Study of new solutions for data analysis in the Leasing field through the application of sophisticated Machine Learning algorithms. More specifically, study of insolvencies and identification of cases of contracts at risk.
The solution was the provision of Advanced Analytics on the world of insolvencies: Identification of contractual anomalies at risk of insolvency and fraud risk (on contracts-tenants-suppliers) through Clustering Analysis and Pattern Recognition of Customers and Contracts; Data Visualization with geo-localization of the scoring of the Models.
The benefit of a Machine Learning project is often also in the so-called Data Quality, a fundamental link to collect “correct” and “clean” data.
More generally. the project has made it possible to identify both anomalies of the data during the Data Preparation phase and to plan a set of new Analytics based on Machine Learning Models to be definitively implemented as a service via MLOPS.
Implementation of the Machine Learning Pilot service, from the creation of Machine Learning Models to Advanced Analytics.