The BIS Innovation Hub Singapore Centre and the Monetary Authority of Singapore (MAS) today revealed they have developed a new prototype platform that integrates regulatory data and analytics.
The prototype is known as Project Ellipse. The platform helps regulatory authorities identify potential risks to individual banks and the banking system by integrating regulatory and other data, such as articles and news.
According to the official announcement, BIS will launch an Ellipse collaboration community to share, further test, customise and scale this solution across regulatory authorities around the globe.
The Ellipse prototype is going to be published on BIS Open Tech first. This new platform allows sharing of statistical and financial software as public goods, thereby promoting international cooperation and coordination.
Ross Leckow, Acting Head of the BIS Innovation Hub, said:
Regulators need accurate and timely information to assess emerging risks and to make informed supervisory decisions. Project Ellipse has now developed a potential tool for the global regulatory community to further explore and collaborate on common solutions that can improve the data and analytical capabilities of regulatory authorities. It has the potential to be a game – changer by giving supervisors access to more and better data, structured and unstructured, with greater predictive insights than ever before, it can be scaled to provide real time analysis on a national or cross border supervisory basis.
Hern Shin Ho, Deputy Managing Director (Financial Supervision), MAS, added:
Hern Shin Ho
Recent technological advancements have opened up possibilities for supervisors to leverage on more granular, timely and varied datasets to significantly improve supervisory effectiveness. Project Ellipse clearly demonstrates that collection and use of such datasets need not be prohibitive, but can be codified, efficient, cost effective and potentially scalable even on a cross border basis. MAS is adapting the prototype for our own supervisory needs.
The project is supported by the Bank of England, the International Swaps and Derivatives Association, Accenture and Financial Network Analytics. The first phase of its development investigated how machine executable digital reporting could enable data-driven supervision, using a cross-border common data model. And in the second phase, it was examined how advanced analytics like machine learning and natural language processing could be leveraged to unstructured and granular reporting data. This helped with the identification of risk correlations and sentiment analysis and to signal to supervisors in real time about issues that may need further investigation.
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