Misinvoicing is a major tool in fraud including money laundering. We develop a method of detecting the patterns of outliers that indicate systematic mis-pricing. As the data only become available year by year, we develop a combination of very robust regression and the use of 'cleaned' prior information from earlier years, which leads to early and sharp indication of potentially fraudulent activity that can be passed to legal agencies to institute prosecution. As an example, we use yearly imports of a specific seafood into the European Union. This is only one of over one million annual data sets, each of which can currently potentially contain 336 observations. We provide a solution to the resulting big data problem, which requires analysis with the minimum of human intervention.

The Use of Prior Information in Very Robust Regression for Fraud Detection / Riani, Marco; Corbellini, Aldo; Atkinson, Anthony C.. - In: INTERNATIONAL STATISTICAL REVIEW. - ISSN 0306-7734. - (2018), pp. 1-14. [10.1111/insr.12247]

The Use of Prior Information in Very Robust Regression for Fraud Detection

Riani, Marco;Corbellini, Aldo;Atkinson, Anthony C.
2018-01-01

Abstract

Misinvoicing is a major tool in fraud including money laundering. We develop a method of detecting the patterns of outliers that indicate systematic mis-pricing. As the data only become available year by year, we develop a combination of very robust regression and the use of 'cleaned' prior information from earlier years, which leads to early and sharp indication of potentially fraudulent activity that can be passed to legal agencies to institute prosecution. As an example, we use yearly imports of a specific seafood into the European Union. This is only one of over one million annual data sets, each of which can currently potentially contain 336 observations. We provide a solution to the resulting big data problem, which requires analysis with the minimum of human intervention.
2018
The Use of Prior Information in Very Robust Regression for Fraud Detection / Riani, Marco; Corbellini, Aldo; Atkinson, Anthony C.. - In: INTERNATIONAL STATISTICAL REVIEW. - ISSN 0306-7734. - (2018), pp. 1-14. [10.1111/insr.12247]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11381/2841340
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