This thesis describes the development of a fraud detection scheme for car insurance customers, based only on information that is available at the moment of underwriting. It explains how we manipulated raw anonymised data and turned it into a graph, and how we used this graph to assign a fraudulence score to each node. Finally, it evaluates the performance of this score in identifying unknown fraudsters. The results obtained in the thesis have been obtained by means of several ad hoc optimised and parallel algorithms, which have been tested and run on multiple HPC platforms.
|Titolo:||Fraud detection and link analysis in Genertel’s customer network|
|Relatore/i esterni:||Consorti, Valerio; Cozzini, Stefano; Della Noce, Gloria|
|Data di pubblicazione:||18-dic-2017|
|Aree SISSA:||Laboratorio Interdisciplinare|
|Appare nelle tipologie:||8.4 Master thesis in High Performance Computing (HPC)|