Countless research works of deep neural networks (DNNs) in the task of credit card fraud
detection have focused on improving the accuracy of point predictions and mitigating …

Insurance is a data-rich sector, hosting large volumes of customer data that is analysed to
evaluate risk. Machine learning techniques are increasingly used in the effective …

The primary goal of an investment in a financial instrument is to generate a profit, but it's
crucial to understand that this investment involves many risks. Investors will therefore need a …

With the exponential rise in government and private health-supported schemes, the number
of fraudulent billing cases is also increasing. Detection of fraudulent transactions in …

Fighting fraudulent insurance claims is a vital task for insurance companies as it costs them
billions of dollars each year. Fraudulent insurance claims happen in all areas of insurance …

One of the most common types of fraudulent is insurance fraud. And in particular fraud in
automobile insurance, the cost of automobile insurance fraud is substantial for property …

Insurance is a pivotal element in modern society, but insurers face a persistent challenge
from fraudulent behaviour performed by policyholders. This behaviour could be detrimental …

Default in premium payments impacts significantly on the profitability of the insurance
company. Therefore, predicting defaults in advance is very important for insurance …

The paper presents a novel methodology based on machine learning to optimize medical
benefits in healthcare settings, ie, corporate, private, public or statutory. The optimization is …

The number of policyholders involved in fraudulent activities has increased dramatically in
recent years. Intentionally misleading insurers by missing facts when claiming insurance has …