A Framework to Assess Risk of Illicit Trades Using Bayesian Belief Networks

Rashid Anzoom; Rakesh Nagi; Chrysafis Vogiatzis

doi:10.1007/978-3-030-85914-5_54

A Framework to Assess Risk of Illicit Trades Using Bayesian Belief Networks

Rashid Anzoom, Rakesh Nagi, Chrysafis Vogiatzis

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

Recent years have seen the initiatives against illicit trades gain significant traction at both national and global levels. A crucial component in this fight is correct assessment of the risks posed by different trades across different regions. To aid in this cause, we provide a risk prediction framework based on Bayesian Belief Networks. It involves the development of a causal model incorporating variables related to the rise/decline of the illicit trade volume. The influence of these variables are determined by training on available data that are allowed to update over time. Implementation on a sample case study shows relatively low prediction accuracy of our model. Factors constraining its performance are analyzed and possible ways to avert them are discussed. We expect this framework to act as a decision support tool to the policymakers and strengthen them in the fight against illicit trades.

Original language	English (US)
Title of host publication	Advances in Production Management Systems. Artificial Intelligence for Sustainable and Resilient Production Systems - IFIP WG 5.7 International Conference, APMS 2021, Proceedings
Editors	Alexandre Dolgui, Alain Bernard, David Lemoine, Gregor von Cieminski, David Romero
Publisher	Springer
Pages	504-513
Number of pages	10
ISBN (Print)	9783030859138
DOIs	https://doi.org/10.1007/978-3-030-85914-5_54
State	Published - 2021
Event	IFIP WG 5.7 International Conference on Advances in Production Management Systems, APMS 2021 - Nantes, France Duration: Sep 5 2021 → Sep 9 2021

Publication series

Name	IFIP Advances in Information and Communication Technology
Volume	634 IFIP
ISSN (Print)	1868-4238
ISSN (Electronic)	1868-422X

Conference

Conference	IFIP WG 5.7 International Conference on Advances in Production Management Systems, APMS 2021
Country/Territory	France
City	Nantes
Period	9/5/21 → 9/9/21

Keywords

Bayesian Belief Networks
Illicit trade
Risk assessment

ASJC Scopus subject areas

Information Systems and Management

Online availability

10.1007/978-3-030-85914-5_54

Library availability

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Anzoom, R., Nagi, R., & Vogiatzis, C. (2021). A Framework to Assess Risk of Illicit Trades Using Bayesian Belief Networks. In A. Dolgui, A. Bernard, D. Lemoine, G. von Cieminski, & D. Romero (Eds.), Advances in Production Management Systems. Artificial Intelligence for Sustainable and Resilient Production Systems - IFIP WG 5.7 International Conference, APMS 2021, Proceedings (pp. 504-513). (IFIP Advances in Information and Communication Technology; Vol. 634 IFIP). Springer. https://doi.org/10.1007/978-3-030-85914-5_54

A Framework to Assess Risk of Illicit Trades Using Bayesian Belief Networks. / Anzoom, Rashid; Nagi, Rakesh ; Vogiatzis, Chrysafis.
Advances in Production Management Systems. Artificial Intelligence for Sustainable and Resilient Production Systems - IFIP WG 5.7 International Conference, APMS 2021, Proceedings. ed. / Alexandre Dolgui; Alain Bernard; David Lemoine; Gregor von Cieminski; David Romero. Springer, 2021. p. 504-513 (IFIP Advances in Information and Communication Technology; Vol. 634 IFIP).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Anzoom, R, Nagi, R & Vogiatzis, C 2021, A Framework to Assess Risk of Illicit Trades Using Bayesian Belief Networks. in A Dolgui, A Bernard, D Lemoine, G von Cieminski & D Romero (eds), Advances in Production Management Systems. Artificial Intelligence for Sustainable and Resilient Production Systems - IFIP WG 5.7 International Conference, APMS 2021, Proceedings. IFIP Advances in Information and Communication Technology, vol. 634 IFIP, Springer, pp. 504-513, IFIP WG 5.7 International Conference on Advances in Production Management Systems, APMS 2021, Nantes, France, 9/5/21. https://doi.org/10.1007/978-3-030-85914-5_54

Anzoom R, Nagi R , Vogiatzis C. A Framework to Assess Risk of Illicit Trades Using Bayesian Belief Networks. In Dolgui A, Bernard A, Lemoine D, von Cieminski G, Romero D, editors, Advances in Production Management Systems. Artificial Intelligence for Sustainable and Resilient Production Systems - IFIP WG 5.7 International Conference, APMS 2021, Proceedings. Springer. 2021. p. 504-513. (IFIP Advances in Information and Communication Technology). doi: 10.1007/978-3-030-85914-5_54

Anzoom, Rashid ; Nagi, Rakesh ; Vogiatzis, Chrysafis. / A Framework to Assess Risk of Illicit Trades Using Bayesian Belief Networks. Advances in Production Management Systems. Artificial Intelligence for Sustainable and Resilient Production Systems - IFIP WG 5.7 International Conference, APMS 2021, Proceedings. editor / Alexandre Dolgui ; Alain Bernard ; David Lemoine ; Gregor von Cieminski ; David Romero. Springer, 2021. pp. 504-513 (IFIP Advances in Information and Communication Technology).

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A Framework to Assess Risk of Illicit Trades Using Bayesian Belief Networks

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