Subtopic Deep Dive
Robotic Process Automation in Auditing
Research Guide
What is Robotic Process Automation in Auditing?
Robotic Process Automation in Auditing applies RPA bots to automate repetitive audit tasks including compliance checks, data extraction from financial documents, and risk assessments.
Researchers develop frameworks integrating RPA with traditional auditing for efficiency gains. Key papers include Huang and Vasarhelyi (2019) proposing an RPA framework for auditing (279 citations) and Eulerich et al. (2021) providing guidance on bot prioritization (117 citations). Over 10 papers since 2019 map RPA applications in accounting and auditing.
Why It Matters
RPA in auditing reduces manual data processing time by up to 80% in compliance checks, as shown in Huang and Vasarhelyi (2019). Gotthardt et al. (2020) highlight its role in addressing auditor shortages amid rising regulatory demands (161 citations). Zhang (2019) demonstrates IPA combining RPA with AI for intelligent risk detection, enhancing audit accuracy in firms like Big Four accounting practices.
Key Research Challenges
Integration with Legacy Systems
RPA bots struggle to interface with outdated auditing software, requiring custom adapters. Gotthardt et al. (2020) identify this as a barrier in accounting implementations. Syed et al. (2019) note compatibility issues across 494 cited themes (494 citations).
Ensuring Bot Accuracy in Judgments
Automating judgment-based audit tasks risks errors without human oversight. Zhang (2019) discusses IPA limitations in flexible decision-making. Eulerich et al. (2021) emphasize prioritizing verifiable tasks to avoid compliance failures.
Scalability During Peak Audit Seasons
RPA deployments face bottlenecks in high-volume periods like year-end closes. Siderska (2021) reports adoption challenges during COVID-19 surges (85 citations). Enríquez et al. (2020) map scalability gaps in industrial RPA studies.
Essential Papers
Robotic Process Automation: Contemporary themes and challenges
Rehan Syed, Suriadi Suriadi, Michael Adams et al. · 2019 · Computers in Industry · 494 citations
Robotic Process Automation and Artificial Intelligence in Industry 4.0 – A Literature review
Jorge Ribeiro, Rui Lima, Tiago Eckhardt et al. · 2021 · Procedia Computer Science · 439 citations
Taking into account the technological evolution of the last decades and the proliferation of information systems in society, today we see the vast majority of services provided by companies and ins...
The Impact of Artificial Intelligence and Blockchain on the Accounting Profession
Yingying Zhang, Feng Xiong, Yi Xie et al. · 2020 · IEEE Access · 312 citations
Recent developments in technology have introduced dramatic changes to the practice of the accounting profession. This paper provides a comprehensive review of current developments in big data, mach...
Applying robotic process automation (RPA) in auditing: A framework
Feiqi Huang, Miklos A. Vasarhelyi · 2019 · International Journal of Accounting Information Systems · 279 citations
Robotic Process Automation: A Scientific and Industrial Systematic Mapping Study
J. G. Enríquez, Andres J. Ramirez, Francisco José Domínguez Mayo et al. · 2020 · IEEE Access · 172 citations
The automation of robotic processes has been experiencing an increasing trend of interest in recent times. However, most of literature describes only theoretical foundations on RPA or industrial re...
Current State and Challenges in the Implementation of Smart Robotic Process Automation in Accounting and Auditing
Max Gotthardt, Dan Koivulaakso, Okyanus Paksoy et al. · 2020 · ACRN Journal of Finance and Risk Perspectives · 161 citations
Technology development has grown rapidly in the last decades and gained importance for accounting and auditing through its identified potentials. Particularly the automation of judgment systems and...
Imperative Role of Integrating Digitalization in the Firms Finance: A Technological Perspective
Deepa Bisht, Rajesh Singh, Anita Gehlot et al. · 2022 · Electronics · 140 citations
Financial management is a critical aspect of firms, and entails the strategic planning, direction, and control of financial endeavors. Risk assessment, fraud detection, wealth management, online tr...
Reading Guide
Foundational Papers
Start with Anagnoste (2013) for RPA center setup basics (51 citations), then Huang and Vasarhelyi (2019) for auditing-specific frameworks to build integration knowledge.
Recent Advances
Study Eulerich et al. (2021) on practical bot frameworks and Siderska (2021) on pandemic-driven adoption for current scalability insights.
Core Methods
Core techniques: rule-based bot scripting (Syed et al., 2019), IPA with AI (Zhang, 2019), and task prioritization algorithms (Eulerich et al., 2021).
How PapersFlow Helps You Research Robotic Process Automation in Auditing
Discover & Search
Research Agent uses searchPapers and citationGraph to map RPA auditing literature from Huang and Vasarhelyi (2019), revealing 279 citing works on frameworks. exaSearch uncovers niche applications like Gotthardt et al. (2020) on smart RPA challenges, while findSimilarPapers links to Zhang (2019) IPA extensions.
Analyze & Verify
Analysis Agent employs readPaperContent on Eulerich et al. (2021) to extract bot prioritization frameworks, then verifyResponse with CoVe checks claims against Syed et al. (2019). runPythonAnalysis processes audit data volumes from Gotthardt et al. (2020) using pandas for efficiency metrics, graded by GRADE for statistical rigor.
Synthesize & Write
Synthesis Agent detects gaps in RPA scalability from Siderska (2021) and flags contradictions with foundational Anagnoste (2013). Writing Agent uses latexEditText and latexSyncCitations to draft frameworks, latexCompile for audit process diagrams via exportMermaid.
Use Cases
"Analyze RPA efficiency metrics from auditing papers using Python."
Research Agent → searchPapers('RPA auditing efficiency') → Analysis Agent → readPaperContent(Huang 2019) → runPythonAnalysis(pandas on extracted data tables) → matplotlib plots of time savings output.
"Draft LaTeX framework integrating RPA with audit compliance."
Synthesis Agent → gap detection(Eulerich 2021 + Gotthardt 2020) → Writing Agent → latexEditText(structured framework) → latexSyncCitations(all refs) → latexCompile(PDF with Mermaid RPA flowchart) output.
"Find GitHub repos with RPA auditing bot code from papers."
Research Agent → searchPapers('RPA auditing code') → Code Discovery → paperExtractUrls(Zhang 2019) → paperFindGithubRepo → githubRepoInspect(sample bots for compliance checks) output.
Automated Workflows
Deep Research workflow conducts systematic review of 50+ RPA papers, chaining citationGraph from Syed et al. (2019) to structured reports on auditing trends. DeepScan applies 7-step analysis with CoVe checkpoints to verify Huang and Vasarhelyi (2019) framework claims. Theorizer generates hypotheses on IPA scalability from Zhang (2019) and Siderska (2021).
Frequently Asked Questions
What is Robotic Process Automation in Auditing?
RPA in auditing deploys software bots for data extraction, compliance testing, and risk scoring in financial audits. Huang and Vasarhelyi (2019) provide a core framework (279 citations).
What methods are used in RPA auditing frameworks?
Methods include bot scripting for rule-based tasks and IPA integration with AI, as in Zhang (2019). Eulerich et al. (2021) outline task prioritization for auditors.
What are key papers on RPA in auditing?
Huang and Vasarhelyi (2019, 279 citations) on frameworks; Gotthardt et al. (2020, 161 citations) on smart RPA challenges; Eulerich et al. (2021, 117 citations) on bot development.
What open problems exist in RPA auditing?
Challenges include legacy system integration and judgment automation, per Gotthardt et al. (2020). Scalability in peaks remains unresolved, as in Siderska (2021).
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