Interesting. I can see how this could be very useful in chemical manufacturing, where I used to work. I used PCA many times on chemical data to detect changes, but not with the Change Detection part of the analysis. We used Shewhart charts on the PCA scores to detect changes.
Now I work in the world of banking, we have similar multivariate streams of data, which of course change over time. Yet the default methodology to detect changes is a univariate, single-time point analysis (actually comparing current time point to some baseline time point) called a Population Stability Index. So, the multivariate nature of the data is not used, and the time series nature of the data is also ignored (so if the data is trending in a certain direction, no signal is found until it hits a threshold, doesn't matter if it is trending in that direction for 12 consecutive time periods, there is no signal from this tool).
Seems like this PCA and Change Detection fits perfectly in the banking case and would give a much more powerful analysis tool. The problem would be to overcome strong reluctance to use a new methodology in place of — or along side of — a well known industry standard. An additional concern might be that auditors and regulators may not want to see new methodology being used for these decisions, I don't know. If I ever get a chance to use PCA and Change Detection on banking data, I will give it a try.
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