The hybrid approach based on genetic algorithm and neural network to predict financial fraud in banks

Authors

  • Afsaneh Azimi Islamic Azad University, Electronic Unit, Department of Computer Engineering, Tehran, Iran
  • Majid Noor Hosseini Amirkabir University of Technology, Department of Computer Engineering and Information Technology, ,Tehran, Iran
Abstract:

Audit has become an essential topic in the world because there is much evidence about deliberate manipulations in the reports. One of the concerns in the field of audit is discovery and search of the financial statements and the high volume of bulk data. This study tried to suggest the appropriate method to detect these frauds due to the data which has been available and a proposed algorithm. Research data of the Greek companies have been used and the results of output show that about 83 percent correct prediction are shown in the output.

Upgrade to premium to download articles

Sign up to access the full text

Already have an account?login

similar resources

A hybrid model based on machine learning and genetic algorithm for detecting fraud in financial statements

Financial statement fraud has increasingly become a serious problem for business, government, and investors. In fact, this threatens the reliability of capital markets, corporate heads, and even the audit profession. Auditors in particular face their apparent inability to detect large-scale fraud, and there are various ways to identify this problem. In order to identify this problem, the majori...

full text

The Predictability Power of Neural Network and Genetic Algorithm from Fiems’ Financial crisis

Organizations expose to financial risk that can lead to bankruptcy and loss of business is increased nowadays. This may leads to discontinuity in operations, increased legal fees, administrative costs and other indirect costs. Accordingly, the purpose of this study was to predict the financial crisis of Tehran Stock Exchange using neural network and genetic algorithm. This research is descripti...

full text

Investigating Financial Crisis Prediction Power using Neural Network and Non-Linear Genetic Algorithm

Bankruptcy is an event with strong impacts on management, shareholders, employees, creditors, customers and other stakeholders, so as bankruptcy challenges the country both socially and economically. Therefore, correct prediction of bankruptcy is of high importance in the financial world. This research intends to investigate financial crisis prediction power using models based on Neural Network...

full text

Providing a Model for Detecting Tax Fraud Based on the Personality Types of Corporate Financial Managers using the Neural Network Approach

One of the management measures to reduce tax liabilities is non-payment of taxes through tax fraud. Because personality factors may play a role in explaining tax ethics, examining personality traits and aspects of tax fraud can help to better understand the factors that influence tax decisions. The main purpose of this study is to provide a model for detecting tax fraud based on the personality...

full text

Prediction of Driver’s Accelerating Behavior in the Stop and Go Maneuvers Using Genetic Algorithm-Artificial Neural Network Hybrid Intelligence

Research on vehicle longitudinal control with a stop and go system is presently one of the most important topics in the field of intelligent transportation systems. The purpose of stop and go systems is to assist drivers for repeatedly accelerate and stop their vehicles in traffic jams. This system can improve the driving comfort, safety and reduce the danger of collisions and fuel consumption....

full text

My Resources

Save resource for easier access later

Save to my library Already added to my library

{@ msg_add @}


Journal title

volume 6  issue 1

pages  641- 648

publication date 2017-06-01

By following a journal you will be notified via email when a new issue of this journal is published.

Hosted on Doprax cloud platform doprax.com

copyright © 2015-2023