Financial Statement Fraud Detection by Data Mining
نویسنده
چکیده
-------------------------------------------------------------------ABSTRACT---------------------------------------------------------------------Financial losses due to financial statement frauds (FSF) are increasing day by day in the world. The industry recognizes the problem and is just now starting to act. Although prevention is the best way to reduce frauds, fraudsters are adaptive and will usually find ways to circumvent such measures. Detecting fraud is essential once prevention mechanism has failed. Several data mining algorithms have been developed that allow one to extract relevant knowledge from a large amount of data like fraudulent financial statements to detect FSF. It is an attempt to detect FSF ; We present a generic framework to do our analysis.
منابع مشابه
Financial Reporting Fraud Detection: An Analysis of Data Mining Algorithms
In the last decade, high profile financial frauds committed by large companies in both developed and developing countries were discovered and reported. This study compares the performance of five popular statistical and machine learning models in detecting financial statement fraud. The research objects are companies which experienced both fraudulent and non-fraudulent financial statements betw...
متن کاملPresenting a Model for Financial Reporting Fraud Detection using Genetic Algorithm
both academic and auditing firms have been searching for ways to detect corporate fraud. The main objective of this study was to present a model to detect financial reporting fraud by companies listed on Tehran Stock Exchange (TSE) using genetic algorithm. For this purpose, consistent with theoretical foundations, 21 variables were selected to predict fraud in financial reporting that finally, ...
متن کاملApplication of Data Mining Techniques for Financial Accounting Fraud Detection Scheme
Data mining techniques are providing great aid in financial accounting fraud detection, since dealing with the large data volumes and complexities of financial data are big challenges for forensic accounting. The implementation of data mining techniques for fraud detection follows the traditional information flow of data mining, which begins with feature selection followed by representation, da...
متن کاملA Solution for Preventing Fraudulent Financial Reporting using Descriptive Data Mining Techniques
In the present age of scams, financial statement fraud represents enormous cost to our economy. The deliberate misstatement of numbers in the accounting books with the help of well planned scheme by an intelligent squad of knowledgeable perpetrators in order to deceive the capital market participants is termed as financial statement fraud. In order to reduce fraud risk which comprehends both de...
متن کاملIdentification of Fraud in Banking Data and Financial Institutions Using Classification Algorithms
In recent years, due to the expansion of financial institutions,as well as the popularity of the World Wide Weband e-commerce, a significant increase in the volume offinancial transactions observed. In addition to the increasein turnover, a huge increase in the number of fraud by user’sabnormality is resulting in billions of dollars in lossesover the world. T...
متن کاملIdentification of Fraud in Banking Data and Financial Institutions Using Classification Algorithms
In recent years, due to the expansion of financial institutions,as well as the popularity of the World Wide Weband e-commerce, a significant increase in the volume offinancial transactions observed. In addition to the increasein turnover, a huge increase in the number of fraud by user’sabnormality is resulting in billions of dollars in lossesover the world. T...
متن کامل