With the rapid growth of artificial intelligence in the financial sector, banks are looking towards machine learning to stay regulatory compliant.

In a recent article at Risk.net the author discuss the adoption of machine learning based models when validating models and calculation engines. A particularly useful case has been found to be when validating internal models built for regulatory stress tests. At the same time, regulators express scepticism towards this development as they argue that the methods lack transparency and might obscure the true nature of banks’ vulnerabilities.

For more information, the full article can be found here.