing reliance on artificial intelligence has started to change that perspective, prompting a reassessment of how technology contributes to growth and competitiveness. Alvin explained that many financial institutions now recognise the need for a clearer connection between business goals and technology deployment. He said this while pointing to a gap that many institutions are still working to close. Building that link requires more than adding isolated AI projects. Drawing on its work with global banks, Huawei introduced a framework known as the Intelligent Finance Value Implementer. The model is intended to help financial institutions identify meaningful AI scenarios, design supporting enterprise architecture and deploy intelligent systems in ways that align with long term business priorities. Selecting the right use cases plays a central role in that process. Projects tied to customer experience, risk control and operational efficiency often deliver the most immediate impact. Once those foundations are in place, institutions can expand AI capabilities across additional services and departments. Underpinning this shift is a broader change in mindset. “Technology is no longer a support function. It is now a value center at the heart of the business,” Alvin mentioned. Where Banks Are Testing AI Todays Several real world examples shared during the event illustrated how these ideas are already being tested in banking environments. Document processing for credit card applications offers one illustration. Staff members traditionally review customer documents manually, a process that can take around twenty minutes per application. AI assisted systems now perform the initial review in roughly twenty seconds while maintaining optical character recognition accuracy above 95 percent. Conversational services provide another glimpse into how banking experiences may evolve. Natural language interfaces combined with specialised AI agents allow customers to interact with digital assistants that guide them through tasks such as checking balances, making deposits or exploring investment options. Over time, these systems build a more detailed understanding of user behaviour by analysing patterns in transactions and previous interactions. The result is a service experience that adapts to individual customers rather than offering the same responses to everyone. Small and medium enterprise lending represents another area where AI tools are beginning to appear. Loan applications in this segment often require coordination between multiple teams. Some banks are experimenting with systems that simulate these roles through separate AI agents that support relationship managers, operations teams and risk analysts during the evaluation process. Human oversight remains essential, yet intelligent tools help reduce the time required to gather information and prepare recommendations. Bringing these elements together requires more than isolated tools. As the President of Huawei Digital Finance International noted, the key to AI banking lies in using systems engineering to unify AI infrastructure with open ecosystems, reengineering banking processes through human and artificial intelligence collaboration. Preparing Banking Systems for AI Workloads Applications such as these depend on a strong technical foundation. Financial institutions operate under strict requirements for reliability, security and performance. Infrastructure must therefore support demanding AI workloads without compromising stability. Huawei used the Digital Finance session to introduce several upgrades designed for that purpose. Among the technologies highlighted were the SuperPoD computing platform, an AI data platform and the Xinghe AI network architecture. Together these systems aim to provide the computing capacity and connectivity required to support advanced financial applications powered by artificial intelligence. Engineering improvements were also discussed. Huawei reported that new optimisation techniques have shortened AI agent development cycles from months to weeks while improving prompt accuracy and reducing end to end processing latency. Such changes matter for large banks that must integrate new technologies with long established core systems. Scaling AI Innovation Through Industry Partnerships No single technology provider can address the complexity of financial services on its own. Huawei therefore emphasised the importance of collaboration through its RongHai partner program. The initiative brings together technology vendors, consulting firms and system integrators working on financial solutions across different markets. More than 150 solution partners now participate alongside over 11,000 consulting, sales and service partners worldwide. Joint development through this network allows banks to deploy solutions tailored to specific regulatory environments while benefiting from shared expertise across the ecosystem. Banks Face the Next Stage of Digital Change Huawei’s digital finance business now supports thousands of financial institutions across more than eighty countries. Over the years, the company has worked with banks on projects ranging from infrastructure modernisation to large scale data platforms. Conversations at the MWC session suggested that the industry may be approaching another turning point. Artificial intelligence continues to expand into areas that were once handled entirely by human teams. Institutions experimenting with these tools are beginning to uncover new ways of serving customers, managing risk and improving operational efficiency. Alvin closed his thoughts with a simple observation about what lies ahead for the sector. Featured image: Edited by Fintech News Malaysia based on an image by Austler via Freepik The post Alvin Feng Shares Huawei’s Vision for AI-Driven Banking at MWC 2026 appeared first on Fintech Singapore.

FOMO Pay is launching a new soundbox in Singapore that allows merchants to accept cards, PayNow, QR payments, e-wallets and stablecoins through one terminal. The FOMO AI Soundbox also provides real-time audio confirmation for each transaction and is designed to reduce the need for merchants to manage separate devices or integrations for different payment options. The Singapore-headquartered payment firm said the launch is part of a broader push to support both traditional payment rails and emerging on-chain payment methods in everyday commerce. FOMO Pay is also developing an AI-powered merchant intelligence layer linked to its merchant portal, which is intended to help merchants access insights from their transaction data more easily. The device includes a built-in microphone that could support future AI features, including tools that let merchants query business data in real time through the terminal. These planned features are aimed especially at small and mid-sized businesses that may not have the time or resources to analyse transaction data on their own. Louis Liu Louis Liu, Founder and CEO of FOMO Pay, said, “AI agents are increasingly becoming active participants in commerce, capable of researching options, making decisions, and completing purchases on behalf of the people they serve. This shift will change consumer behaviour more profoundly than anything we have seen since the advent of mobile payments, and the infrastructure that powers those transactions must evolve with them. At FOMO Pay, we are building the infrastructure that makes this possible, payment rails that are not just fast and connected, but intelligent enough to support a world where AI agents, businesses and consumers move as one.”     Featured image: Edited by Fintech News Singapore, based on image by FOMO Pay via YouTube The post FOMO Pay Launches Merchant Soundbox for Cards, PayNow and Stablecoins appeared first on Fintech Singapore.

Singlife has appointed Leo Mun Wai as an Independent Non-Executive Director to the boards of Singapore Life Holdings and Singapore Life. He will also serve on the company’s Risk and Audit Committees. Mun Wai has more than 30 years of experience in the financial sector, including over two decades in senior regulatory roles and about a decade in board positions. Before moving into board roles, he held senior positions at the Monetary Authority of Singapore and retired as Assistant Managing Director, where he was responsible for the regulation and supervision of Singapore’s capital markets. He also served as Executive Director of Banking Supervision, overseeing foreign banks operating in Singapore. His public service roles included serving as a founding board member of the Casino Regulatory Authority and as a member of the Securities Industry Council. Mun Wai has also served on the boards of Great Eastern Life Assurance Singapore and Great Eastern General Insurance. He currently sits on the board of CapitaLand Integrated Commercial Trust, where he is a member of its Risk and Audit Committees. Ray Ferguson Ray Ferguson, Board Chairman of Singlife, said, “His extensive experience in regulatory oversight and governance, coupled with his expertise in market conduct and digital transformation, will further strengthen the skillset of our board. His insights will be valuable as we continue delivering innovative financial solutions and building long-term trust with our customers.”     Featured image: Edited by Fintech News Singapore, based on image by topntp26 via Freepik   The post Singlife Appoints Former MAS Official Leo Mun Wai to Board appeared first on Fintech Singapore.

India and Bhutan are set to introduce a cross-border remittance service through their postal networks under the planned UPU-UPI initiative. UPI, or Unified Payments Interface, is India’s real-time payments system that allows money to be sent and received instantly. The service will link the Universal Postal Union’s PosTransfer system with UPI to support remittances between the two countries. The initiative was one of the key highlights of a visit by India’s Secretary of Posts to Bhutan during which both sides also signed a memorandum of understanding on postal cooperation. The agreement sets out a broader framework for collaboration between India Post and Bhutan Post in areas including postal operations, technology, logistics, training and knowledge exchange. Both sides said the remittance link is expected to improve financial connectivity and widen access to digital remittance services in both countries. India also said it is ready to share its experience in postal financial services, including how postal networks can support financial inclusion and expand access to savings and other basic financial services.     Featured image credit: Government of India The post India and Bhutan to Launch UPI-Linked Postal Remittance Service appeared first on Fintech Singapore.

Ripple has joined the Monetary Authority of Singapore’s BLOOM initiative and teamed up with Unloq to pilot a programmable trade settlement use case. The initiative, led by MAS, is aimed at extending settlement capabilities using tokenised bank liabilities and regulated stablecoins. The pilot is intended to showcase a model for Singapore’s future development of interoperable settlement infrastructure for cross-border trade. The project will use Unloq’s SC+ trade finance infrastructure, which combines trade obligations, settlement conditions and financing workflows in a single execution layer. It will also use Ripple’s infrastructure, the XRP Ledger and Ripple USD, or RLUSD. The pilot will test how digital settlement assets can be used to address inefficiencies in cross-border trade settlement. Under the model, payments are released only when pre-agreed commercial conditions are met, such as shipment verification. The companies said this could improve risk transparency and support access to financing for SMEs. Fiona Murray Fiona Murray, Managing Director, Asia Pacific at Ripple said, “Singapore continues to take a leading role globally in providing the regulatory clarity necessary for the digital asset space to thrive. Ripple is incredibly excited to be part of BLOOM, an initiative that perfectly aligns with our commitment to compliant, real-world utility for blockchain technology.” Letitia Chau Letitia Chau, President and Chief Risk Officer of Unloq said, “BLOOM represents an important step toward modernising trade finance infrastructure in a controlled and regulated environment. Through SC+, we are demonstrating how digital settlement rails can be integrated into existing trade and financing workflows without disrupting commercial relationships. Collaboration with MAS and Ripple enables us to explore scalable, interoperable models for cross-border trade.”     Featured image: Edited by Fintech News Singapore, based on image by MAS The post Ripple Joins MAS’ BLOOM Initiative for Trade Settlement Pilot appeared first on Fintech Singapore.

Grab will buy back up to US$400 million of its shares over the next four months under its existing repurchase plan. The repurchases will be carried out through two agreements. They include a US$250 million accelerated share repurchase deal with JPMorgan Chase Bank and a contingent forward purchase agreement with Morgan Stanley worth up to US$150 million. Both transactions fall under the US$500 million share repurchase programme approved by Grab’s board in February 2026. Once completed, Grab will have used US$400 million of that amount, leaving US$100 million for further buybacks. Peter Oey “We view the current share price dislocation as a clear opportunity to enhance shareholder value. Our trajectory toward our 2028 $1.5 billion Adjusted EBITDA and 80% Adjusted Free Cash Flow conversion targets also underscores the operational leverage we are now realizing. By leveraging our robust balance sheet and net cash liquidity position, we continue to maintain a disciplined approach to capital allocation by investing in our rapidly scaling ecosystem while being committed to returning excess cash to investors.” said Peter Oey, Chief Financial Officer of Grab. Under the accelerated share repurchase agreement, Grab will pay US$250 million to JPMorgan for an initial delivery of about 54.9 million Class A ordinary shares. This represents around 80 percent of the total shares that may be repurchased based on the last closing price of the shares. The final number of shares repurchased under the agreement will be based on the average volume-weighted average price of Grab’s Class A ordinary shares on specified dates during the term of the transaction. That figure will be subject to a customary discount and other adjustments under the agreement. Grab expects the transaction to be completed by the second quarter of 2026. Under the contingent forward purchase agreement, the number of shares Grab may acquire will depend on the company’s share price performance over the term of the deal, subject to the agreement’s pricing terms and thresholds. The total amount payable under the agreement will not exceed US$150 million, with settlement scheduled for July 2026. Grab said both transactions will be funded from existing cash reserves. As of 31 December 2025, the company had gross cash liquidity of US$7.4 billion and net cash liquidity of US$5.4 billion. The remaining US$100 million under the repurchase authorisation gives it flexibility for further buybacks.     Featured image: Edited by Fintech News Singapore, based on image by thanyakij-12 via Freepik The post Grab to Buy Back Up to US$400 Million in Shares Over the Next Four Months appeared first on Fintech Singapore.

For decades, accepting card payments meant investing in dedicated hardware, like a separate terminal for every checkout point. Each tech evolution, from early card terminals to modern POS systems, often came with its own set of requirements and processes. Today, the landscape of in-person commerce is spinning on its axis. Businesses are moving away from traditional and stationary checkout counters, driven by the need for greater agility and the flexibility to meet evolving customer expectations. Mobile POS solutions are a strategic response to this, bringing payments closer to the customer, shortening the sales cycle, and delivering a faster and seamless checkout experience. Where Digital Expectations For Payments Meet Reality Take a step back and think about the Asia Pacific region as an example. Digital wallet adoption here is among the highest globally. Consumers increasingly expect transactions to be as instant and mobile as their smartphones. Recent Adyen research confirms this shift: “62% of shoppers already tap their phones to pay, making the fixed counter a relic of the past. By turning everyday devices into terminals, businesses can meet the need for speed and capture that high-value in-store traffic without the barrier of a queue.” This raises a critical question for businesses operating in markets like Hong Kong SAR China and Singapore. Sure, payment terminals work. But can they work smarter, with faster setups, quicker checkouts, and one less device to manage? Every second at checkout matters. Meeting these expectations requires payment solutions that remove additional hardware dependencies, reduce operational overhead and complexity, yet deliver frictionless checkout experiences that grow with your business. Sounds like a tall order? Well, the answer lies in Tap to Pay On iPhone (TTPOI) with Adyen. From Hardware to Software-First Flexibility Tap to Pay on iPhone represents a shift from device-dependent payments to a software-first, infrastructure-light approach. With Tap to Pay on iPhone and Adyen, new devices can be onboarded quickly, skipping traditional POS systems that tend to require procurement, installation, and maintenance. This agility allows businesses to respond swiftly to demand surges or launch temporary locations without complex hardware deployments. Simply equipping staff with iPhones transforms them into mobile points of sale, ready to serve customers anywhere, even at their own table. This flexibility aligns perfectly with the broader payments landscape across the Asia Pacific, where diverse payment preferences coexist. From QR codes in Southeast Asia to card-based systems in Hong Kong SAR China and Singapore, merchants need adaptable payment solutions. Tap to Pay on iPhone with Adyen provides a unified platform capable of accepting multiple payment methods, thereby enabling businesses to accommodate local consumer behaviour without adding operational complexity. The Checkout Experience That Counts While digital wallets and invisible payments dominate headlines, the physical moment of payment remains profoundly important. Those final seconds often define how customers remember their entire shopping experience, regardless of whether they’re using NFC-enabled cards, digital wallets or wearables to tap and pay. Friction, like waiting in line, juggling devices, or managing clunky hardware, erodes loyalty and reduces conversion. Mobile-first payments put checkout in the hands of staff on the sales floor, at tables, or in pop-up locations. Luxury brands like Prada and global retailers like Lululemon have demonstrated how mobile payments reduce queues, improve conversion, and let staff focus on customers rather than transactions. Lululemon’s deployment of Tap to Pay on iPhone with Adyen across Australia, the United Kingdom, France, Germany, and New Zealand exemplifies this transformation. Adyen’s unified platform enables consistent experiences for both customers and operational teams. By creating a single integration point for key markets, Lululemon freed up resources to focus on strategic initiatives while ensuring guests experience premium service even during peak periods. As Zoé Denom, Global Payment Operations Manager at Lululemon, notes: “The flexibility has been huge. The cost savings has immediate impact and also allow us to rethink future store designs.” This operational flexibility extends beyond immediate cost benefits. By removing the constraints of fixed checkout counters, retailers can focus on creating more open layouts, engaging spaces where staff can interact with customers throughout their journey rather than being tethered to traditional POS stations. The result is a retail environment that feels less transactional and more experiential, precisely what today’s consumers expect from brands. Enterprise-Grade Security and Compliance When a customer taps their iPhone, Apple Watch or other digital wallet at the merchant’s iPhone, privacy protection happens instantly and invisibly as the purchase is completed. Tap to Pay on iPhone uses the same technology that makes Apple Pay secure. Transactions are encrypted and processed through the Secure Element in real-time. Apple never sees what’s being purchased or who’s buying it. Card numbers and transaction data don’t touch the device or Apple’s servers. Source: Adyen Security matters because trust is earned through effort, yet lost in seconds. With PCI CPOC compliance built in and software-based risk management responding to fraud patterns in real-time across all locations, businesses can maintain the same level of trust as traditional POS systems, minus the vulnerability of physical hardware that can be compromised, stolen, or tampered with. Tap to Pay on iPhone does more than simplify checkout by removing the need for more hardware. It lays a strategic foundation for modern retail by simplifying operations, integrating seamlessly with existing systems, meeting customers where they are, and enabling businesses to scale rapidly, reduce costs, and enhance the overall shopper experience. Streamline Payments and Scale with Tap to Pay on iPhone Tap to Pay on iPhone, powered by Adyen, enables your business to accept all contactless payments, from credit and debit cards to Apple Pay and digital wallets, using just an iPhone. No additional terminals, complex installations, or hardware constraints. Discover how Tap to Pay on iPhone with Adyen can transform your in-person payment strategy and help your business stay agile, secure, and customer-focused. Featured image based on an image by Adyen The post Transform Any iPhone Into a Contactless Payment Device With Adyen appeared first on Fintech Singapore.

Revolut Singapore remained net profitable for a second straight year in 2025 as customers used the app more for everyday spending and transfers. The update came as parent Revolut reported record 2025 group revenue of US$6.0 billion, up 46 percent year on year, and profit before tax of US$2.3 billion, up 57 percent. In Singapore, subscription revenue rose 75 percent, card payment revenue increased by close to 20 percent and foreign exchange fee and spread revenue grew 6 percent. Average monthly transactions rose by nearly 20 percent, while retail e-wallet balances increased by more than 25 percent and business account balances grew more than sixfold. Revolut Singapore’s retail customer base expanded by more than 20 percent in 2025, while its business customer base grew fivefold. Young adults aged 18 to 34 now make up half of its retail customer base, and expatriates accounted for close to 30 percent of customers, up from 25 percent a year earlier. Revolut Deepens Everyday Use in Singapore Domestic transaction volumes rose by more than 30 percent year on year, while the number of domestic transactions increased by about 25 percent. Domestic transactions now make up nearly half of Revolut Singapore’s total activity. Peer-to-peer payment volumes within the app rose by close to 40 percent, while both the number and volume of virtual card payments increased by more than 55 percent. Product Push and Hiring Expansion in Singapore During the year, Revolut Singapore expanded its retail and business offerings. New additions included a robo-advisor, Flexible Cash Funds for businesses and merchant acquiring tools spanning account-to-account, online and in-person payments. It also integrated with Alipay to support transfers to China. Revolut Singapore nearly doubled its workforce from 2024 to 2025, with headcount rising by more than 95 percent. The company is targeting more than 300 employees locally within the next three years. Raymond Ng Raymond Ng, Chief Executive Officer, Revolut Singapore & South East Asia, said: “We’re seeing a clear shift from Revolut being used primarily for travel to becoming an everyday financial app, with strong growth in domestic spending, peer-to-peer payments, and increasing engagement with wealth products and our Kids & Teen offering. We remain focused on expanding our offering to meet the evolving needs of our customers while continuing to invest in local talent to support our long-term growth.”     Featured image: Edited by Fintech News Singapore, based on image by mrsiraphol via Freepik   The post Revolut Singapore Stays Profitable in 2025 as Subscription Revenue Jumps 75% appeared first on Fintech Singapore.

MariBank has launched a new investment product that gives customers access to Singapore equities from S$1, with no transaction fees. The product, called Mari Invest Singapore Equity, distributes the Amova Singapore Dividend Equity Fund SGD Class and is being rolled out first on an invite-only basis. It will be made available to the public through the MariBank app in early April 2026. Natalia Goh “This reflects our commitment to lowering barriers and helping customers grow their wealth confidently. Having invested through various economic and liquidity cycles over more than 25 years, Amova Asset Management has consistently demonstrated high discipline and delivered strong results, making them a natural partner for us.” said Natalia Goh, CEO of MariBank. The fund is managed by Amova Asset Management Asia Limited, formerly Nikko Asset Management Asia Limited. It invests mainly in equities listed on the Singapore Exchange, including stocks outside the Straits Times Index, as well as selected overseas-listed equities with similar characteristics. The fund focuses on companies with sustainable dividend yields and dividend growth potential, alongside undervalued firms showing positive fundamental change. It targets a monthly distribution of between 5 percent and 7 percent per annum of NAV per unit, based on its stated distribution policy. MariBank said payouts are not guaranteed and may be made from income and/or capital, and any payout is expected to result in an immediate reduction in NAV per unit. Amova is one of six appointed managers under the Monetary Authority of Singapore’s S$6.5 billion Equity Market Development Programme, which was first announced in May 2025. Eleanor Seet “Lowering investment barriers is integral to building a fundamentally deeper and more inclusive equities market. As one of the appointed managers under MAS’s Equity Market Development Programme, we see a strategic role in partnerships like our collaboration with MariBank, which reflects a shared commitment to progressive, investor-first solutions,” said Eleanor Seet, President and Head of Asia ex-Japan of Amova Asset Management Asia Limited. This launch adds to MariBank’s existing investment lineup, which includes Mari Invest Gold, Mari Invest Income and Mari Invest SavePlus. The bank said about one in three of its customers has invested in at least one of its investment products.     Featured image: Edited by Fintech News Singapore, based on image by thanyakij-12 via Freepik The post MariBank Rolls Out Singapore Equities Investment Product from S$1 appeared first on Fintech Singapore.

Former OCBC CEO Helen Wong’s 2025 pay fell 6.3 percent to S$12 million as the bank’s earnings eased from the year before, according to The Business Times. Wong retired as Group CEO at the end of 2025 with Tan Teck Long taking over as Group CEO from 1 January 2026. Her pay came in below the S$12.8 million she received in FY2024 as OCBC’s net profit fell to S$7.42 billion from S$7.59 billion a year earlier. Her remuneration package included a S$1.2 million base salary, S$6.3 million in cash bonus, about S$4.2 million in deferred shares, and S$323,000 in other benefits. OCBC still generated record income of S$14.6 billion in FY2025, up 1 percent from a year earlier, despite the drop in net profit. Higher fee income helped offset margin pressure, with non-interest income rising 16 percent to S$5.46 billion and wealth management fees up 33 percent. The bank has proposed a final ordinary dividend of S$0.42 per share and a special dividend of S$0.16 per share. With the interim dividend of S$0.41, total dividends for FY2025 reached S$0.99 per share, representing a 60 percent payout ratio. OCBC also said it remains on track to complete its S$2.5 billion capital return plan, comprising special dividends and share buybacks, by the end of FY2026. Wong’s FY2025 pay was in line with UOB CEO Wee Ee Cheong’s S$12 million package, while DBS CEO Tan Su Shan received S$9.6 million in her first year as CEO.     Featured image: Edited by Fintech News Singapore, based on image by OCBC The post Helen Wong Took Home S$12 Million in Her Final Year as OCBC CEO appeared first on Fintech Singapore.

Singapore police have arrested two more Malaysians over their suspected roles in a government official impersonation scam, bringing the total for similar cases this month to eight. The two men, aged 30 and 20, will be charged on 22 March and 23 March, respectively. Police said the case surfaced on 20 March after a 62-year-old woman reported receiving calls from people claiming to be from M1 and the Monetary Authority of Singapore over an overdue S$350 bill that could not be deducted from her bank account. The conversation later moved to WhatsApp, where she was told purchases had been made using her accounts. After she said she did not recognise the transactions, she was referred to a man posing as an MAS investigation officer. He allegedly told her she was linked to a money laundering case and told her to declare her valuables. After learning she had 8.6kg of gold, he instructed her to hand it over for inspection to prove her innocence. The woman was then told to place the gold in a bag and head to the vicinity of the MAS building, where a man approached her car, said a codeword and took the bag. She later checked with a security guard, who told her the man was not affiliated with MAS, before calling the police. Two Arrested in Follow-Up Operation Police later identified the two suspects, who were detained in Singapore on 21 March. The 30-year-old was held while trying to leave the country, while the 20-year-old was arrested near Woodlands. Preliminary investigations found the pair had allegedly been directed by people believed to be part of a transnational scam syndicate to collect valuables from victims and pass them to others. They will be charged under Section 51 of the Corruption, Drug Trafficking and Other Serious Crimes (Confiscation of Benefits) Act 1992 for assisting another to retain benefits from criminal conduct. The offence carries up to 10 years’ jail, a fine of up to S$500,000, or both. Police said they continue to observe an increasing trend of Malaysian nationals travelling to Singapore to help scam syndicates collect valuables from victims. The arrests follow a similar case announced on 19 March that brought the total then to six Malaysians arrested and charged in similar government official impersonation scam cases within two weeks.     Featured image: Edited by Fintech News Singapore, based on image by tehcheesiong via Freepik   The post Singapore Arrests Two More Malaysians Over Govt Official Impersonation Scam appeared first on Fintech Singapore.

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.