Big Data is here to stay, and it’s only going to get bigger. Organisations are investing in tools and resources that can harness the power of that data, but not everyone knows how to capitalise on it. It’s a difficult and expensive job, even for the highly trained data scientist, of whom there are few.
Though some banks have begun to explore their options with respect to large-scale adoption of Google Cloud AutoML solutions, others have been reluctant due to concerns that security and code dependencies remain. In this report, we discuss these concerns in relation to current solutions and highlight key considerations and takeaway messages for financial institutions.