Riani, Marco, Corbellini, Aldo and Atkinson, Anthony C. (2018) The use of prior information in very robust regression for fraud detection. International Statistical Review, 86 (2). pp. 205-218. ISSN 0306-7734
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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.
| Item Type: | Article |
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| Official URL: | https://onlinelibrary.wiley.com/journal/17515823 |
| Additional Information: | © 2018 The Authors, International Statistical Institute |
| Divisions: | Statistics |
| Subjects: | H Social Sciences > HA Statistics H Social Sciences > HG Finance H Social Sciences > HV Social pathology. Social and public welfare. Criminology |
| Date Deposited: | 27 Apr 2018 15:04 |
| Last Modified: | 11 Dec 2024 21:37 |
| Projects: | IC1408 |
| Funders: | European Anti‐Fraud Office, CRoNoS |
| URI: | http://eprints.lse.ac.uk/id/eprint/87685 |
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