Next steps

We have analyzed our dataset, performed necessary feature engineering and statistical tests, built visualizations, and gained substantial domain knowledge about credit risk analysis and what kind of features are considered by banks when they analyze customers. The reason why we analyzed each feature in the dataset in detail was to give you an idea about each feature that is considered by banks when analyzing credit rating for customers. This was to give you good domain knowledge understanding and also to help you get familiar with the techniques of performing an exploratory and descriptive analysis of any dataset in the future. So, what next? Now comes the really interesting part of using this dataset; building feature sets from this data and feeding them into predictive models to predict which customers can be potential credit risks and which of them are not. As mentioned previously, there are two steps to this: data and algorithms. In fact, we will go a step further and say...