Data mining has a tremendous contribution for researchers to extract the hidden knowledge and information which have been inherited in the raw data. This study has proposed a brand new and practical fuzzy analytic network process (FANP) based weighted RFM (Recency, Frequency, Monetary value) model for application in K-means algorithm for auto insurance customers’ segmentation. The developed met...

Due to today’s advancement in technology and businesses, fraud detection has become a critical component of financial transactions. Considering vast amounts of data in large datasets, it becomes more difficult to detect fraud transactions manually. In this research, we propose a combined method using both data mining and statistical tasks, utilizing feature selection, resampling and cost-...

Fraud is increasing dramatically with the expansion of modern technology and the global superhighways of communication, resulting in the loss of billions of dollars worldwide each year. Although prevention technologies are the best way of reducing fraud, fraudsters are adaptive and, given time, will usually find ways to circumvent such measures. Methodologies for the detection of fraud are esse...

Quantum Computing in high-frequency trading and fraud detection is an analysis of quantum computing how it can be used by the different industries especially finance. It evolution from traditional method. a process that concentrated on creating systems technology based theory rules. describes energy atomic subatomic levels. uses bits (qubits) which are more advanced than computers. This article...

Fraud in healthcare is widespread, as doctors could prescribe unnecessary treatments to increase bills. Insurance companies want detect these anomalous fraudulent bills and reduce their losses. Traditional fraud detection methods use expert rules manual data processing. Recently, machine learning techniques automate this process, but hand-labeled extremely costly usually out of date. We propose...

Auto insurance rates can vary dramatically; premiums are often much higher in poor and minority areas than elsewhere, even after accounting for individual characteristics, driving history, and coverage. This paper uses a unique data set to examine the relative influence of place-based socioeconomic (SES) characteristics (or “redlining”) and place-based risk factors on the place-based component ...

Fighting fraudulent insurance claims is a vital task for companies as it costs them billions of dollars each year. Fraudulent happen in all areas insurance, with auto being the most widely reported and prominent type fraud. Traditional methods identifying claims, such statistical techniques predictive modeling, can be both costly inaccurate. In this research, we propose new way to detect using ...

This paper presents an H optimization-based approach for the detection and isolation of faults in a horizontal axis wind turbine. The primary residuals are generated from separate parity equations for each of the blade pitch and drivetrain subsystems. Then, a robust secondary residual filtering scheme is developed to remove undesirable cross coupling in fault-residual pairings while suppressin...

With the rise and swift growth of E-Commerce, credit card uses for online purchases has increased dramatically and it caused sudden outbreak in the credit card fraud. Fraud is one of the major ethical issues in the credit card industry. With both online as well as regular purchase, credit card becomes the most popular mode of payment with cases of fraud associated with it are also increasing. A...