|AUDITING DECISIONS AND ARTIFICIAL NEURAL NETWORKS|
|Written by LUMINITA IONESCU|
ABSTRACT. Trinkle and Baldwin write that poor credit granting decisions are coming back to haunt providers of loan finance. Hoogs et al. present a genetic algorithm approach to detecting financial statement fraud. Gaganis investigates the efficiency of k-nearest neighbours (k-NN) in developing models for estimating auditors' opinions, as opposed to models developed with discriminant and logit analyses. Moutinho et al. introduce a conceptual model whereby the focus is placed on environmental scanning, diagnostics and decision-making on the basis of managerial judgement through the application of tools such as intelligent agents, hybrid intelligent systems, scenario analysis and knowledge-based systems.
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