Discriminant analysis and neural network methodologies were applied to the problem of identifying illegal sales transactions. The researchers independently developed models using data provided by a cr^it card company. A series of measures were developed and used to construct the models. The final results were that the discriminant analysis model recognized 32.3 % of the fraudulent activity, while the neural network approach found 28.9%. With only 11.6 % of the transactions in common, the combination of the two models identified 49.6%i. In order to provide a real time monitoring program, the models were simplified yielding a capture rate of approximately 42%
Banks as old institutions are in the middle of change. Emerging FinTech companies combine the newest...
Data mining is popularly used to combat frauds because of its effectiveness. It is a well-defined pr...
This research aims to examine whether Artificial Neural Network (ANN) method can detect fraudulent f...
Discriminant analysis and neural network methodologies were applied to the problem of identifying il...
Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses...
The task of detection card fraud transactions using neural networks and their committees is consider...
Credit card fraud is a financial type of fraud that involves the use of credit card details to purch...
Internet fraud is increasing on a daily basis with new methods for fraudulently extracting funds fro...
Abstract--- Fraud detection is necessary for any financial system. However, the way of committing fr...
Fraudulent financial reporting has become an important issue in accounting profession, the implement...
Fraud detection refers to the attempt to detect illegitimate usage of a communications network. Thre...
Misuse detection is the process of attempting to identify instances of network attacks by comparing ...
Data mining is popularly used to combat frauds because of its effectiveness. It is a well-defined pr...
Recently, compliance and regulation has been number one threat; not only for the area of financial s...
With the continuous development and wide application of artificial intelligence technology, artifici...
Banks as old institutions are in the middle of change. Emerging FinTech companies combine the newest...
Data mining is popularly used to combat frauds because of its effectiveness. It is a well-defined pr...
This research aims to examine whether Artificial Neural Network (ANN) method can detect fraudulent f...
Discriminant analysis and neural network methodologies were applied to the problem of identifying il...
Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses...
The task of detection card fraud transactions using neural networks and their committees is consider...
Credit card fraud is a financial type of fraud that involves the use of credit card details to purch...
Internet fraud is increasing on a daily basis with new methods for fraudulently extracting funds fro...
Abstract--- Fraud detection is necessary for any financial system. However, the way of committing fr...
Fraudulent financial reporting has become an important issue in accounting profession, the implement...
Fraud detection refers to the attempt to detect illegitimate usage of a communications network. Thre...
Misuse detection is the process of attempting to identify instances of network attacks by comparing ...
Data mining is popularly used to combat frauds because of its effectiveness. It is a well-defined pr...
Recently, compliance and regulation has been number one threat; not only for the area of financial s...
With the continuous development and wide application of artificial intelligence technology, artifici...
Banks as old institutions are in the middle of change. Emerging FinTech companies combine the newest...
Data mining is popularly used to combat frauds because of its effectiveness. It is a well-defined pr...
This research aims to examine whether Artificial Neural Network (ANN) method can detect fraudulent f...