Advancing Entity Resolution for Fraud Detection with TigerGraph
First in our series of blogs straight from our engineers to you. In today's digitally interconnected world the proliferation of data has presented both unprecedented opportunities and challenges. One of…
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…
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,…
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It’s Time to Harness the Power of Graph Technology [Infographic]
It’s time for your enterprise to harness the power of graph technology. A graph database platform – like TigerGraph – stores your data in intuitive, connected patterns so that queries…
Supercharging Fraud Detection: How a Leading Financial Institution Utilizes TigerGraph for Real-Time Entity Resolution
In today's fast-paced financial landscape, real-time fraud detection has become essential for safeguarding customer assets and preserving trust in financial institutions. One leading investment bank recently embraced an innovative solution…
