I work in a bank and most data is in tabular format in relational databases. I have been reading about graph algorithms (page rank), graph libraries (spark graphx) and graph databases (neo4j). I would like to pick a use case from my field (finance). What use case would be suitable for graph algirithms and databases?

  • 1
    $\begingroup$ Fraud detection using social features. $\endgroup$
    – Emre
    Jan 9, 2018 at 21:06

1 Answer 1


There are many use cases of graph theory in Finance industry and it is a very broad question. As Emre said can be used for Fraud Detection, Risk Modelling, Economic Networks etc.

These below links can give you better understanding of different application, please go through for better understanding:

  1. Applications of Graph Theory In Finance
  2. Graph Theory for Systemic Risk Models
  3. Graph theory: connections in the market
  4. Analysis of Equity Markets: A Graph Theory Approach
  5. Portfolio Diversification
  6. From Graph Theory to Models of Economic Networks. A Tutorial

Do let me know if you need any additional information.

  • $\begingroup$ Thank you, those are some amazing links; never thought of using graphs as a visual way to measure correlation $\endgroup$
    – Victor
    Jan 11, 2018 at 20:57
  • $\begingroup$ Good to hear! Do let me know if you have any issues. $\endgroup$
    – Toros91
    Jan 12, 2018 at 1:27
  • $\begingroup$ I am just having difficulty how a graph model can detect a fraud ring.? You start with a oerson known to be a fraud and find all his connections on social media and based on the number of direct interactions eith the primary ring leader,assign a fraudster probability to each connection? $\endgroup$
    – Victor
    Jul 15, 2018 at 3:32
  • $\begingroup$ @Victor: For you to do that you need to use this methodology like giving weight-age to the respective connection and based on that which ever link has more and darker link between 2 nodes $\endgroup$
    – Toros91
    Jul 16, 2018 at 9:14

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