The SupTech Blueprint: DataStack Architecture for Consumer and Investor Protection

Financial consumer and investor protection authorities have digitized faster than they have integrated. Complaint portals, disclosure-ingestion tools, and rule-based screening proliferate, yet most authorities plateau at foundation functions and don't reach sustained, production-grade. AI-powered supervisory intelligence. The binding constraint is rarely the absence of technology; it is architectural incoherence across the end-to-end supervisory pipeline.

This Manual is a build guide for closing that gap. It translates consumer and investor protection supervision (CIPS) mandates into a concrete DataStack design method — what to build, at which layer, and in what sequence — structured across five sequential layers (collection, validation and processing, storage, analytics, and data products) and two cross-cutting dimensions (access and interoperability, governance and explainability). Rather than scoring maturity as a single index, it assesses readiness dimension-by-dimension, identifies the binding constraints, and converts them into buildable specifications: data dictionaries, workflow definitions, interoperability patterns, and implementation sequencing.

The method is grounded in an empirical corpus of 102 deployed and prototyped supervisory solutions across consumer-facing authorities (e.g., CFPB, BSP, OJK, Banco de Portugal) and investor-facing securities and conduct authorities (e.g., CONSOB, ASIC, AMF Canada, U.S. SEC), with layer-by-layer reference architectures, workbook templates, and a four-phase implementation sequence calibrated to documented cost and time benchmarks.

It is the companion to SupTech-powered Consumer and Investor Protection Supervision: Architectural Pathway from Reactive Oversight to Outcome-Driven Institutional Intelligence: the Report establishes why authorities plateau and what works; the Manual specifies how to design the foundation-to-intelligence transition into a resilient, AI-ready architecture.