Central banks are among the most data-dense public institutions. As they modernize digital payments and financial supervision, artificial intelligence (AI)-enabled analytics and supervisory technology (SupTech) enable them to draw connections across the large datasets they hold. In doing so, these tools expand central banks’ ability to infer information about legal entities and individuals beyond what is directly contained in any single dataset.
Walter Bagehot ([1873], 2000) famously commented in his book Lombard Street on the 
need to adapt a central bank’s governance structure to its changing purpose, writing that “‘putting new wine into old bottles’ is safe only when you watch the condition of the bottle, and adapt its structure most carefully.” This metaphor is particularly useful in understanding new and emerging challenges involved in tailoring the structure of financial policy governance in the post-crisis era.
Netherlands for the World Bank 