Attributed graphs with both topological information and node information have prevalent
applications in the real world, including recommendation systems, biological networks …

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 …

Fraud detection is one of the main issues in reducing the unsystematic risks in insurance
business as its costs might reach to catastrophic amounts leading to higher loadings on …

In the wake of increasing digital fraud, this paper introduces an innovative application of
Artificial Intelligence (AI) in detecting fraudulent activities across finance, healthcare, and e …

Automobile insurance fraud detection is one of the most essential and highly demanding
process need to be accomplished in the insurance industries. The existing works are highly …

Clustering has been widely used in every field, but traditional classical clustering unable to
handle multiple tasks at the same time under the scenario of data sets. Comparing with the …

Territory risk analysis has played an important role in auto insurance rate regulation. It aims
to design rating territories from a set of basic rating units so that their respective risk …

Neural Networks have dominated the sphere of Machine Learning and computerized
decision trends for the past decade. The most straightforward neural architecture holds the …

Despite insurance companies detecting a large worth of fraudulent insurance claims,
detected insurance fraud is assumed to constitute only a small fraction of all insurance fraud …

The primary purpose of vehicle insurance is to cover the vehicle against damage, personal
injury, and third-party liability. In addition to this, some insurance companies also provide …