Fraud is one of the major sources of loss for private companies, as well as public institutions. It takes many different forms, from duplicating user accounts to insurance or credit card fraud. Of course, depending on the type of fraud you are interested in, solutions for identifying fraudsters will vary. In this section, we are going to review the different types of fraud and how a graph database such as Neo4j can help in identifying fraud. After that, we will learn how centrality measures (the main topic of this chapter) are able to provide interesting insights regarding fraud detection in some specific cases.
Detecting fraud using Neo4j
Fraudulent behavior can have multiple forms and is constantly evolving. Someone with bad intentions might steal a credit card and transfer a large amount of money to another account. This kind of transaction can be identified with traditional statistical methods and/or machine learning. The goal of these algorithms...
