Market-level suptech solution to enhance financial consumer complaints analysis.
We designed and implemented a working prototype for a market-level SupTech solution to strengthen this financial authority’s consumer protection and market conduct supervision. The solution automated the collection and reporting of consumer complaints data, integrating new, granular datasets from supervised entities and external sources. This improved data flow enhanced the authority’s ability to conduct data-driven regulation, informed decision-making, and more timely interventions.
The prototype was designed for extensibility, allowing future integration of advanced features such as AI-powered trend analysis, root cause identification, risk detection, benchmarking across financial institutions, and real-time supervisory dashboards. Eventually, the solution could enable predictive analytics, providing early warning signals for emerging market risks and consumer harm.
Throughout the project, various AI and machine learning techniques were explored to evaluate their potential for enhancing supervisory processes. This proof-of-concept demonstrated the feasibility and value of transitioning from reactive complaint handling to proactive, intelligence-led supervision, laying the groundwork for future scaling of the solution across the market.
