Graph database analytics for investigations and fraud detection

Video: Graph database analytics for investigations, compliance and fraud detection

Terry Goodman, Managing Director of Intech Solutions, delivered a Graph database analytics specific keynote address at the 7th Annual Australian Government Data Summit held on the 23-25th March 2021 in Canberra.


Terry’s presentation covered an exciting new topic regarding graph database analytics and its use in investigations, compliance and financial fraud detection solutions. His presentation included:

  • Relational vs key-value vs graph databases
  • The next generation of graph databases
  • Preparing data for graph database analytics

Terry also shared an interesting case study, describing the Australian Tax Office (ATO) adoption of the TigerGraph graph database.  TigerGraph is a modern graph solution winning global applause for its unrivalled speed and scalability. 


Watch Terry’s full presentation below.  Graph database analytics for investigations, compliance and fraud detection

Data Science

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Data collected by organizations is increasing at a relentless pace, but can still give a misleading or fragmented view of the real world. 

For example, a person could appear multiple times or have multiple digital entities within the same database, due to typos, name changes, aggregation of different systems and so on. So, how do we match entities when the ID systems may be different or contain errors?

Entity resolution (ER) helps get to the truth. Entity resolution, which is the disambiguation of real-world entities in a database, is an essential data quality tool.

Graph provides an efficient approach for the entity resolution problem. A native graph database with massive parallel computing capability is the best tool to implement the approach.

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Intech provides data solutions that lay a secure foundation for robust, cost-effective and timely business transformation. Intech’s products have been successfully deployed to thousands of users, across hundreds of sites. See For more, see graph database solutions and TigerGraph.

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