Detecting tax evasion: a co-evolutionary approach

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@Article{Hemberg:2016:AIL,

• author = "Erik Hemberg and Jacob B. Rosen and Geoff Warner and Sanith Wijesinghe and Una-May O'Reilly",
• title = "Detecting tax evasion: a co-evolutionary approach",
• journal = "Artificial Intelligence and Law",
• year = "2016",
• volume = "24",
• number = "2",
• pages = "149--182",
• month = jun,
• keywords = "genetic algorithms, genetic programming, Grammatical evolution, Tax evasion, Co-evolution, Auditing policy, Partnership tax",
• timestamp = "Thu, 18 May 2017 09:54:58 +0200",
• biburl = "https://dblp.org/rec/journals/ail/HembergRWWO16.bib",
• ISSN = "0924-8463",
• URL = "https://core.ac.uk/download/pdf/78071385.pdf",
• DOI = "doi:10.1007/s10506-016-9181-6",
• size = "34 pages",
• abstract = "We present an algorithm that can anticipate tax evasion by modelling the co-evolution of tax schemes with auditing policies. Malicious tax non-compliance, or evasion, accounts for billions of lost revenue each year. Unfortunately when tax administrators change the tax laws or auditing procedures to eliminate known fraudulent schemes another potentially more profitable scheme takes it place. Modeling both the tax schemes and auditing policies within a single framework can therefore provide major advantages. In particular we can explore the likely forms of tax schemes in response to changes in audit policies. This can serve as an early warning system to help focus enforcement efforts. In addition, the audit policies can be fine tuned to help improve tax scheme detection. We demonstrate our approach using the iBOB tax scheme and show it can capture the co-evolution between tax evasion and audit policy. Our experiments shows the expected oscillatory behaviour of a biological co-evolving system.",
• notes = "also known as \cite{DBLP:journals/ail/HembergRWWO16}",

}

Genetic Programming entries for Erik Hemberg Jacob B Rosen Geoff Warner Sanith Wijesinghe Una-May O'Reilly

Citations