Bank of England: How to see it coming: predicting bank distress with machine learning

The great American baseball sage, Yogi Berra, is thought to have once remarked: ‘It’s tough to make predictions, especially about the future’. That is certainly true, but thankfully the accelerating development and deployment of machine learning methodologies in recent years is making prediction easier and easier. That is good news for many sectors and activities, including microprudential regulation. In this post, we show how machine learning can be applied to help regulators. In particular, we outline our recent research that develops an early warning system of bank distress, demonstrating the improved performance of machine learning techniques relative to traditional approaches.

Read more of this post

Related Posts

Previous Post
Get the weekly SFM update – our February 28 newsletter is online
Next Post
Have we hit a tipping point of buy-side firms taking responsibility for their own collateral? (Premium)

Fill out this field
Fill out this field
Please enter a valid email address.

X

Reset password

Create an account