Graph + AI World:                   

Building a State of the Art Fraud Detection System with Graph + AI

Graph + AI World Session - Recorded September 2020
A walk-through and demonstration of what analytic features can be rapidly generated by using graph analytics on modest cloud hardware, and how they improves fraud scores, reducing missed frauds AND reducing false-positives, in a standard machine-learning pipeline.

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You gotta use the right tool for the right job. If you only have one user in the system, you are just doing single analytics and you have time to load terabytes of data into your RAM, Spark might be an option. But it is only going to fit about 2-3% of the use cases that we use TigerGraph for.

Dan McCreary, Optum

About TigerGraph

TigerGraph is the only scalable graph database for the enterprise. Based on the industry’s first Native and Parallel Graph technology, TigerGraph unleashes the power of interconnected data, offering organizations deeper insights and better outcomes. TigerGraph fulfills the true promise and benefits of the graph platform by tackling the toughest data challenges in real time, no matter how large or complex the dataset. TigerGraph’s proven technology supports applications such as fraud detection, customer 360, MDM, IoT, AI and machine learning to make sense of ever-changing big data, and is used by customers including Amgen, China Mobile, Intuit, Wish and Zillow, along with some of the world’s largest healthcare, entertainment and financial institutions. 


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