0000000000617994
AUTHOR
Pietro Vassallo
Covariance and correlation estimators in bipartite complex systems with a double heterogeneity
Complex bipartite systems are studied in Biology, Physics, Economics, and Social Sciences, and they can suitably be described as bipartite networks. The heterogeneity of elements in those systems makes it very difficult to perform a statistical analysis of similarity starting from empirical data. Though binary Pearson's correlation coefficient has proved effective to investigate the similarity structure of some real-world bipartite networks, here we show that both the usual sample covariance and correlation coefficient are affected by a bias, which is due to the aforementioned heterogeneity. Such a bias affects real bipartite systems, and, for example, we report its effects on empirical dat…
Development of multivariate and network models for the analysis of Big Data: applications in economics, insurance, and social sciences
In questa tesi sviluppo metodi statistici multivariati e di rete per lo studio di sistemi complessi. In particolare, focalizzo la mia analisi sullo studio di reti complesse bipartite e le loro applicazioni a (i) l'economia, per capire l'effetto di contagio tra istituti finanziari e stati sovrani, (ii) la sorveglianza nelle assicurazioni, per individuare comportamenti fraudolenti, e (iii) le scienze sociali, per studiare l'effetto delle politiche del REF sulle eccellenze nella ricerca delle università in UK. In this thesis I develop multivariate statistical and network methods for the study of complex systems. In particular, I focus my analysis on the study of bipartite complex networks and …
Insurance fraud detection: A statistically validated network approach
Fraud is a social phenomenon, and fraudsters often collaborate with other fraudsters, taking on different roles. The challenge for insurance companies is to implement claim assessment and improve fraud detection accuracy. We developed an investigative system based on bipartite networks, highlighting the relationships between subjects and accidents or vehicles and accidents. We formalize filtering rules through probability models and test specific methods to assess the existence of communities in extensive networks and propose new alert metrics for suspicious structures. We apply the methodology to a real database-the Italian Antifraud Integrated Archive-and compare the results to out-of-sam…