Investigating ultimate beneficiaries to detect fraudulent transactions is a complex challenge that requires integration of data from financial transactions with external data from multiple sources.
Timbr accelerates data integration without need to transform data into graph format, and exposes the data as a web of relationships that any analyst can use to explore the data and identify fraudulent transactions.
Users take advantage of fast graph algorithms working on CPUs or GPUs, that deliver advanced analytics in any BI tool, so there’s no need to add new infrastructure or learn new skills.
Learn more about Timbr AML capabilities and register for free to test Timbr.
With Timbr productivity features, data teams deliver analytical requests in hours or days instead of months:
Create conceptual data models with meaning and relationships
Map the model to your databases and external data sources
Query in No JOINs SQL, Apache Spark, Python, R, Java or Scala
Visualize and traverse your databases as a graph
Use graph algorithms to create recommendation engines with ease
Connect your BI and DS tools or use Timbr’s charts and dashboards