Bangkok, 29 May 2026 – More than 90 professionals gathered for a training programme organized by Thailand's Specialized Financial Institution Development Fund under the Ministry of Finance. The full-day event brought together officials from the Ministry of Finance, senior representatives from the Ministry of Finance, experts from Specialized Financial Institutions (SFIs), and key ecosystem partners. Three technology organizations were invited to contribute international expertise and practical frameworks: Business Online Public Company Limited (BOL), TrustDecision Thailand, and Huawei.
The agenda addressed a question at the heart of Thailand's next decade of financial development.
How can government agencies, regulators, and technology partners work together to strengthen the country's Specialized Financial Institutions — not just as safety-net lenders, but as modern, data-intelligent engines of national financial stability and inclusion?
Thailand's SFIs: A Legacy Worth Strengthening
Thailand's network of Specialized Financial Institutions, including BAAC, the Government Savings Bank, Government Housing Bank, SME Bank, and EXIM Thailand, was built on a compelling premise: that financial access should not be reserved for those who already have it. These institutions have, for decades, extended credit, savings products, and housing finance to segments of the population that commercial banks have historically found difficult to serve.
Thailand's financial inclusion story is one of genuine progress. The National Credit Bureau today tracks approximately 80 million individual accounts, reflecting a credit ecosystem of real scale and depth. Household participation in formal financial services has grown substantially, underpinning consumer activity and economic resilience across the country.
Yet progress creates its own imperatives. As Thailand's financial system matures and digitizes, the data infrastructure that supports sound lending decisions, early risk detection, and fraud prevention must also mature with it. The training was a recognition of the pivotal role SFIs have in driving Thailand's financial inclusion agenda while also highlighting the need for innovative tools and infrastructure to propel it further, with greater precision, resilience, and confidence.
The Case for a National Data Foundation
One of the training's central themes was the strategic opportunity Thailand has to elevate financial data to a national-level asset.
The programme explored how peer economies in Asia, including China, Singapore, and Hong Kong, have invested deliberately in shared, interoperable financial data infrastructure, enabling lenders, regulators, and policymakers to make better decisions at every level of the system. For Thailand, the proposed National Central Database System represents a comparable strategic inflection point: a shared, governed platform that can aggregate credit, risk, and financial behavioral data across SFIs and other institutions.
The training provided a forum to examine what technical, regulatory, and governance foundations are needed to make this vision operational, and what the international experience tells us about where to start.
Business Online PCL, as Thailand's leading financial data and analytics company with over two decades of experience serving government agencies and major financial institutions, was well-positioned to anchor this conversation. BOL's platform infrastructure and credit bureau partnerships, including its work with Dun & Bradstreet and strategic alignment with CTOS Malaysia, make it a central node in Thailand's evolving data ecosystem.
Credit Intelligence for a New Generation of Borrowers
A second major theme was the transformation of credit assessment, and what it means for the populations Thai SFIs are mandated to serve.
Traditional credit scoring relies on bureau records: a history of borrowing, repayment, and account activity within the formal financial system. For individuals who have operated largely outside that system, including rural workers, micro-entrepreneurs, and first-time borrowers, the bureau record is thin or absent. This has historically created a tension at the heart of SFI lending: the people most in need of credit are also the hardest to assess under conventional models.
Alternative data changes this equation. Mobile behavior, digital footprints, multi-platform loan activity, device-level signals, government employment and income records — these sources can construct a meaningful, AI-validated picture of creditworthiness even where a bureau record does not yet exist.
TrustDecision's work in this space, which covers the Thai market alongside deployments across Southeast Asia, the Middle East, and Latin America, was brought to the training as a concrete example of what is now operationally possible. The company's alternative credit scoring and data intelligence solutions, including identity verification via Thai ID cards, repayment behavior analytics, and AI-powered credit rating assessment, offer SFIs a pathway to more inclusive and more accurate lending decisions. For institutions like BAAC and SME Bank, whose borrower bases overlap significantly with Thailand's credit-underserved population, this capability is not incremental. It is foundational.
The Fraud-AML Convergence: Why Silos Are No Longer Sufficient
The training also addressed one of the most pressing operational challenges facing modern financial institutions: the convergence of fraud risk and anti-money laundering (AML) compliance into a single, interconnected threat landscape.
Historically, fraud prevention and AML have been managed by separate teams, running separate systems, with separate data. This architecture made operational sense in a world of branch transactions and paper records. It is increasingly insufficient in an environment of real-time payments, digital onboarding, and sophisticated organized crime networks that exploit both simultaneously.
TrustDecision's experience across the banking, fintech, and payments sectors shows that the entities driving fraud, including mule account networks, synthetic identity rings, and coordinated cash-out operations, are often the same entities moving illicit funds. Knowledge graph-based detection maps relationships between accounts, devices, IP addresses, and identity documents to surface network-level risk, closing the gap that transaction-level analysis leaves open. Deployed in real time and at scale, this approach enables SFIs to meet FATF compliance obligations while simultaneously reducing fraud losses. Not as two separate programs, but as one.
Thailand's active effort to meet FATF standards, including the Data Bureau initiative under the Subcommittee on Financial Data Integration and phased cross-agency data sharing, makes this convergence model directly relevant to the country's near-term regulatory agenda.
Building the Platform: Architecture, Compliance, and Governance
The afternoon's sessions turned to implementation: the practical architecture of a national data platform and the governance model needed to sustain it.
Huawei's contribution to the training was grounded in the technical and organizational realities of deploying large-scale government data infrastructure. The sessions examined national-level data platform design; secure data sharing frameworks compliant with Thailand's Personal Data Protection Act (PDPA) and built on Zero Trust security principles; Hybrid/Multi-Cloud and inter-agency network design; and governance models that enable decentralized data management under common standards.
The PDPA dimension is particularly significant. Thailand's data protection framework, which applies fully to banks and SFIs, requires explicit consent, data processing agreements, and robust access governance for all personal data sharing. Any national database initiative must embed these requirements from the ground up — not as a compliance add-on, but as a design principle. Zero Trust architecture, which verifies every access request continuously rather than relying on perimeter security, is the international standard for environments where sensitive data must be shared across institutional boundaries without being exposed.
A structured group workshop, facilitated in the afternoon, gave participants the opportunity to exchange perspectives on the policy priorities and implementation barriers they see from their own vantage points, translating the day's presentations into a more grounded, actionable dialogue.
A Signal, Not Just an Event
The presence of the Director General of the Fiscal Policy Office to formally open the programme was a meaningful signal. The FPO is the Ministry of Finance's analytical and policy engine, responsible for economic forecasting, fiscal strategy, and SFI oversight. Its engagement at this level reflects an institutional seriousness about the data infrastructure agenda that goes beyond any single training event.
Thailand is hosting the IMF-World Bank Group Annual Meetings in 2026, a moment of heightened global visibility for the country's financial governance and reform credibility. The work being done to modernize the SFI ecosystem, build shared data infrastructure, and equip financial institutions with AI-driven risk capabilities is directly relevant to how Thailand is seen, and how it sees itself, as a maturing financial center in Southeast Asia.
For TrustDecision, participating in this programme reflects its long-term commitment to Thailand and its continued investment in building a strong local presence and team to serve the market. Through close collaboration with financial institutions, regulators, and ecosystem partners, TrustDecision remains dedicated to empowering organizations with intelligent decisions to identify risks, reduce losses, and unlock sustainable growth for both institutions and the communities they serve.
The financial system that Thailand deserves is one where no creditworthy borrower is turned away for lack of data, where fraud is detected before losses occur, and where the institutions built to serve the many have the infrastructure to do so safely and sustainably.
That system is being designed now. We are proud to be part of the conversation.
