Banks are reporting a sharp rise in cases of internal and external fraud perpetrated during the coronavirus pandemic – and with typical patterns of behaviour among retail and corporate clients turned on their respective heads, detection systems that rely on past patterns of behaviour to make predictions are struggling to cope.

In ordinary times, machine learning technology can dramatically improve fraud detection rates by spotting transactions that look atypical of observed customer behaviour