The responsibility of a central bank is sizable and varied, and they have numerous obligations that are critical to economic prosperity. Executing on all mandates requires a significant amount of research and reporting on market trends, risks and irregularities. At Nasdaq, we are seeing trends emerge in debt and currency markets, which we have seen play out over the years in securities markets, such as the movement of activity into electronic networks and platforms. These changes precipitate even more growth in the velocity and volume of data that central banks must manage. We’ve learned that the best course of action is to get ahead of the challenge, as those that do not will face difficulty catching up.
Keeping up with data collection, capture, normalization and storage is an enormous task. In the best-case scenario, central banks systematically collect structured data electronically through reporting systems and directly from banks, brokers and market data feeds. However, in many instances, data collection is ad hoc, poorly structured, or in a non-electronic form. This approach is not only very labor-intensive and prone to error but hampers the ability to apply modern data analytics against data.
This is only the start of the challenges, as many central banks still use Excel spreadsheets to process all this data and create reports. On top of that, central banks often don’t have a centralized data repository, so they can’t run complex scenario analyses or proactively and efficiently monitor compliance.
Securities markets and regulators, which have been faced with rapid technological change, have accepted the need for a systematic, automated, data-driven process as a core part of their monitoring regime. Ideally, central banks need a solution that can automatically validate and verify the integrity and quality of the data by checking for receipt, completeness, correctness, plausibility and consistency. The solution can normalize transactional, reference and alerting data, as well as combine it with unstructured data such as news or social media. Once gathered, advanced data analytic techniques can be applied rigorously against all of the data, not just against already known bad behavior. In addition, it is extremely important that those working in central banks can decipher and summarize this data.
Data collected in this manner also lends itself significantly better to the latest tools, such as the use of artificial intelligence. That way, crises can be managed more effectively or avoided altogether. Moreover, systematic alerting can detect unusual trade patterns, as well as variations in prices and volumes against trends and in the theoretical yields or prices, which may indicate market manipulation.
Central banks need to ensure their infrastructure is efficient and robust, as these banks play a key role in monetary policy, oversight and regulation, and economic development. Nasdaq Market Surveillance and Supervision for Central Banks, coupled with the experience that Nasdaq brings in critical country-wide financial data management, can help enhance market oversight capabilities and reduce operational costs, benefitting both the central banks and local economies.