Table of Contents
The trend tracker is used to identify outlier behaviour that appears within each individual time series. All time series across all time periods are compared to their historical movements to identify anything out of the ordinary. This both alerts MIAC to any issues within the model outputs for any given month and therefore serves as a useful MI tool for model validation and governance and provides an automated way to identify genuine trends that exist within the data.
Here we detail some of the highlights of the MI analysis that are performed on a monthly basis, their rationale along with possible actions clients could perform to mitigate any flagged weaknesses.