The traditional credit scoring approach is based on the borrower’s credit scorecard, that is, their past credit history. It also considers the client’s socio-demographics, including their age, gender, occupation, marital status, and the number of family members. However, this method has limitations as it prevents access to the lending market for new clients without a credit history. Second, it doesn’t take into account the revenue prospects of young borrowers based on their education, investment activity, etc. These characteristics are included only in more innovative, ML-based credit scoring algorithms.