Top blog posts of 2020
As we wrap up the year 2020, we thought it’d be the perfect opportunity to look back on some of the top blog posts we’ve shared throughout the year (in no particular order). From how to leverage graph analytics in money laundering and fraud investigations to our latest releases, breaking coverage on the FinCEN files investigation, and more.
2020 was an unprecedented year – but we’ve got our sights set high for what’s to come in 2021. Be sure to stick around for more to come!
Empowering anti-financial crime heroes
Anti-money laundering use cases for graph analytics
Anti-money laundering (AML) and graph analytics are 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 against money laundering.
Fraud use cases for graph analytics
Fraudsters continue to exploit new technology to undermine and target businesses and individuals. In the industry, anti-fraud professionals often describe their fight against fraudulent activity as an ‘arms race’ that forces businesses and public organizations to constantly find new lines of defense to protect themselves and their stakeholders.
In this post, we highlight the various use cases that can be leveraged to expose fraud networks with the help of graph technology.
AML compliance: new technologies to fight back against money laundering networks
This article will present the benefits of graph analytics to identify the complex schemes and suspicious relationships associated with sophisticated money laundering patterns. You will discover how Linkurious Enterprise helps speed up anti-money laundering investigations and drive down anti-money laundering risks.
The technology behind the FinCEN files investigations
ICIJ’s latest investigation, the FinCEN files, sheds light on how financial criminals use US banks to move money throughout the world. This blog post looks behind the scenes of the investigation to explain how ICIJ used Linkurious Enterprise coupled with the Neo4j graph database and other tools to uncover stories of corruption, fraud and money laundering.
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 these changes in behavior pose an even larger threat to consumer safety as criminals seek to exploit the pandemic and carry out illegal activity.
A new set of super powers for analysts and investigators
Top 10 Query Templates to accelerate your investigations
Do your investigations involve recurring steps? Are you looking to make the power of graph queries available to non technical users? Linkurious Enterprise’s Query Templates are exactly what you need.
This blog post showcases 10 examples of what can be done with Query Templates. It covers scenarios such as turning a specific set of graph traversals into a single button, calling an external service to enrich your graph, and how to turn complex code into an easy to use form.
Linkurious Enterprise 2.10: Edge grouping and dynamic node sizing
The release of Linkurious Enterprise added new capabilities such as edge grouping, dynamic sizing of nodes, and the ability to use edges and current users as input in Query Templates along with changes such as improved support for CosmosDB, compatibility with Elasticsearch 7.X, information about users’ last active date, additional information for closed alerts, and removal of filtered out nodes and edges in exports.
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