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A quality control method for fraud detection on utility customers without an active contract

Author
Coma, B.; Carmona, J.
Type of activity
Presentation of work at congresses
Name of edition
33th ACM Symposium On Applied Computing
Date of publication
2018
Presentation's date
2018-04-09
Book of congress proceedings
The 33rd Annual ACM Symposium on Applied Computing: Pau, France: April 9-13, 2018
First page
495
Last page
498
Publisher
Association for Computing Machinery (ACM)
DOI
https://doi.org/10.1145/3167132.3167384 Open in new window
Repository
http://hdl.handle.net/2117/123717 Open in new window
URL
https://dl.acm.org/citation.cfm?id=3167384&dl=ACM&coll=DL Open in new window
Abstract
Fraud detection in energy consumption has proven to be a difficult problem for current techniques. In general, the approaches used in this area are restricted to compute a fraud score for each client based on its behaviour. The problem gets much more complicated on customers with no contract, since the company does not have enough information from them to compute an accurate profile. On this paper, we introduce a semi-autonomous method that combines different machine learning algorithms and huma...
Citation
Coma-Puig, B., Carmona, J. A quality control method for fraud detection on utility customers without an active contract. A: ACM Symposium on Applied Computing. "The 33rd Annual ACM Symposium on Applied Computing: Pau, France: April 9-13, 2018". New York: Association for Computing Machinery (ACM), 2018, p. 495-498.
Keywords
Crime, Energy utilization, Fraud detection, Human knowledge, Learning algorithms, Learning systems, Quality control method, Utility company
Group of research
ALBCOM - Algorithms, Computational Biology, Complexity and Formal Methods

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