Good morning to all. It is a great pleasure to participate in the Global FinTech Festival, one of the largest FinTech events in the world.
The AI Inflection Point
Let me start by noting that we are all standing on the cusp of great technological transformation over the next 10 years. Three technologies stand out.
The AI transformation is already upon us. Tokenisation may take a little more time to scale, perhaps another few years. Quantum computing is a little further out. Experts estimate 5-10 years. But it is not too early to prepare now for quantum resilience.
All three technologies have far reaching consequences but let me focus on AI. The technology is advancing the most rapidly, and adoption is spreading the fastest.
Model performance is clearly advancing rapidly. It is well known that AI models already perform at expert or specialist level in many defined tasks, such as in coding, graduate-level science and mathematics, and general knowledge work.
Where there are still gaps to human performance are in areas requiring complex interpretation, strategic judgement and decisions, and human interaction skills.
Corporate adoption of AI is progressing rapidly. While a high proportion of companies report using AI, a much smaller proportion report significant productivity gains.
The proportion of firms reporting productivity gains are likely to increase as employees and organisations become better users of AI through training and process and product redesign.
In time to come, we can expect AI to become a foundational capability for organisations. Those that use it well and safely will innovate faster, serve customers better, and unlock new opportunities.
The challenge for regulators is to support innovation for competitiveness and growth; and also steer it on a course that is safe and sustainable.
Innovation must be founded on trust and stability if it is to scale.
What We Are Seeing in Singapore's Financial Sector
In Singapore's financial sector, we are seeing wide AI adoption. Common use cases include fraud detection, credit underwriting, risk management, regulatory compliance, marketing, customer service and document processing. These use cases have moved beyond pilots and are being deployed at scale.
The largest, well-managed financial institutions need no encouragement. They are in rapid adoption. Our focus with them is good governance — around safety, guardrails, and accountability.
AI should not only be a competitive tool wielded by the largest financial institutions. We should avoid a winner-takes-all dynamic if we are to maintain a competitive and stable financial system to support the public and the economy.
We want the benefits of AI to spread across the whole industry. Our aim should be for a sustainable productivity uplift for the entire sector.
Pathfin.ai
To that end, MAS launched Pathfin.ai. This is a platform and programme to share and match validated AI solutions across the industry.
Smaller financial institutions can lower the cost and effort of finding and deploying effective AI solutions. If a solution has been validated and works, we want to make it easier for others to find and implement it.
We now have over 300 participants and a growing number of successful matches.
Solving Problems as a Whole System
AI also gives us an opportunity to solve problems at the system level — problems no single financial institution can solve alone.
Detecting and disrupting scams and fraud is an example. MAS is working with the law enforcement agency, and the banking industry. We are testing different AI models, drawing on cross-bank and public-private data, to improve the detection of suspicious accounts and transactions in near-real time.
The aim is to detect sooner, intervene faster and reduce losses. We expect to have findings from this work by the end of this year.
Developing Sound Practices Together
To propagate sound AI governance and risk management in the financial industry, we have found it very useful for MAS to collaborate with the industry.
The first step was taken in 2023. MAS and the industry collectively published a Gen AI risk framework to establish a common understanding and baseline.
The second step was taken in 2025. We published jointly with the industry two AI Risk Management Handbooks to promote good practices. These recommended practices were applicable across the banking, insurance, capital markets sectors.
MAS has also issued a set of Guidelines for AI Risk Management for public consultation. These guidelines set out supervisory expectations for governance and risk management, as well as AI life cycle controls and capabilities.
The Guidelines will work in tandem with the Risk Management Handbooks. The first will set out the what. The latter will set out the how. For example, the Guidelines require financial institutions to perform risk materiality assessments, while the Handbook provides examples of how such assessments can be implemented.
Updating good AI risk governance practices will be important as the technology progresses fast.
The latest joint initiative with industry is SAFR — Safeguards for Agentic Finance at Runtime. As AI agents take on more consequential tasks and are given more autonomy, it is essential to ensure clear accountability, oversight and governance.
SAFR was published as a white paper in July this year. It sets out a framework for implementing runtime safeguards such as establishing an agent's identity and authority, evaluating agent actions against controls before execution, and maintaining a clear audit record.
All our work in this space of AI risk management and governance is published. We see this as a global public good. India too is undertaking important work in this area. The Reserve Bank of India has published the Framework for Responsible and Ethical Enablement of Artificial Intelligence, or FREE-AI.
It sets out the principles and recommendations for responsible AI adoption, placing accountability, fairness, resilience and trust at the centre. This is an important contribution to safe and responsible adoption of AI in the global financial system.
Cybersecurity
Let me say a few words about cybersecurity in an AI age. This has been a watershed year.
First was the Mythos moment — AI capable of vulnerability discovery and exploitation at speed and scale.
Second was the Open AI agent attack moment — AI agents working autonomously and in concert to escape its controls and launch successful cyber breaches.
It is therefore no surprise that with more capable AI models we have seen a significant increase in vulnerability discovery and also cyber attacks.
High severity Common Vulnerabilities and Exposures (CVEs) went up 6 times this year to 2200 compared to the average of the preceding 3 years. Crowdstrike reports an 89% increase in AI-enabled cyber attacks. We know also that AI is enabling more persuasive deception through deepfake and other means.
The good news is that while vulnerability discovery and attacks have gone up, reported successful breaches have not surged to the same extent.
One reason is model guardrails against harmful use. Another is that a well-implemented multi-layered cyber defence is still effective.
These layers include strong authentication, rapid patching, network segmentation, modular architecture, access control, endpoint detection, database monitoring, incidence response. This has bought us time.
But we have to expect models to get more capable, and determined parties to jailbreak guardrails.
We have to make use of this time to strengthen sound implementation of multi-layered cyber defences, and steer our financial institutions to make greater use of AI for cyber defence.
AI can be used to discover and fix vulnerabilities first, perform continuous code scanning, enable faster testing and patching, strengthen real-time threat detection, and enhance incident response.
In these areas of AI governance and cyber resilience, there is considerable scope for regulators and industry in Singapore and India to learn from one another as our financial systems face these common challenges.
What Lies Ahead
What can we expect from technology and AI in the years ahead? The trajectory of technology is that it is taking frictions out of the system — transaction frictions and decision frictions.
Imagine AI being deployed to optimise cashflows, cash management, payments, investments. Decisions are made near instantaneously and agents are deployed to execute. We can expect money to move around more quickly for smaller incentives.
Competition for the business of managing money will be heightened.
There will be large implications for incumbents and challengers in the financial industry. There will also be regulatory and financial stability implications that central banks and regulators have to start considering.
These are serious questions where platforms like the GFF can make a real contribution through dialogue and exchanges.
The Singapore-India Partnership
Let me turn to the financial partnership between Singapore and India. We have built strong and enduring pillars of partnership.
In 2018, the Department of Economic Affairs of the Government of India signed an MOU with MAS to strengthen financial innovation cooperation. In 2022, an MOU was signed with the International Financial Services Centres Authority (IFSCA) to enhance supervisory cooperation. In 2025, an MOU was signed with the Reserve Bank of India on digital asset cooperation.
In 2023, our Prime Ministers launched the UPI-PayNow linkage. This enabled cheaper, faster and safe cross-border retail payments and remittances. This was India's first cross-border real time payment systems linkage and Singapore's second. Transaction volumes have more than doubled each year since launch. We expect volumes this year to grow even faster.
The next step is Nexus, the multilateral fast-payment interconnection initiative. Singapore and India are both founding members of Nexus. Instead of every country building a separate bilateral connection, each payment system connects once to a common framework and reaches multiple jurisdictions.
PayNow-UPI showed what can be achieved bilaterally. Nexus gives us the opportunity to take that idea to multilateral scale.
India's UPI is a clear demonstration of innovation and leadership in digital payments globally. It has served as a north star for many countries seeking to democratise access to fast and cheap payments services.
MAS published earlier this year a roadmap to guide the further development of our digital payments infrastructure. India's UPI was among the important references for MAS.
In the area of FinTech partnership, it is about bringing companies together — FinTechs and financial institutions from India and Singapore finding opportunities for collaboration and partnership.
Let me give one example.
Pints AI, a Singapore AI FinTech and winner of the 2023 Singapore-India Hackathon, partnered with a large Indian insurer. They used AI to significantly raise the efficiency and speed for running automated checks and preparing information for the insurer's underwriters. A pairing of AI capabilities for preparing information with human expert judgement and decision-making.
Two countries, two firms of very different sizes, one problem, one practical solution. That is what good FinTech partnership looks like. The parties are now developing a white paper to turn this into a practical reference for other financial institutions.
We want to see more of this. The Singapore FinTech Festival (SFF) and GFF are where these partnerships can begin. We want to encourage innovative FinTechs and financial institutions from both our countries to use both these platforms well.
Closing
Let me conclude.
We are on the cusp of significant transformation. AI is the technology advancing most quickly and adopted most rapidly.
Processes in financial institutions will be redesigned and transformed. Employees will need to be trained so as to get the most benefits out of AI use.
As AI is deployed in more complex functions and given more autonomy, it must be accompanied by strong governance and controls. As AI advances, there will also be significant implications for cyber security and the resilience of our financial infrastructure.
How money is used, transacted and moved could also be transformed. The approaches that regulators take have to keep pace with these rapid developments.
Innovation and technology brings both opportunities and challenges. India and Singapore have much common ground to share and learn from each other's approaches, towards a common objective that technology and innovation brings safe and sustainable benefits.
I wish you all fruitful connections and new inspiration at the Global FinTech Festival.