Collaboration is key to central banks making the most of data

As data becomes increasingly significant for central banks, working with the right people and employing the right approaches is central to meeting objectives, says Maciej Piechocki of BearingPoint.

The financial crisis exposed central banks’ and regulators’ need for high‑quality, comparable and timely data on the financial system. Since then, central bankers, policymakers, supervisory authorities and standard-setters have been collaborating to harmonise and standardise regulatory reporting for banks and insurance companies. There are ongoing debates about how the financial services industry could be better and less onerously supervised through a smarter approach, how central banks are dealing with data – big data in particular – and how they are becoming data-driven enterprises. 

In view of these developments, it is mission-critical for central banks to reshape their data management and automate processes, as well as find innovative approaches to deal with data and big data. Automation helps minimise risk, reduce errors, increase transparency and deliver a better basis for decision-making, and regulatory and risk technology – regulatory technology (regtech) and supervisory technology (suptech) – support central banks with this.

The Basel Committee on Banking Supervision (BCBS) recently issued a consultation paper examining the benefits of regtech for the financial industry, as well as for regulators and – in particular – banking supervisors. According to the paper, the effective development and application of regtech offers an opportunity to automate regulatory reporting and compliance requirements, and facilitate cross-sectoral and cross-jurisdictional co-operation for improved compliance – regtech can enable effective risk-data aggregation and risk management. Quoted in BCBS 415, BearingPoint – with its Abacus platform as a representative example of such regtech/suptech – signifies developments in this area. In bringing its regtech/risktech to the market, BearingPoint facilitates the conception and realisation of innovative approaches to regulatory reporting, such as shared utilities, integrated platforms for data management and analytics, and Regulatory-as-a-Service. Although unique in its conception, the Austrian approach could be the future of regulatory reporting.

The Global Partnership for Financial Inclusion also referred to the AuRep project in its report, Digital financial inclusion: Emerging policy approaches, which gives directions for regulatory reporting and supervision on a global stage. The authors name AuRep as an example of the “input-based” approach that “leverages new technologies – or regtech – which enable regulators to capture more granular data on financial sector activity, including activity by new market entrants, or related to new digitally enabled delivery mechanisms or products, while reducing the reporting burden on regulated institutions.”

Because of the vast amount of structured and unstructured data from various sources, decision-making is now more difficult than before, and central banks need adequate solutions to analyse this data. A crucial point is how to mine all this information from different sources exhaustively and at reasonable cost. 

The specific challenge for central banks in the sense of an effective 360-degree risk-based supervision is to rapidly access and effectively manage, process and analyse the increasing amounts of supervisory, statistical and markets data and big data in a timely manner. The real-time or near-real-time access and efficient processing are especially regarded as critical factors due to limitations in human and IT resources.

Data and big data are key topics for central banks worldwide. But first, combining data with the right people, technology, processes and collaboration models – such as those in Austria – will allow central banks to leverage it for their missions and objectives.  

This article is part of the Central Banking focus report, Big data in central banks, published in association with BearingPoint.

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