Fraud Audit Based on Visual Analysis: A Process Mining Approach
Please use this identifier to cite or link to this item:
http://hdl.handle.net/10045/116146
Title: | Fraud Audit Based on Visual Analysis: A Process Mining Approach |
---|---|
Authors: | Rodríguez-Quintero, Jorge-Félix | Sánchez, Alexander | Iriarte Navarro, Leonel | Maté, Alejandro | Marco Such, Manuel | Trujillo, Juan |
Research Group/s: | Lucentia |
Center, Department or Service: | Universidad de Alicante. Departamento de Lenguajes y Sistemas Informáticos |
Keywords: | Fraud audit | Process mining | Visual analytics |
Knowledge Area: | Lenguajes y Sistemas Informáticos |
Issue Date: | 21-May-2021 |
Publisher: | MDPI |
Citation: | Rodríguez-Quintero J-F, Sánchez-Díaz A, Iriarte-Navarro L, Maté A, Marco-Such M, Trujillo J. Fraud Audit Based on Visual Analysis: A Process Mining Approach. Applied Sciences. 2021; 11(11):4751. https://doi.org/10.3390/app11114751 |
Abstract: | Among the knowledge areas in which process mining has had an impact, the audit domain is particularly striking. Traditionally, audits seek evidence in a data sample that allows making inferences about a population. Mistakes are usually committed when generalizing the results and anomalies; therefore, they appear in unprocessed sets; however, there are some efforts to address these limitations using process-mining-based approaches for fraud detection. To the best of our knowledge, no fraud audit method exists that combines process mining techniques and visual analytics to identify relevant patterns. This paper presents a fraud audit approach based on the combination of process mining techniques and visual analytics. The main advantages are: (i) a method is included that guides the use of the visual capabilities of process mining to detect fraud data patterns during an audit; (ii) the approach can be generalized to any business domain; (iii) well-known process mining techniques are used (dotted chart, trace alignment, fuzzy miner…). The techniques were selected by a group of experts and were extended to enable filtering for contextual analysis, to handle levels of process abstraction, and to facilitate implementation in the area of fraud audits. Based on the proposed approach, we developed a software solution that is currently being used in the financial sector as well as in the telecommunications and hospitality sectors. Finally, for demonstration purposes, we present a real hotel management use case in which we detected suspected fraud behaviors, thus validating the effectiveness of the approach. |
Sponsor: | This work has been co-funded by the ECLIPSE-UA (RTI2018-094283-B-C32) project funded by the Spanish Ministry of Science, Innovation. |
URI: | http://hdl.handle.net/10045/116146 |
ISSN: | 2076-3417 |
DOI: | 10.3390/app11114751 |
Language: | eng |
Type: | info:eu-repo/semantics/article |
Rights: | © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
Peer Review: | si |
Publisher version: | https://doi.org/10.3390/app11114751 |
Appears in Collections: | INV - LUCENTIA - Artículos de Revistas |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
![]() | 6,3 MB | Adobe PDF | Open Preview | |
This item is licensed under a Creative Commons License