Name: Fabiano da Rocha Louzada
Type: MSc dissertation
Publication date: 27/06/2017
Advisor:

Name Rolesort descending
Credine Silva de Menezes Advisor *

Examining board:

Name Rolesort descending
Credine Silva de Menezes Advisor *
Sergio Crespo Coelho da Silva Pinto External Examiner *
Orivaldo de Lira Tavares Internal Examiner *

Summary: The annual records of public spending, associated with the need to ensure the efficiency,
legality and economy in the application of public resources, have made most of the
control institutions face a huge challenge of allocating limited audit resources more
effectively. The risk-based audit planning, which is a onerous activity in time and financial
resources, aims to ensure that the auditor examine the issues of greatest risk to the
achievement of organizational goals. In this work, we propose a methodology of audit
planning based on risk assessment with the support of a specialist system that uses
fuzzy logic to execute the process of risk assessment.
The rules have been defined based on risk factors selected from the Guide to Combating
Corruption and Fraud in Development Projects, developed by the International Anti-
Corruption Resource Center. The membership functions of the linguistic terms of the
nebulous rules were initially defined based on the knowledge of the author, who is
Auditor of the State of Espírito Santo, and afterwards a questionnaire was applied with
17 (seventeen) other State Auditors, whose result was used to refine the membership
functions of the linguistic terms, and to obtain the relevance of each of the risk factors.
The prototype was executed using, as input, a sample of one hundred contracts from the
Government of the State of Espírito Santo, obtained from the Transparency Portal, and
the results were presented to State Auditors, who are experts in the subject, to verify if
the system gives an acceptable opinion about the processes that must be audited, in
other words, whether it is able to select processes that they consider relevant and reject
those they consider to be irrelevant.
Regarding the contracts selected by the system and rejected by the specialists, the
system obtained an average of 80.5% accuracy. Regarding the contracts rejected by
the system and that were selected by the specialists, the system obtained an average
of 95.13% accuracy. In addition, the heuristic adopted by the system, different from
the heuristics adopted by the specialists, analyzes a greater range of risk factors in a
standardized way, confirming the initial hypothesis.

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