A Review of Text Mining Methods in Fraudulent Financial Statements Detection
Financial fraud is one of the most serious threats to the financial industry. Financial statements are basic documents that duplicate a company’s economic situation. The fundamental foundations of a decision-making process for financing stakeholders include financial information users such as the general public, creditors, and so on. Financial fraud has severely harmed the long-term growth of financial markets and businesses. The number of financial reporting fraud instances continues to rise. Each incidence is a heavy blow to partners, banks, and financial experts, and it has a big impact on human growth. One of the most important concerns is detecting financial reporting fraud through the use of an active model. The goal of this research is to uncover frauds using various text-mining algorithms in order to protect the public’s investments. This research will be beneficial to auditors and financial regulators.
Keywords: Adaptive Crime, Deep Belief Network, Financial statements, Fraud Detection Model Text Mining.
