Shen, YufeiSantini, Andrea2024-10-242024-10-242024-02-012023-12-18http://hdl.handle.net/10362/173974The use of Machine Learning algorithms to identify insurance fraud, a major financial burden on the sector, is examined in this thesis. Working together with Grupo Crédito Agrícola Vida, we made use of a large dataset for forecasting. The study evaluates the effectiveness of sequential neural networks, random forests, and logistic regression in spotting fraud in insurance claims. It addresses the necessity for ethical considerations in automated decision-making and highlights the synergy between human expertise and machine learning. The study emphasizes how Machine Learning may improve operational effectiveness and fraud detection accuracy, which can strengthen the insurance industry's credibility and integrity.engMachine learningFraudDataData analysisData processingArtificial intelligenceBusiness analyticsmaster thesis203605322