Question

Define Fuzzy logic and give a scenario in which it would be useful in auditing.

Answer 1

Fuzzy logic is an approach to computing based on "degrees of truth" rather than the usual "true or false" (1 or 0) Boolean logic on which the modern computer is based.

The idea of fuzzy logic was first advanced by Dr. Lotfi Zadeh of the University of California at Berkeley in the 1960s. Dr. Zadeh was working on the problem of computer understanding of natural language. Natural language (like most other activities in life and indeed the universe) is not easily translated into the absolute terms of 0 and 1. (Whether everything is ultimately describable in binary terms is a philosophical question worth pursuing, but in practice much data we might want to feed a computer is in some state in between and so, frequently, are the results of computing.) It may help to see fuzzy logic as the way reasoning really works and binary or Boolean logic is simply a special case of it.

                                             Fuzzy logic for risk assessment in auditing.

The assessment of the risks that an entity's internal control system may fail represents a significant challenge to independent auditors. The methodologies used to audit financial statements are usually supported by classical logic, also called binary logic, departing from the relatively simplistic premise that risk factors are either present or not in a certain kind of control process. This study aimed to conceive a risk assessment model for an entity's internal control system, using the fuzzy logic approach, to take into account the diffuse elements that compose the factors of this type or risk, which are analyzed in financial statements auditing. The conceived model was conceptually validated though interviews and debates with financial statement auditing experts and relevant bibliography. We concluded that the use of fuzzy logic to support risk assessment models not only eliminates the binary restriction imposed by classic logic, but also allows for the quantitative treatment of ambiguous concepts through a psychometric scale, to refl ect adjectives like "very good", "good", "reasonable", "of great importance", "of little importance" etc. This approach makes it possible to produce broader results that are closer to reality.