Decision Sciences Journal
Volume 32, Number 3
Summer 2001
A Cascaded Inference Model for Evaluation of the Internal
Audit Report
Ganesh Krishnamoorthy
Accounting Group, College of Business Administration, Northeastern
University, Boston, MA 02115-5000, email: g.krishnamoorthy@neu.edu
ABSTRACT. This paper provides a normative framework
for how external auditors should evaluate internal audit (IA)
work, with a view to assessing the risk of material misstatement.
The central issue facing the external auditor when evaluating
IA work is the reliability of IA work. Reliability assessments
are structured using the cascaded inference framework from behavioral
decision theory, in which attributes of source reliability are
explicitly modeled and combined using Bayes’ rule in order
to determine the inferential value of IA work. Results suggest
that the inferential value of an IA report is highly sensitive
to internal auditor reporting bias, but relatively insensitive
to reporting veracity. Veracity refers to internal auditors’
propensity to report truthfully, whereas bias refers to the propensity
to misreport findings. Results also indicate that this sensitivity
to reporting bias is conditional on the level of internal auditor
competence, thus suggesting significant interaction effects between
the objectivity and competence factors. Collectively, these findings
suggest that the impact of source reliability attributes may
be more complex than portrayed in the auditing standards and
that recognizing these subtleties may lead to greater efficiency
and effectiveness.
Subject Areas: Audit Evidence, Audit Judgment, Bayes’
Theorem, Cascaded Inference, Internal Audit, and Probability
Models. |