Data Mining Techniques Research On Financial Statement

Abstract

Data mining is the most widely used method for detecting and preventing financial fraud. For fraud detection, data mining techniques are used in a similar way as other data mining techniques, starting with highlight determination and ending with execution assessment. Data mining techniques can distinguish fraud because they can use previous instances of fraud to build models that recognise and identify the danger of fraud. Fiscal summary fraud, one of the monetary frauds, has spread like a plague globally. The high-profile failures of high-profile companies have tarnished corporate governance, financial reporting, and review capacities. Globally, financial summary fraud has become a major issue for organisations. Accounts Recognized Data mining techniques can help identify fraudulent financial disclosures. Inspectors should provide data regardless of whether the financial summary is in accordance with GAAP (Generally Accepted Accounting Principles). They can't certify that all material errors are identified. Many data mining techniques have been proposed and implemented by local experts to better detect and prevent fiscal summary fraud.