In an increasingly digital world, fraud has become far more difficult to detect. Online identity theft is growing at a concerning rate, with card fraud expected to hit $35bn by 2023.
This tech-savvy, dynamic fraud, and the recent increase in collusive fraud has led to businesses losing more and more money each year.
So, how can the financial services industries tackle this pressing issue?
Our latest whitepaper takes a look at how data science can be key to a secure digital service, detecting fraudulent activity with 100% certainty.
Find fraud fast
Data science can be a keen detective in the fight against identity theft, and the four step approach offered by a graph database provides a layered approach to uncovering fraud rings.
Convert a relational database of customer features such as account number, phone number, IP address and transactional data (such as the number of transactions, purchase volume etc.) into a graph database. ,
Synthetic fraud rings typically operate in large networks through a mix of real and fake identities shared across the network. Hence, a community detection algorithm can be effective in uncovering these networks.
A centrality algorithm like PageRank can then be used to determine nodes central to the fraud ring based on factors such as transaction volume, frequency of transactions and density of connections.
Successful isolation of a single fraud ring can help in the identification of other fraud rings based on similar patterns by using similarity algorithms such as Jaccard.
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Meet our experts
Client Partner, Financial Services
Senior consultant, Financial Services