Clara Accuardi, Manager of Reporting and Admin, introduces us to the Business Rule Editor, an iovation tool that gives our subscribers un-matched control over their fraud and risk management implementation.

Explore your data and configure your service to investigate transactions, explore hidden relationships, drill down into individual attributes, and search across the history to find trends and patterns of fraudsters. Feed the evidence of confirmed fraud back into the system, and create business rules to flag fraudulent behaviors to stop them from continuing.

See https://www.iovation.com/fraudforce-fraud-detection-prevention to learn all about FraudForce Device-Based Reputation and schedule a demo today.

Read the Full Transcript

Clara Accuardi:
I'm Clara Accuardi. I'm a development manager here at Iovation and I have the pleasure of working with the team that develops our intelligence on our application. Our intelligence center was really designed as a one-stop shopping experience for our customers to be able to explore their data and configure their service. So from the application, you can investigate individual transactions, accounts, devices. You can explore the hidden relationships between them. You can drill down into individual attributes and search across the history to find trends in the data and try to identify patterns of fraudsters. You can also provide feedback directly into the system about evidence that you find of bad behavior, confirmed fraud. And then you can also take the learnings from your investigations about the activities of fraudsters to create business rules that help stop that fraud from coming back.

Clara Accuardi:
As an example, you could take an account that you know has confirms account takeover history and go look at the transactions associated with that account to try to better understand what happened. And you might be able to identify the transaction where the account takeover occurred and then drill down into any anomalies or attributes from that transaction that seems out of the norm. You can then take those attributes and do further investigation across your whole set of data to see if there are in fact, trends that correlate highly to fraud. Once you've identified those, say for example particular ISP that seems unusual and often correlates to account takeover, you could go and create a new business rule to look specifically for any transactions coming from that ISP and stop them going forward.

Share