When it comes to data, central banks need efficiencies in two core areas: collection and analytics. This should not be an either/or proposition.
Central banks are facing a big data problem. Amid rapid innovation and steadily increasing regulation across the financial landscape, the number of firms and disclosures they must supervise is increasing rapidly and is straining limited resources.
But simply having a solution in place is not a silver bullet. Central banks need modern systems and a plan to bring it all together.
In this article, we explore how – with the appropriate platforms, partners and processes in place – supervisory technology can be utilised as a driver of transformation. We also offer a few key principles and conclude with some best practices.