In this section, we will be answering a few questions asked by a consumer bank's marketers. Then, we will look at another important model development technique—ensemble learning—which will be useful in combining predictions from different models.
Sources of wealth: asset, income, and gifted
One of the most common tasks in retail banking customer analytics is to retrieve additional data that helps us to explain the customers' investment behavior and patterns. No doubt we will know the response of the customers, but the work of a model is to find out why they respond as they do. Surprisingly, there is a lot of aggregated information concerning the behaviors of individuals, such as census data. We can also find data from social media, where users use social media for authentication. The relevant social media information can then be chained together with individual-level transactional data that we observed...