Big data should help solve problems ‘on the ground’ – Ireland’s Kearns

Central banks need to do more than simply invest in technology and analytics, says Kearns

When it comes to making use of big data to support financial supervision, central banks should think about how it can help solve problems “on the ground”, says the Central Bank of Ireland’s Allan Kearns.

“Our supervisors are inundated with all sorts of information – whether it’s narrative, whether it’s quantitative – and being able to pick out the signal from all the noise in that data is a key challenge,” he says.

Kearns, who is head of prudential analytics in the insurance division, says big data helps support the central bank’s risk-based supervision. There are challenges for supervisors around prioritising risks, and risk may emerge in “real-time” – big data can help identify those, he says, as standard regulatory reports tend to be more backward-looking.

The Central Bank of Ireland has built a six-stage process that ranges from acquiring, cleaning and integrating data, to analytics, passing insights on to supervisors, and working through challenges in delivering “business value”.

“We tend to work backwards, right back to the analysis, to the technology and the data we need,” he says.

There are “real, tangible” opportunities for big data to make a difference, Kearns said in the interview, recorded on the sidelines of Central Banking’s recent Fintech and Regtech summit in London.

But central banks looking to adopt big data need to think not only about investments in analytics and technology, but also changes to culture and processes, he says.

“Don’t underestimate the extent to which you will need to amend your supervisory processes, your approach, even the type of supervisors and the skill sets that they have, in order to fully leverage the insights,” says Kearns.

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