REDWOOD CITY, Calif., Nov. 20, 2019 – TigerGraph, the only scalable graph database for the enterprise, today announced that the world’s most innovative financial services organizations — from emerging ...

Graph Database Market Size, Share & Trends Analysis Report By Type (RDF, Property Graph), By Solution (Software, Services), By Application (Analytics, Risk Management & Fraud Detection ...

In bridging those silos, graph databases can help AI/ML deliver superior predictive analytics, risk management, fraud detection, anti-money laundering, insider-trading monitoring, automated ...

Graph databases enable investigators to store detailed patterns of problematic actors. Then, they can query the data to uncover intricate connections between the suspicious actor and other entities.

NEW PRODUCT ANALYSIS: Unlike other graph databases that delve two to three levels deep into the connected data, TigerGraph's pattern analytics is tuned to be efficient and tractable with the ...

Similarly, an ecommerce platform employs graph networks to identify high-risk orders based on behavioral anomalies, effectively reducing chargebacks while preserving a seamless customer experience.

Neo4j's Bryan Evans talks about the company's fraud detection strategy, based on a database of knowledge graphs, at AWS Financial Services Symposium.

Key-value, document-oriented, column family, graph, relational… Today we seem to have as many kinds of databases as there are kinds of data. While this may make choosing a database harder, it ...

Graph databases enable investigators to store detailed patterns of problematic actors. Then, they can query the data to uncover intricate connections between the suspicious actor and other entities.