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Financial fraud has shown itself to be a fundamental issue throughout history, and due to its substantial impact on society consideration into the best method of solving it is highly important. There are a several key experimental issues that are relevant to computational intelligence-based financial fraud detection, and in this paper we will investigate three of them: choice of detection algorithm,...
Financial fraud is an issue with far reaching consequences in the finance industry, government, corporate sectors, and for ordinary consumers. Increasing dependence on new technologies such as cloud and mobile computing in recent years has compounded the problem. Traditional methods involving manual detection are not only time consuming, expensive and inaccurate, but in the age of big data they are...
Financial fraud detection is an important problem with a number of design aspects to consider. Issues such as problem representation, choice of detection technique, feature selection, and performance analysis will all affect the perceived ability of solutions, so for auditors and researchers to be able to sufficiently detect financial fraud it is necessary that these issues be thoroughly explored...
Financial fraud detection is an important problem with a number of design aspects to consider. Issues such as algorithm selection and performance analysis will affect the perceived ability of proposed solutions, so for auditors and researchers to be able to sufficiently detect financial fraud it is necessary that these issues be thoroughly explored. In this paper we will revisit the key performance...
Financial statement fraud detection is an important problem with a number of design aspects to consider. Issues such as (i) problem representation, (ii) feature selection, and (iii) choice of performance metrics all influence the perceived performance of detection algorithms. Efficient implementation of financial fraud detection methods relies on a clear understanding of these issues. In this paper...
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