We at the National Bank do not lag either. We use the tools Predictive Analytics and Machine Learning in our early warning system which predicts the likelihood of troubles in banks by using machine learning techniques (Self-Organising Maps and Lasso logistic regression). We thereby monitor bank riskiness from the aspect of likelihood of the occurrence of any difficulties in their operation.
Within the IPS system there is a Fraud Management Module, which ensures a mechanism for detecting fraud. Machine Learning is used to assess the macroeconomic environment when validating scenarios for stress testing of the banking sector, but also as a supporting tool when projecting the reference guide for the countercyclical capital buffer rate.