Graph-Powered Cybersecurity
If you're reading this, then your daily personal and work life is probably dependent on information that is stored and accessed digitally. People and processes are working around the clock…
Reduce AML Investigation Costs with TigerGraph
by Parker Erickson and Victor LeeAnti-Money Laundering (AML) refers to the set of laws, regulations, and procedures aimed at preventing and detecting money laundering – the concealment of illegally obtained…
Using Graph Machine Learning to Improve Fraud Detection Rates
by Parker Erickson Fraud comes in all shapes and forms across many industries; from account takeovers, to transaction fraud, the financial services industry to healthcare, fraud is both prevalent and…
Integrating TigerGraph and Large Language Models for Generative AI
by Parker Erickson Introduction to Large Language Models Generative AI and Large Language Models are on everyone's mind - they have been proven to be very useful tools for general…
Graph-Powered Analytics: Why You Need It and How to Learn It
Businesses need to stay ahead of the competition, to cut losses, and to find more revenue. By looking at their data as a network and then analyzing the connections –…
The Connected Customer: Building the Foundation with TigerGraph
In the rapidly evolving world of customer-facing businesses, providing an exceptional omnichannel customer experience has become the key to success. As online retail sales have soared over the last decade,…
