The Future of Suptech: From Compliance to Infrastructure
By Dr. Carlos Leon ( Director of Central Banks and Financial Market Infrastructures) and Dr. Kimmo Soramäki (Founder & CEO)
Five years ago, FNA was honored to win the inaugural G20 TechSprint challenge, looking for new innovative technologies to resolve operational problems in the areas of regulatory compliance (Regtech) and supervision (Suptech). Recently, in a discussion, we were asked to reflect on how Suptech has evolved since then—and what the next five years may hold. It’s an important and timely question, and one that deserves careful consideration.
We believe that over the next 5–10 years, the most transformative shift in the intersection of finance and technology will not be driven by a single innovation, but by a new supervisory paradigm. This paradigm redefines the role of supervisors from periodic overseers into real-time systemic enablers, supported by shared infrastructures, intelligent analytics, and integrated data flows. These developments signal a transition from supervision as compliance enforcement to supervision as infrastructure and intelligence.
This article explores three anticipated breakthroughs: the rise of shared utilities with common standard operating procedures (SOPs), the deployment of real-time Digital Twins for financial systems, and the fusion of supervisory and payments data to generate systemic intelligence.
1. From Institution-Specific Compliance to Shared Supervisory and Industry Utilities
One of the most profound changes will be the migration from fragmented, institution-specific supervisory processes toward sector-wide shared utilities, jointly operated by authorities and the industry.
Rather than each bank implementing bespoke regulatory technology stacks, we will see the rise of national platforms that host:
Real-Time Gross Settlement (RTGS) Liquidity Optimization Utilities: These include overlay Liquidity Saving Mechanisms (LSMs) that optimize payment sequencing and timing without altering core RTGS infrastructure (see e.g., FNA paper on LSM’s as an Overlay Service).
National Anti-Scam Utilities: Enabling real-time detection, tracing, freezing, and restitution of fraudulent transactions across banks and payment service providers. These platforms are built on AI models and shared SOPs (e.g., Malaysia’s National Fraud Portal).
Cross-Institution AML Monitoring: Utilities for detecting suspicious transaction patterns and inter-institutional money laundering schemes, operated via secure collaborative analytics environments that enable tracing funds across financial institutions, payment systems, and jurisdictions (e.g., Anticipatory and Adaptive Anti-Money Laundering initiative by DARPA).
These shared utilities are fast to deploy, interoperable across systems, and aligned with policy objectives. They signal the move to regulatory infrastructure-as-a-service, a model that combines legal coherence with technical agility.
2. Real-Time Digital Twins for System-Wide Policy Simulation
Another defining shift will be the mainstreaming of Digital Twins, i.e., real-time, data-driven replicas of financial systems. Unlike static models, Digital Twins evolve continuously with actual system behavior and enable “learning-by-simulating” rather than risky and inflexible “learning-by-doing.” (see e.g., From RTGS Simulation to RTGS Digital Twins – Why are they more powerful?)
Deployed by central banks and financial market infrastructures such as the Saudi Central Bank, Bank of England, Deutsche Bundesbank, and Payments Canada, Digital Twin platforms replicate the internal logic of RTGS, CBDC, and settlement systems, supporting:
Intraday liquidity analysis and optimization
Crisis response simulations (e.g., participant default, cyber incidents)
Design evaluation for new features or market infrastructure interconnections
CBDC design, adoption, and interoperability testing
These environments empower supervisors and policymakers to test future scenarios safely before real-world deployment, thereby transforming financial oversight into a proactive and evidence-driven discipline.
3. Systemic Intelligence from the Fusion of Supervisory and Payments Data
A third frontier will be the fusion of historically siloed data streams into a unified supervisory intelligence layer. By combining granular supervisory reports (e.g., balance sheets, exposures) with real-time transaction data (e.g., from RTGS, instant payment systems), authorities can gain:
Network views of systemic risk: Identifying liquidity bottlenecks, monitoring direct and indirect interdependencies in interbank and financial markets, and understanding contagion risks at different layers in the financial system
AI-driven anomaly detection: Targeting high-value or policy-relevant anomalies that deviate from behavioral baselines in supervisory reports and transactional data
Supervisory triggers and alerts: Based on algorithmic thresholds and pattern recognition models, supporting early intervention
This data fusion is underpinned by machine-readable regulatory frameworks, large language model (LLM) driven analysis of unstructured data, and interoperable analytics modules. It supports a modular, real-time suptech stack that spans prudential, payments, and conduct domains.
Conclusion: From Compliance to Infrastructure
Taken together, these breakthroughs represent a transformation in both capability and posture. Supervisors will increasingly act not only as monitors of compliance but as orchestrators of system-wide stability and efficiency. Suptech will cease to be a back-office analytics function and become an essential layer of the financial ecosystem’s operating infrastructure.
To realize this vision, authorities must invest in interoperable data pipelines, agile policy-simulation environments, and shared governance for sector-wide utilities. Suptech is no longer a collection of tools. It is a strategic capability that enables anticipatory, adaptive, and collaborative regulation in a complex financial world.
The next decade will define which jurisdictions lead this shift. Those who adopt infrastructure thinking, intelligent automation, and integrated oversight will not only enhance financial stability but also unlock systemic efficiencies, trust, and innovation at scale.
