Detecting the financial offences

Financial offences are getting more and more difficult to detect. Fraudsters are making up:

  • Artificial identities – taking different elements from various sources, new identities are being forged,
  • Connecting networks, bigger and smaller. The greater number of interconnected persons or business entities, the bigger scale of alleged frauds.

Standard mechanisms for fraud tracking (also those, based on Machine Learning), to a significant extent are not able to discover the situation mentioned above. It’s so, because analysed are the data, not the connections. If we connect persons, that use the same ID card no. or personal identifcation no., or persons hsharing the same phone no. or email address, or persons sharing the same living address etc., it will become obvious that these persons will be identified as “mutually connected” – although in conventional databases they will remain strangers. Graph database in-built algorithms allow for discovering connections and the groups of information, which in turn helps in finding the fraud chains.

The structure of GraphIQ tool enables to adapt the data structures to ever-changing requirements (e.g. fraud detection tactics).

Defining adequate conditions, e.g.:

  • running the same business,
  • dealing with the same goods,
  • the same security issuer,
  • connections within the capital groups,
  • identifying the relation of control (e.g.: creating the consolidated reports, right of vote, decision making power),
  • identifying economic dependance  (e.g.: mutual warranties, significant connection with one of the clients/partners/suppliers/buyers, common owners

we can draw a clearly designed graph, containing nodes and relations within previously indicated transactions and conditions, and subject it to further analyses. It is also possible to make use of external data.

There are also algorithms, predicting a specific behaviour of specific persons, based on their “friends” (persons directly related to each other). Defining the connections between different persons may be of a crucial importance, now and in the future.