Abstract
Legal persons (i.e., entities such as corporations, companies, partnerships, firms, associations, and foundations) may commit financial crimes or employ fraudulent activities like money laundering, tax fraud, or bankruptcy fraud. Therefore, in the Netherlands legal persons are automatically screened for misuse based on a set of so called risk indicators. These indicators, which are based on the data obtained from, among others, the Netherlands Chamber of Commerce, the Dutch police, and the Dutch tax authority, encompass information about certain suspicious behaviours and past insolvencies or convictions (criminal records). In order to determine whether there is an increased risk of fraud, we have devised a number of scoring functions to give a legal person a score on each risk indicator based on the registered information about the legal person and its representatives. These individual scores are subsequently combined and weighed into a total risk score that indicates whether a legal person is likely to commit fraud based on all risk indicators. This contribution reports on our two ranking approaches: one based on the empirical probabilities of the indicators and the other based on the information entropy rate of the empirical probabilities.
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van den Braak, S., Bargh, M.S., Choenni, S. (2014). Fraud Indicators Applied to Legal Entities: An Empirical Ranking Approach. In: Decker, H., Lhotská, L., Link, S., Spies, M., Wagner, R.R. (eds) Database and Expert Systems Applications. DEXA 2014. Lecture Notes in Computer Science, vol 8645. Springer, Cham. https://doi.org/10.1007/978-3-319-10085-2_9
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DOI: https://doi.org/10.1007/978-3-319-10085-2_9
Publisher Name: Springer, Cham
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