Predictive models development

S2E is developing, with the help of Its partners and Univerity institutes some predictive algorithms based on Learning machine and neural networks.

S2E applies those models to some use cases referring to the banking world and to consumer credit, as well as to other sectors connected to Farma world.

In particular, for a bank customer, S2E has applied some algorithms based on Learning machines and neural networks in order to identify the account holders who will ask for personal credits and the potential ammount requested.



Artificial intelligence applied in Finance area

20.000 cases of funding

70% for training

30% for test

Implemented neural network

Principal advantages of neural network in the case under consideration 

  • On time prediction (instead of a class as in the classical statistics methods)
  • Extreme accuracy



Mistake on the AMMOUNT (differences between real and predicted):


with credit ranging between 1.500,00€ and 75.000,00€ in real data


Mistake on the  DURATION (difference between real and predicted):

60 days

with duration ranging between 30 and 3.600 days in real data

Prevision examples & real data offset