Materiality Maps: Process Mining Data Visualization for Financial Audits

Publikation: Bidrag til bog/antologi/rapportKonferencebidrag i proceedingsForskningpeer review

Resumé

Financial audits are a safeguard to prevent the distribution of false information which could detrimentally influence stakeholder decisions. The increasing integration of computer technology for the processing of business transactions create new challenges for auditors who have to deal with increasingly large and complex data. Process mining can be used as a novel Big Data analysis technique to support auditors in this context. A challenge for using this type of technique is the representation of analyzed data. Process mining algorithms usually discover large sets of mined process variants. This study introduces a new approach to visualize process mining results specifically for financial audits in an aggregate manner as materiality maps. Such maps provide an overview about the processes identified in an organization and indicate which business processes should be considered for audit purposes. They reduce an auditor’s information overload and help to improve decision making in the audit process.
OriginalsprogEngelsk
TitelProceedings of the 52nd Hawaii International Conference on System Sciences
Antal sider10
Udgivelses stedHonolulu
ForlagHawaii International Conference on System Sciences (HICSS)
Publikationsdato2019
Sider1045-1054
ISBN (Trykt)9780998133126
DOI
StatusUdgivet - 2019
BegivenhedThe 52nd Hawaii International Conference on System Sciences. HICSS 2019 - Wailea, USA
Varighed: 8 jan. 201911 jan. 2019
Konferencens nummer: 52
https://scholarspace.manoa.hawaii.edu/handle/10125/59440

Konference

KonferenceThe 52nd Hawaii International Conference on System Sciences. HICSS 2019
Nummer52
LandUSA
ByWailea
Periode08/01/201911/01/2019
Internetadresse
NavnProceedings of the Annual Hawaii International Conference on System Sciences
ISSN1060-3425

Emneord

  • Data visualization
  • Data analytics
  • Financial statement audit
  • Materiality
  • Process mining

Citer dette

Werner, M. (2019). Materiality Maps: Process Mining Data Visualization for Financial Audits. I Proceedings of the 52nd Hawaii International Conference on System Sciences (s. 1045-1054). Honolulu: Hawaii International Conference on System Sciences (HICSS). Proceedings of the Annual Hawaii International Conference on System Sciences https://doi.org/10125/59544
Werner, Michael . / Materiality Maps : Process Mining Data Visualization for Financial Audits. Proceedings of the 52nd Hawaii International Conference on System Sciences. Honolulu : Hawaii International Conference on System Sciences (HICSS), 2019. s. 1045-1054 (Proceedings of the Annual Hawaii International Conference on System Sciences).
@inproceedings{0aad3e4e3f994c379ce9945ebba3b10f,
title = "Materiality Maps: Process Mining Data Visualization for Financial Audits",
abstract = "Financial audits are a safeguard to prevent the distribution of false information which could detrimentally influence stakeholder decisions. The increasing integration of computer technology for the processing of business transactions create new challenges for auditors who have to deal with increasingly large and complex data. Process mining can be used as a novel Big Data analysis technique to support auditors in this context. A challenge for using this type of technique is the representation of analyzed data. Process mining algorithms usually discover large sets of mined process variants. This study introduces a new approach to visualize process mining results specifically for financial audits in an aggregate manner as materiality maps. Such maps provide an overview about the processes identified in an organization and indicate which business processes should be considered for audit purposes. They reduce an auditor’s information overload and help to improve decision making in the audit process.",
keywords = "Data visualization, Data analytics, Financial statement audit, Materiality, Process mining, Data visualization, Data analytics, Financial statement audit, Materiality, Process mining",
author = "Michael Werner",
year = "2019",
doi = "10125/59544",
language = "English",
isbn = "9780998133126",
series = "Proceedings of the Annual Hawaii International Conference on System Sciences",
publisher = "Hawaii International Conference on System Sciences (HICSS)",
pages = "1045--1054",
booktitle = "Proceedings of the 52nd Hawaii International Conference on System Sciences",
address = "United States",

}

Werner, M 2019, Materiality Maps: Process Mining Data Visualization for Financial Audits. i Proceedings of the 52nd Hawaii International Conference on System Sciences. Hawaii International Conference on System Sciences (HICSS), Honolulu, Proceedings of the Annual Hawaii International Conference on System Sciences, s. 1045-1054, The 52nd Hawaii International Conference on System Sciences. HICSS 2019, Wailea, USA, 08/01/2019. https://doi.org/10125/59544

Materiality Maps : Process Mining Data Visualization for Financial Audits. / Werner, Michael .

Proceedings of the 52nd Hawaii International Conference on System Sciences. Honolulu : Hawaii International Conference on System Sciences (HICSS), 2019. s. 1045-1054 (Proceedings of the Annual Hawaii International Conference on System Sciences).

Publikation: Bidrag til bog/antologi/rapportKonferencebidrag i proceedingsForskningpeer review

TY - GEN

T1 - Materiality Maps

T2 - Process Mining Data Visualization for Financial Audits

AU - Werner, Michael

PY - 2019

Y1 - 2019

N2 - Financial audits are a safeguard to prevent the distribution of false information which could detrimentally influence stakeholder decisions. The increasing integration of computer technology for the processing of business transactions create new challenges for auditors who have to deal with increasingly large and complex data. Process mining can be used as a novel Big Data analysis technique to support auditors in this context. A challenge for using this type of technique is the representation of analyzed data. Process mining algorithms usually discover large sets of mined process variants. This study introduces a new approach to visualize process mining results specifically for financial audits in an aggregate manner as materiality maps. Such maps provide an overview about the processes identified in an organization and indicate which business processes should be considered for audit purposes. They reduce an auditor’s information overload and help to improve decision making in the audit process.

AB - Financial audits are a safeguard to prevent the distribution of false information which could detrimentally influence stakeholder decisions. The increasing integration of computer technology for the processing of business transactions create new challenges for auditors who have to deal with increasingly large and complex data. Process mining can be used as a novel Big Data analysis technique to support auditors in this context. A challenge for using this type of technique is the representation of analyzed data. Process mining algorithms usually discover large sets of mined process variants. This study introduces a new approach to visualize process mining results specifically for financial audits in an aggregate manner as materiality maps. Such maps provide an overview about the processes identified in an organization and indicate which business processes should be considered for audit purposes. They reduce an auditor’s information overload and help to improve decision making in the audit process.

KW - Data visualization

KW - Data analytics

KW - Financial statement audit

KW - Materiality

KW - Process mining

KW - Data visualization

KW - Data analytics

KW - Financial statement audit

KW - Materiality

KW - Process mining

U2 - 10125/59544

DO - 10125/59544

M3 - Article in proceedings

SN - 9780998133126

T3 - Proceedings of the Annual Hawaii International Conference on System Sciences

SP - 1045

EP - 1054

BT - Proceedings of the 52nd Hawaii International Conference on System Sciences

PB - Hawaii International Conference on System Sciences (HICSS)

CY - Honolulu

ER -

Werner M. Materiality Maps: Process Mining Data Visualization for Financial Audits. I Proceedings of the 52nd Hawaii International Conference on System Sciences. Honolulu: Hawaii International Conference on System Sciences (HICSS). 2019. s. 1045-1054. (Proceedings of the Annual Hawaii International Conference on System Sciences). https://doi.org/10125/59544