Towards a financial fraud ontology: A legal modelling approach [Book Review]
Artificial Intelligence and Law 12 (4):419-446 (2004)
Abstract
This document discusses the status of research on detection and prevention of financial fraud undertaken as part of the IST European Commission funded FF POIROT (Financial Fraud Prevention Oriented Information Resources Using Ontology Technology) project. A first task has been the specification of the user requirements that define the functionality of the financial fraud ontology to be designed by the FF POIROT partners. It is claimed here that modeling fraudulent activity involves a mixture of law and facts as well as inferences about facts present, facts presumed or facts missing. The purpose of this paper is to explain this abstract model and to specify the set of user requirements.Author's Profile
DOI
10.1007/s10506-005-4163-0
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Citations of this work
Legal concepts as inferential nodes and ontological categories.Giovanni Sartor - 2009 - Artificial Intelligence and Law 17 (3):217-251.
Detecting tax evasion: a co-evolutionary approach.Erik Hemberg, Jacob Rosen, Geoff Warner, Sanith Wijesinghe & Una-May O’Reilly - 2016 - Artificial Intelligence and Law 24 (2):149-182.
References found in this work
The Evidential Foundations of Probabilistic Reasoning.David A. Schum - 1994 - New York, NY, USA: Wiley-Interscience.
Form follows function fails - as a sociological foundation of comparative law.Burkhard Schafer - 1999 - Social Epistemology 13 (2):113 – 128.
