Current fraud detection systems are based on more or less simple analysis parameters, but the complexity of fraud networks makes the use of new fraud detection technology essential.
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Detecting complex fraud rings
So far we have looked at “intra-incident” information when assessing potential fraud in a file, but fraud rings are becoming larger and more complex, and require a holistic view of the relationships between those involved, events, etc. beyond the individual.
The key word here is “pattern”. Using graphs we will be able to find patterns of behaviour that take into account the relationships between data far beyond the simple file, and taking into account the totality of the historical data at our disposal.
Specifically, Neo4j helps to create robust systems for detecting bank fraud, eCommerce purchases, credit cards, insurance, etc., and all this giving real-time response, an essential requirement in the online world in which we live.
Detect fraud in real time before it occurs by creating a firewall that will stop fraudulent transactions.
Operations risk assessment
It is crucial to have a reliable system in place to assess the risk of each transaction and to provide a response that takes into account the full context of the customer in real time.
Analysis and improvement of the Fraud Prevention system
Use Neo4j’s Graph Analytics capabilities to improve your fraud prevention system in a way never seen before.
What do we want to achieve?
A fraud detection system
You will have a robust system that closes the virtuous circle of fraud management by having a real-time fraud detection system and advanced graph-based analytics that allows for continuous improvement of the system and its detection rules.
What challenges will we face?
Connecting sensing systems
We are currently working with discrete, unconnected and isolated data systems.
Connecting them and generating their hidden relationships is the first piece of this puzzle that will enable the fraud prevention solution to be generated.
What are the benefits?
Improve detection rates
Improved fraud detection rates, elimination of false positives, improved service to your customers and partners, cost savings.
These are just some of the direct consequences of the use of networks in the world of fraud prevention.
The role of Graph technology in business digitisation processes
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Let’s turn your data into relevant information for your business. Let’s explore together graph solutions for your databases and apply Neo4j technology among others.