Continuous Auditing in Big Data Computing Environments: Towards an Integrated Audit Approach by Using CAATTs



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Continuous Auditing in Big Data Computing Environments: Towards an Integrated Audit Approach by Using CAATTs Andreas Kiesow, Novica Zarvić, Oliver Thomas Stuttgart, 23.09.2014 Management komplexer IT-Systeme und Anwendungen (MITA) 2014

Agenda Introduction Theoretical Background Research Approach Results Discussion Conclusion & Outlook 2

Introduction Impact of the Big Data paradigm on Financial Audit: The Big Data Computing Environment (BDCE) Enterprise Accounting Transactions Assessment Accounting Processes Accounting Information Systems (AIS) Control Environment Financial Statements Certification Computer-Assisted Audit Tools Audit Transaction Level and Techniques (CAATTs) True and Fair View? 3

Introduction Impact of the Big Data paradigm on Financial Audit: The Big Data Computing Environment (BDCE) Volume: Complexity and Risk Enterprise Audit Accounting Transactions Variety: increasing complexity and complicate the ex post traceability of data source Assessment Velocity: Limitations of manual, Transaction annual audit with Level historic data Accounting Processes Veracity: Completeness and Accounting Information Accuracy, Systems data (AIS) privacy and Control information Environment security Computer-Assisted Audit Tools and Techniques (CAATTs) Financial Statements Certification Big Data Analytics: fraud detection, risk-assessment True and Fair View? 4

Introduction Impact of the Big Data paradigm on Financial Audit: The Big Data Computing Environment (BDCE) Enterprise Accounting Transactions Assessment Accounting Processes Accounting Information Systems (AIS) Control Environment Continuous Auditing Financial Statements Certification Computer-Assisted Audit Tools Audit Transaction Level and Techniques (CAATTs) True and Fair View? 5

Introduction The overall goal: Realization of Continuous Auditing (CA) Scope of this paper: Analysis of established types of CAATTs in terms to their support of the IT auditor to conduct a proper examination of financial statements in a BDCE 6

Theoretical Background: CAATTs Computer-Assisted Audit Tools and Techniques (CAATTS) are tools and techniques used to examine directly the internal logic of an application as well as the tools and techniques used to draw indirectly inferences upon an application's logic by examining the data processed by the application (Hall, 2010) Types of CAATTs Test Data (TD) Integrated Test Facility (ITF) Parallel Simulation (PS) Embedded Audit Module, System Control and Audit Review Files (EAM/ SCARF) Generalized Audit Software (GAS) Snapshot Method (tagging and tracing) Description Fictitious, auditor-prepared data, which will be processed by the audited systems. The evaluation bases on a comparison between the results of the test data and the auditor s expectations. The processing within the audited systems is a black box. Processing of Test Data in separated areas or modules within the audited system. The results of the internal system controls are visible for the auditor. Auditor-developed application, which is completely separated from the client s systems. The results of processing real data are compared with the results of the client s systems. Auditor-developed module which is implemented within a client s system. EAM evaluates real data by predefined criteria while it is processed. Results of EAM evaluations can be written into a SCARF, which is send to the auditors for further examination Auditor-developed and self-contained applications, which evaluate extracted real data and analyze them, regarding predefined criteria. Selection and marking of accounting transactions and monitoring their processing within the AIS. After every step, a snapshot is created and analyzed. Typology of CAATTs (Braun & Davis, 2003; Rittenberg et al., 2009) 7

Research Approach Design Science (March, Smith 1995 & Hevner et al. 2004) Diffusion Analysis Requirements Analysis (Kiesow et al. 2014) Conceptual Architecture (Scope of this Paper) Evaluation Design Iterative Research Approach (Österle et al., 2011) 8

Results: Investigating Existing Audit Tools and Techniques Assessment: Applicability of CAATTs for the Dimensions of Big Data based on literature and own considerations 9

Results: Conceptual IT Architecture The combination of Embedded Audit Modules (EAM), Test Data, General Audit Software (GAS) enables basically the adoption of Big Data Audit Cockpit enables permanent monitoring of the control environment 10

Discussion: Informed Argument Assessment according to the Typology of Audit (Marten et al., 2007) No. Dimension 1 Risk-oriented Audit 2 Direct Audit 3 System Audit, Goal-oriented Audit 4 Transaction Audit 5 Basic Population Audit 6 Progressive Audit and Retrograde Audit 7 Formal Audit 8 Computer-assisted Audit 9.1 Continuous Audit 9.2 On-site Audit and Off-site Audit 9.3 Announced Audit and Unannounced Audit 11

Discussion: Limitations Technical realization of the approach requires the implementation of manifold interfaces Reorganization of the processes Controls and data flows have to be carved out and analyzed Approach is not able to cover manual controls Reduction of system performance Code modifications Long-term solution, strategic planning/management decisions 12

Conclusion & Outlook Conclusion The design of appropriate audit solutions for BDCE is of increasing importance Continuous Auditing (CA) gains in importance due to the evolution of (A)IS CA has to be realized by computer-assisted audit tools and techniques (CAATTs) The tools and techniques to handle and use Big Data are already in place Audit Solution can build on the combination of different techniques Realization and Implementation is a recognized technical challenge and related with high costs Outlook Prototyping Stronger Evaluation (in practical environment) Organizational requirements, internal controls, IT framework (e.g. COSO, COBIT) 13

Questions & Comments Thank you for your attention. Questions and Comments? Andreas Kiesow, CISA Information Management and Information Systems Osnabrück University, Germany andreas.kiesow@uni-osnabrueck.de 14