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Title: Arquitectura aplicada a un modelo predictivo de detección de fraude en las reclamaciones del sector seguros
Author: Russo, Marco
Tutor: Luque Ocaña, Rafael
Others: Curto Díaz, José  
Abstract: This final work shows a viable data architecture solution to address the fraud detection use case of the insurance sector, in the same way to see how to analyse the features for the creation of a fraud prediction model. We will proceed with the design of the architecture, analyse the data pipeline in two temporal moments, batch mode and streaming mode, and finally, shows the results. As complement of that, it will be the comparison between different data treatment processes, study the different ways to consider the start-up phase and to detect possible risks. The aim of the work is to be able to combine data architecture, opting for a hybrid method between Lambda and Kappa architecture, in addition using microservices technology based on Docker and machine learning monitoring by MLOps methods and GitHub workflow.
Keywords: streaming
Kappa architecture
fraud detection
Document type: info:eu-repo/semantics/masterThesis
Issue Date: Jun-2021
Publication license:  
Appears in Collections:Trabajos finales de carrera, trabajos de investigación, etc.

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