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Rapid developments in cloud computing and data science have significantly reduced the cost and expanded the scope of possible analytics in the practise of financial regulation. However, the existing Organizational Architecture of regulatory interaction is still rooted in old models of data that sit in siloes and is not actively integrated or shared. In this paper, we developed a framework to consider how the technology forces of: faster computing; networked data portals; and growth in organizational models for parallelism might facilitate a new Regulatory Data Architecture.In the development of this conception, it is natural to adopt the emerging idea of a Social Machine, as a metaphor for the large-scale interaction of humans and machines via web connections. This view of a more connected regulatory system is put forward as a possible solution to the problem of increasing the degree to which regulators might be: informed; engaged; and agile within the goal of pragmatic attention to financial stability, without impeding entrepreneurial vigour. The challenges to progress are enumerated in the context of developing a view on the Politics of Data, and the emerging Political Economy of Data, as these relate to the ever present frictions between the natural constituencies of: data contributors; data collectors and data consumers. Finally, we put forward the idea of a Financial Intelligence Data Office (FIDO) as a clearing house to facilitate linkage of existing data portals. This proposal is to facilitate public-private experimentation for the development of new Regulatory Analytics to create greater system-wide visibility for enhanced financial stability.