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Fintech projects related to the 'Fintech' course conducted by Daniele Marazzina at Politecnico di Milano.

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data-science machine-learning supervised-learning unsupervised-learning fintech

fintech-projects's Introduction

This repository contains three projects related to Fintech course in Politecnico di Milano. Financial technology (Fintech) is the introduction of new technologies and innovations in the traditional financial methods and services. Within the financial services industry, some of the used technologies include machine learning. The aim of the course is to show use cases where these techniques are applied to specific financial problems, overcoming traditional methods.

Brief description of the projects:

  1. Clients segmentation: the goal of the first business case is to segment $5000$ clients of a bank in order to be able to assign different products to each marketing persona.
  2. Needs-based recommendation system: the goal of the second business case is to build a recommendation system which predicts whether a new client of a bank is inclined to income investments or accumulation investments and assign different products to each client based on the prediction.
  3. Anomaly detection: the goal of the third business case is to develop an anomaly detection algorithm which is able to recognize market crisis periods and to build a virtual portfolio exploiting the market anomaly detection capabilities of the model.

The projects were developed as python notebooks and are supposed to be run in a local python notebook IDE.

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