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Interpretable Fuzzy Rule-Based Systems for Detecting Financial Statement Fraud

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216275%3A25410%2F19%3A39914916" target="_blank" >RIV/00216275:25410/19:39914916 - isvavai.cz</a>

  • Result on the web

    <a href="https://link.springer.com/chapter/10.1007/978-3-030-19823-7_36" target="_blank" >https://link.springer.com/chapter/10.1007/978-3-030-19823-7_36</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1007/978-3-030-19823-7_36" target="_blank" >10.1007/978-3-030-19823-7_36</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Interpretable Fuzzy Rule-Based Systems for Detecting Financial Statement Fraud

  • Original language description

    Systems for detecting financial statement frauds have attracted considerable interest in computational intelligence research. Diverse classification methods have been employed to perform automatic detection of fraudulent companies. However, previous research has aimed to develop highly accurate detection systems, while neglecting the interpretability of those systems. Here we propose a novel fuzzy rule-based detection system that integrates a feature selection component and rule extraction to achieve a highly interpretable system in terms of rule complexity and granularity. Specifically, we use a genetic feature selection to remove irrelevant attributes and then we perform a comparative analysis of state-of-the-art fuzzy rule-based systems, including FURIA and evolutionary fuzzy rule-based systems. Here, we show that using such systems leads not only to competitive accuracy but also to desirable interpretability. This finding has important implications for auditors and other users of the detection systems of financial statement fraud.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Result continuities

  • Project

    <a href="/en/project/GA19-15498S" target="_blank" >GA19-15498S: Modelling emotions in verbal and nonverbal managerial communication to predict corporate financial risk</a><br>

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Others

  • Publication year

    2019

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    IFIP Advances in Information and Communication Technology. Vol. 559

  • ISBN

    978-3-030-19822-0

  • ISSN

    1868-4238

  • e-ISSN

  • Number of pages

    12

  • Pages from-to

    425-436

  • Publisher name

    Springer

  • Place of publication

    Berlin

  • Event location

    Hersonissos

  • Event date

    May 24, 2019

  • Type of event by nationality

    EUR - Evropská akce

  • UT code for WoS article