A financial company wants to develop a scoring model to predict the probability of credit non-payment. This will support the reasoning of accepting or refusing a loan to a potential client, by relying on various data sources (behavioural data, data from other financial institutions...).
In addition, CRMs have reported that clients are increasingly demanding transparency. The company therefore decided to develop an interactive dashboard so that CRMs could explain credit decisions as transparently as possible, but also allow their customers to have access to their personal information and explore it easily.
- An interactive dashboard.
- A folder in github including modelling, dashboard and the deployment source files.
- A methodology note including the learning method, evaluation metrics, cost function, interpretability and limits.
- A support to present the work done and the interactif dashboard.