# name
Detecció de frau en targetes de crèdit/dèbit

# metadata.dc.description[].value
Treballs Finals de Grau en Estadística UB-UPC, Facultat d'Economia i Empresa (UB) i Facultat de Matemàtiques i Estadística (UPC), Curs: 2022-2023, Tutor:  Hector Rufino Alcalde

# metadata.dc.description.abstract[].value
The importance of fraud detection has increased over the last years, which is why
companies, especially banks, are looking for a solution in this regard. This final degree
project focuses on the detection of anomalies in banking transactions with the aim of
preventing fraud. A methodology based on Machine learning has been applied using data
from a real bank. An unsupervised model based on the Isolation Forest algorithm has been
developed to identify anomalous patterns in the transaction logs. The project also includes
the implementation of the model in the bank, contributing to the improvement of fraud
prevention strategies in the bank.

# metadata.dc.source[].value
Treballs Finals de Grau (TFG) - Estadística UB-UPC

# metadata.dc.title[].value
Detecció de frau en targetes de crèdit/dèbit