Session Outline
There is plenty of data out there. In the Nordic financial sector, we are blessed with more data than most, and, in Noitso, we harness this data. However, creating and deploying machine learning models for a production setting is hard. There is also high risk, one mistake in prod will impact your bottom line when dealing out credit. Organizations need MLOps. This encompasses many important things; among others reproducibility, rolling-deployments and online monitoring of data drift and outliers. On top of all this, you also need compliant explanations of what your model is predicting. In the real world, this is true for all predictions based on machine learning.
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