Connect the Data Dots for Financial Stability
“An indiscriminate adoption of Big Data runs the risk of collecting – without connecting – too many dots,” argue Luiz Awazu Pereira da Silva, Deputy General Manager of the Bank for International Settlements (BIS), and Goetz von Peter, Principal Economist at the BIS.
Their remarks, based on a speech delivered at the Ninth European Central Bank Statistics Conference, highlight the need to embrace Big Data to maintain financial stability in an era of fast financial innovation. However, they also caution that the value of data relies heavily on our ability to analyse it.
New data sources offer potential as an early warning system in case of financial strain. Both a breadth of data, to indicate fault lines that transcend borders, and a depth of granular data, to monitor the complex interconnections that made the Lehman Brother’s collapse so disastrous, are needed.
While machine learning and AI analytics can help manage vast, complex data volumes, it is also essential that the data be in machine-readable structured form. Digital, searchable, and comparable data will allow AI to make the most of the vast quantities of information being reported and enable businesses and regulators to harness the potential of Big Data.
At Data Amplified 2018 we saw exciting new developments in the field of data consumption. A new open API for reportingpromises to greatly simplify data analysis, making comparison simple, and the conference also saw the demonstration of a natural language query tool offering the potential to interrogate XBRL databases through speech alone. With these tools making data analytics far easier and more accessible, the potential to connect the dots in Big Data exists, as long as that data is machine-readable and well defined.
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