Materiality Maps – Process Mining Data Visualization for Financial Audits

dc.contributor.authorWerner, Michael
dc.date.accessioned2019-01-02T23:48:28Z
dc.date.available2019-01-02T23:48:28Z
dc.date.issued2019-01-08
dc.description.abstractFinancial 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.
dc.format.extent10 pages
dc.identifier.doi10.24251/HICSS.2019.129
dc.identifier.isbn978-0-9981331-2-6
dc.identifier.urihttp://hdl.handle.net/10125/59544
dc.language.isoeng
dc.relation.ispartofProceedings of the 52nd Hawaii International Conference on System Sciences
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectBig Data and Analytics: Pathways to Maturity
dc.subjectDecision Analytics, Mobile Services, and Service Science
dc.subjectData Visiualization, Data Analytics, Financial Statement Audit, Materiality, Process Mining
dc.titleMateriality Maps – Process Mining Data Visualization for Financial Audits
dc.typeConference Paper
dc.type.dcmiText

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