This blog takes a closer look at the concept of privacy-preserving synthetic data. It answers the question “what is synthetic data” and looks at the origin of synthetic data in the context of data privacy. It also presents one way of generating privacy-preserving synthetic data and its benefits for organizations.…

Graph are meant to be seen

The third layer of graph technology that we discuss in this article is the front-end layer, the graph visualization one. The visualization of information has been the support of many types of analysis, including Social Network Analysis. For decades, visual representations have helped researchers,…

Read part 1 - The graph database landscape

The graph analytics landscape 2019

Graph analytics frameworks consist of a set of tools and methods developed to extract knowledge…

Organizations across industries are adopting graph analytics to reinforce their anti-fraud programs. In this post, we examine three types of fraud graph analytics can help investigators combat: insurance fraud, credit card fraud, VAT fraud.

Detecting fraud is about connecting the dots

In many areas, fraud investigators have at their disposal large datasets in which clues are hidden. These clues are left behind by…

Why is graph visualization so important? How can it help businesses sifting through large amounts of complex data? We explore the answer in this post through 5 advantages of graph visualization and different use cases.

What is graph visualization

Also called network, a graph is a collection of nodes (or vertices) and edges (or links). Each node represents a single data point (a person, a phone number, a transaction) and each edge represents how two nodes…

From detecting anomalies to understanding what are the key elements in a network, or highlighting communities, graph analytics reveal information that would otherwise remain hidden in your data. We will see how to integrate your graph analytics with Linkurious Enterprise to detect and investigate insights in your connected data.

What is graph analytics

Definition and…

For decades, the intelligence community has been collecting and analyzing information to produce timely and actionable insights for intelligence consumers. But as the amount of information collected increases, analysts are facing new challenges in terms of data processing and analysis. In this article, we explore the possibilities that graph technology is offering for intelligence analysis.

Intelligence collection and analysis in the age of…

ECommerce fraud is growing quickly, creating new challenges in terms of prevention and detection. As merchants gather more and more information about customers and their behaviors, the key element in the fight against fraud is now to draw on the connections within the data collected to uncover fraudulent behaviors. In this post we explain why and how graph technologies are crucial in the detection of eCommerce fraud.…

Fighting financial crimes is a daily battle worldwide. Organizations have to deploy intelligent systems to prevent and detect wrongdoings, such as anti-money laundering (AML) control frameworks. We’ll see in this blog post how graph technologies can reinforce those systems.

Using graph technologies to fight financial crimes

In today’s complex economy, law enforcement and financial…