The Innovation Leaders Residency gave Teenoosha the space to translate a long-standing supervisory challenge — reactive, fragmented AML/CFT oversight — into a concrete AI-driven intelligence platform for dynamic risk profiling and real-time anomaly detection. This blog reflects on the lessons from both the Residency and SupTech Week 2025, arguing that SupTech succeeds when it is treated as a supervisory transformation initiative, not an IT project.
Author: Teenoosha Boyjoo, former Acting Manager, Financial Services Commission of Mauritius
This article represents the author’s personal perspectives based on research conducted during the Innovation Leaders Residency initiative, and attending SupTech Week 2025.
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My time in the Innovation Leaders Residency provided a critical bridge between these observations and practical action. The Residency offered space to step back from day-to-day supervisory demands and focus on a fundamental question: how can supervisors move from reactive oversight to proactive, intelligence-led supervision in an increasingly complex financial crime landscape?
The project I developed during the Residency—an AI-driven supervisory intelligence platform for dynamic risk profiling and real-time anomaly detection—was shaped directly by this question. Anchored in the Mauritian AML/CFT context, the project responds to well-known supervisory pain points: fragmented data, static risk assessments, high false positives, and delayed detection of emerging risks.
Rather than proposing a single tool, the project focuses on supervisory intelligence as a capability. It integrates multiple data sources (regulatory returns, STRs, transaction monitoring outputs, and external risk signals) to generate dynamic risk scores for regulated entities, identify behavioural anomalies in near real time, and present insights through intuitive supervisory dashboards. Importantly, explainability and governance are built into the design from the outset—reflecting the reality that supervisors must justify and defend their decisions.
The Residency reinforced a critical insight: SupTech succeeds when it is framed as a supervisory transformation initiative, not an IT project.
The AI reality check: lessons from the AI summit New York
Moving between SupTech Week and the AI Summit New York was a study in contrasts. The AI Summit buzzed with confidence—if not urgency—around GenAI deployment. Conversations revolved around speed, scale, and competitive advantage. In contrast, SupTech discussions were more cautious, centering on data quality, explainability, legal mandates, and accountability.
This caution is not resistance to innovation—it is responsibility. Supervisors are not deploying AI to optimise marketing funnels or automate customer support. We are developing systems that can influence market stability, enforcement actions, and consumer protection outcomes. The consequences of failure are systemic, not only reputational.
The State of SupTech Report 2025 notes that only 27% of authorities are piloting or exploring Generative AI, citing persistent constraints around data quality, privacy, and skills. From my perspective, this measured pace is appropriate. The gap between enterprise AI enthusiasm and supervisory caution is not a weakness—it reflects the higher bar that public authorities must meet.
What actually works: lessons from the field
Some of the most valuable moments at SupTech Week came not from keynote sessions, but from candid exchanges where supervisors shared what is actually working in production environments.
Three lessons stood out.
Start with data governance, not algorithms.
Authorities making real progress had invested years in building reliable, interoperable data foundations before introducing advanced analytics. No AI model can compensate for poor data quality.
Focus on specific supervisory pain points.
Successful SupTech applications were tightly scoped: automating repetitive compliance checks, visualising complex ownership structures, detecting outliers in STR filing behaviour. Incremental wins matter.
Build internal capability alongside partnerships.
Authorities scaling SupTech effectively were not merely procuring solutions. They were developing multidisciplinary teams who understood both the technology and the supervisory context well enough to adapt tools over time.
These lessons strongly echoed the design choices made in my ILR project, particularly the emphasis on modularity, explainability, and supervisory ownership.
What I took back
If I distil my experience—from the Innovation Leaders Residency to SupTech Week and the AI Summit—into actionable insights, four stand out:
- Strategy before solutions. SupTech must be anchored in a clear supervisory strategy aligned to outcomes, not technology trends.
- Honest conversations about constraints matter. Progress accelerates when authorities openly discuss what is not working as well.
- Supervisors and technologists must learn each other’s language. Misalignment here remains one of the biggest barriers to scale.
- Deliberate modernisation is not slow modernisation. Sequencing matters, and foundations enable scale.
Looking ahead
The Innovation Leaders Residency reinforced a simple but powerful insight: innovation in supervision is not about chasing technology trends, but about reimagining how regulators use information to protect financial integrity. My SupTech – driven project developed during the Residency represents one attempt to operationalise this vision—moving from reactive oversight toward proactive, intelligence-led supervision.
As financial systems continue to evolve, supervisors face a choice. They can continue to rely on increasingly strained legacy tools, or they can invest thoughtfully in capabilities that allow them to anticipate risks, prioritise resources, and demonstrate impact. The experiences of 2025—from the Residency to SupTech Week—suggest that the latter path is not only desirable, but increasingly unavoidable
As I return to the daily work, I am struck by the privilege—and responsibility—of operating at a moment where technology can genuinely transform how we safeguard financial systems. But transformation requires more than tools or enthusiasm.
It requires evidence, humility, and intentional design. It requires recognising that SupTech is not a destination, but a journey toward more effective, credible, and resilient supervision.
The convergence of SupTech Week and the AI Summit was not accidental. It reflects the moment we are in: one where supervisory innovation must accelerate, even as rigor and accountability remain non-negotiable. The authorities that strike this balance will be the ones best positioned to navigate the decade ahead.
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For further information, we encourage you to read the State of SupTech Report 2025, access session recordings and engage in discussions on GovSpace.io.
