USING DATA MINING IN FINANCIAL AUDIT

In recent years, the volume and complexity of transactions recorded in the accounts have grown significantly. Auditor's Responsibility to analyze a sufficient number of transactions requires the use of new techniques and in making the audit, computer-assisted audit techniques play an important role. Data mining is a modern and powerful tool that can be used to extract useful information, but still unexpected or unknown. Analysis and data mining of multidimensional database is performed using advanced analysis techniques including statistical algorithms, artificial intelligence, neural networks, fuzzy logic, genetic algorithms and data visualization. Although data mining is frequently considered as a highly skilled technique in many fields of application, it has not been widely adopted in the audit profession yet. However, it is expected to gain increasing popularity in audit. Automation potential mines data suggest that might improve the efficiency of audit professionals, including the replacement level of involvement of professional staff. Data mining, knowledge discovery technique as databases, can be very effective in the audit. Both the testing phase, but also in the risk analysis of a mission, data mining technique could be used as a complementary, as a tool in the hands of the auditor. Thus the stage to perform tests of detail, the techniques of data mining can support the auditor's judgment, offering him an automatic analysis of a large set and complex data in order to discover patterns, "boilerplate" outstanding trends or exceptions would otherwise go unnoticed. Completion risk assessment techniques for unsupervised learning data may lead to identification of risks that were not identified during the audit circuit.