Use Case Example –Recommendations - Learning Neo4j - page 117

Fraud detection systems
We have seen a number of customers that are using Graph Database Management
Systems such as Neo4j for fraud detection systems. The principle is quite simple: in
manycases,thefraudofaparticularnatureisnotdeinedbyonetransactiononly,
butbyachainoftransactionsthathavetheirspeciiccharacteristicsandthatneed
to be compared to one another to see if they really do constitute a case of fraud.

In the following example, we are just looking at a suspect case of credit card fraud:

User User

CreditCard CreditCard

Transaction Transaction Transaction Transaction Transaction Transaction

Suspect
Transaction

Shop
1

Shop
2

A particular user always uses his credit card for transactions at a particular store.
Another user uses his credit card for similar transactions at a different store. And all
of a sudden, there is this new transaction in the middle, which uses the credit card
(let's say for a similar kind of transaction) in the other store. This kind of pattern
maybecomelaggedasasuspectpatterninsomefrauddetectionsystems.The
system would not necessarily immediately block the credit card, but the risk score
ofthatparticulartransaction/cardcombinationwoulddeinitelygoup.Ifthescore
reaches a certain threshold, that would mean that there is an increased likelihood for
that transaction to be fraudulent, and the system would recommend that a particular
action be taken.