If the company sells goods or provides services with obligations, it is profitable and reasonable to deal only with reliable clients with lowest unpaid risk. The way to predict reliable clients and decrease potential risk of debt is to score the clients.
Implementation of scoring model, which helped identify reliable clients and significantly decrease unpaid ratio in the company.
The output of the model was a probability of being a debtor in a shortcoming perspective. Mathematical model was developed using Python.
Identify reliable clients and probability of client’s default
PL/SQL, MS SQL Server, Python, Microstrategy
DB Developer, 2 Data Analysts, Project Manager.
2 months for complete implemented model