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Anti-money laundering use cases for graph analytics

Anti-money laundering (AML) and graph analytics is a match made in heaven. A lot of anti-money laundering use cases require identifying suspicious connections whereas graph analytics is designed to analyze complex connections from big data at scale. In this article we will provide a series of examples where graph analytics can be used to fight back […]

AML and graph analytics: a match made in heaven

Why should Anti-Money Laundering (AML) teams pay attention to graph analytics? In this article we will dive into the problems with today’s AML compliance technology, how it impacts anti-money laundering and how graph analytics can provide a path forward for a more effective detection and investigation of AML cases.

Financial institutions face increased challenges as COVID-19 fraud cases continue to rise

As the world adjusts to a new reality resulting from the recent COVID-19 outbreak, the financial behavior of consumers around the world is shifting. Financial institutions are seeing more and more of their customers turn to channels they otherwise would not use including larger cash withdrawals, cryptocurrency, and the switch to more online banking. But […]

VAT fraud : the mysterious case of the missing trader

We have explored in the past how businesses are targeted by fraud schemes. Countries too are victims of fraud. In Europe the Value Added Tax (VAT) is manipulated by criminals that can win hundreds of millions. Let’s see how these VAT fraud rings operate and how to use graph technologies to detect them. Getting rich […]

3 types of fraud graph analytics can help defeat

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.

Graph-based intelligence analysis

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.