Data exploration and preparation to execute both ML and QML models
As mentioned before, in this chapter, we will walk you through the implementation of hybrid quantum-classical algorithms and how they behave in a real-world scenario in finance, but before you start playing with them in a professional setup, you should think – or at least review – some the following concepts.
Data enrichment refers to the process of enriching or supplementing an existing dataset with extra information. Data enrichment in the context of credit scoring systems is the use of additional data sources to supplement extra variables and features that could come from a credit bureau or a non-traditional source (e.g., mobile data mining) in order to increase the accuracy of credit risk assessments.
By incorporating additional data sources like public records (digital footprints), social media behavior, financial history, open finance, and other alternative data sources, data enrichment can...
