Does Risk Matter? An Audit Risk Approach for Technology Adoption in Financial Audits

ABSTRACT Technology adoption models are widely applied to examine factors influencing the use of computer‐assisted audit techniques and tools (CAATTs). However, these models do not incorporate audit risk components and the risk‐based approach embedded in auditing standards, limiting their relevance to the auditing domain. This study addresses this gap through a qualitative analysis based on an exploratory study and semistructured interviews with audit professionals from 16 accountancy firms that audit public companies. The findings identify key determinants, related to audit risk factors, that shape CAATTs adoption decisions within the context of financial audits. These determinants reflect the unique regulatory and risk‐oriented environment of auditing, distinguishing it from general technology adoption in other industries. The study also proposes a risk‐based decision‐making framework aligned with auditing standards to support effective CAATTs adoption. Notable differences were found between large and small firms, driven by variations in senior management perceptions, access to technological resources and capacity for training and knowledge sharing. The findings offer practical implications for auditors, standard‐setters and developers seeking to enhance CAATTs integration and audit quality through a deeper understanding of audit‐specific contextual factors.

Authors

Institutions

Publication Details

Journal
International Journal of Auditing
Published
2025-09-03
DOI
https://doi.org/10.1111/ijau.70005
Primary Topic
Technology Adoption and User Behaviour
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Does Risk Matter? An Audit Risk Approach for Technology Adoption in Financial Audits

Shalom Levy, Jeffrey Kantor, Arthur M. Cohen
International Journal of Auditing
Technology Adoption and User Behaviour
article

Does Risk Matter? An Audit Risk Approach for Technology Adoption in Financial Audits

Shalom Levy, Jeffrey Kantor, Arthur M. Cohen
article en

Abstract

ABSTRACT Technology adoption models are widely applied to examine factors influencing the use of computer‐assisted audit techniques and tools (CAATTs). However, these models do not incorporate audit risk components and the risk‐based approach embedded in auditing standards, limiting their relevance to the auditing domain. This study addresses this gap through a qualitative analysis based on an exploratory study and semistructured interviews with audit professionals from 16 accountancy firms that audit public companies. The findings identify key determinants, related to audit risk factors, that shape CAATTs adoption decisions within the context of financial audits. These determinants reflect the unique regulatory and risk‐oriented environment of auditing, distinguishing it from general technology adoption in other industries. The study also proposes a risk‐based decision‐making framework aligned with auditing standards to support effective CAATTs adoption. Notable differences were found between large and small firms, driven by variations in senior management perceptions, access to technological resources and capacity for training and knowledge sharing. The findings offer practical implications for auditors, standard‐setters and developers seeking to enhance CAATTs integration and audit quality through a deeper understanding of audit‐specific contextual factors.

International Journal of AuditingVol. 30(1)
Ariel University (IL)
Openalex Percentile: Top 77%
Technology Adoption and User Behaviour
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.