Singapore’s central bank is urging financial institutions to prepare for a rapid transformation driven by artificial intelligence, tokenisation, and quantum computing, while strengthening governance and cybersecurity as increasingly autonomous AI systems reshape the financial system.
Chia Der Jiun, managing director of the Monetary Authority of Singapore (MAS), said AI was advancing and being adopted faster than the other emerging technologies, making it the most immediate challenge and opportunity for the financial sector.
“We are all standing on the cusp of great technological transformation over the next 10 years,” Chia said in a special address at the Global FinTech Fest 2026 on Friday.
Tokenisation could take several more years to scale, while quantum computing was likely five to 10 years away, he said. Financial institutions should nevertheless begin preparing for quantum resilience now.
AI models already perform at expert or specialist levels in areas including coding, graduate-level science and mathematics, and general knowledge work, Chia said. Gaps remain in complex interpretation, strategic judgment, decision-making and human interaction.
Corporate adoption is also accelerating, although a much smaller proportion of companies report significant productivity gains.
Chia said those gains were likely to increase as employees and organisations become better users of AI through training, process redesign and new products.
In Singapore’s financial sector, AI is already being deployed at scale in fraud detection, credit underwriting, risk management, regulatory compliance, marketing, customer service and document processing.
For large, well-managed financial institutions, MAS is focusing on safety, guardrails and accountability rather than encouraging adoption, Chia said.
But the central bank also wants to prevent AI from becoming a competitive advantage available only to the largest 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,” Chia said.
MAS has launched Pathfin.ai, a platform and programme designed to share and match validated AI solutions across the financial industry.
The initiative now has more than 300 participants, with a growing number of successful matches, he said.
AI and financial crime
MAS is also testing AI at the system level to address problems that individual financial institutions cannot solve alone.
Chia said the central bank was working with law enforcement and banks to test different AI models using cross-bank and public-private data to improve the near-real-time detection of suspicious accounts and transactions.
The goal is to detect scams and fraud sooner, intervene faster and reduce losses. MAS expects findings from the work by the end of this year.
The central bank is also developing industry-wide approaches to AI governance.
MAS and the financial industry published a generative AI risk framework in 2023, followed in 2025 by two AI Risk Management Handbooks covering banking, insurance and capital markets.
MAS has separately issued Guidelines for AI Risk Management for public consultation. The guidelines set supervisory expectations for governance, risk management and AI life-cycle controls.
Chia said the guidelines would establish “what” financial institutions should do, while the handbooks would provide guidance on “how” to implement those requirements.
MAS has also worked with industry on SAFR, or Safeguards for Agentic Finance at Runtime, a framework for AI agents carrying out increasingly consequential financial tasks.
The white paper, published in July, covers safeguards including establishing an AI agent’s identity and authority, evaluating actions against controls before execution and maintaining an audit record.
Cybersecurity risks intensify
The rapid improvement of AI is also increasing cybersecurity risks, Chia said.
He cited what he called the “Mythos moment”, involving AI capable of vulnerability discovery and exploitation at speed and scale, and an “Open AI agent attack moment”, in which autonomous AI agents worked in concert to escape controls and launch successful cyber breaches.
High-severity Common Vulnerabilities and Exposures, or CVEs, rose sixfold this year to 2,200 compared with the average of the preceding three years, Chia said. CrowdStrike has reported an 89% increase in AI-enabled cyber attacks, he added.
AI is also enabling more persuasive deception through deepfakes and other techniques.
However, reported successful breaches have not risen at the same rate as vulnerability discovery and attacks, partly because of model guardrails and the continued effectiveness of multilayered cyber defences, Chia said.
Such defences include strong authentication, rapid patching, network segmentation, modular architecture, access controls, endpoint detection, database monitoring, and incident response.
Financial institutions should use the time available to strengthen those defences and deploy AI for cybersecurity itself, he said.
AI could help discover and fix vulnerabilities, conduct continuous code scanning, accelerate testing and patching, improve real-time threat detection and strengthen incident response.
Faster movement of money
Looking ahead, Chia said technology would increasingly remove “transaction frictions and decision frictions” from the financial system.
AI could be used to optimise cash flows, cash management, payments and investments, with decisions made almost instantaneously and AI agents deployed to execute them.
“Competition for the business of managing money will be heightened,” he said.
That could have significant consequences for incumbent financial institutions and challengers, as well as for regulators and financial stability.
Chia said central banks and regulators needed to begin considering those implications as financial activity becomes increasingly automated.
Singapore-India fintech ties
Chia also highlighted growing financial cooperation between Singapore and India, including agreements covering financial innovation, supervisory cooperation and digital assets.
The two countries launched the UPI-PayNow linkage in 2023, enabling faster and cheaper cross-border retail payments and remittances.
Transaction volumes have more than doubled each year since its launch, and MAS expects growth to accelerate further this year.
The next step is Nexus, a multilateral fast-payment interconnection initiative whose founding members include Singapore and India.
Rather than requiring every country to establish separate bilateral links, Nexus allows payment systems to connect once to a common framework and reach multiple jurisdictions.
Chia cited the partnership between Singapore AI fintech Pints AI and a large Indian insurer as an example of practical cross-border fintech cooperation.
The companies used AI to improve the efficiency and speed of automated checks and information preparation for the insurer’s underwriters, combining AI capabilities with human expert judgment.
“Two countries, two firms of very different sizes, one problem, one practical solution,” Chia said.
He said Singapore and India should use fintech platforms to develop more such partnerships as both countries seek to capture the benefits of AI while maintaining trust, stability and resilience in their financial systems.