Rethinking Your Fraud Approach: 3rd-Party Data

Our last two installments of “Rethinking Your Fraud Approach” have focused on how to leverage the data you’ve already collected about your customers to mitigate fraud. Network analytics and stream analytics are certainly effective tactics to detect and prevent fraudulent activity. But now that you’re leveraging your own data, you should also consider how integrating third-party data can provide a bigger, more complete picture to make even better fraud and credit risk decisions. Through third-party data, you can connect your own customers’ data with data on fraud activity that’s happening outside your organization.

For example, connecting with data sources from providers that record, recognize and monitor associations between internet-connected devices and accounts can help you detect risky devices. Other providers analyze the attribute patterns associated with billions of online transactions, as well as millions of fraud and abuse reports, and expose these as up-to-date risk scores and other insights to help prevent fraud and abuse. Third-party bank transaction data can reveal behavioral patterns about existing customers that your internal data alone cannot—not to mention new prospective customers for which the only insight you may have is a simple credit score.

Of course, there’s no magic bullet that fits every organization—that is, there is no single third-party data source that provides your specific needs—so it makes sense to incorporate multiple data sources. However, data costs money, and each new data source represents an additional ongoing cost. That’s why it is important to test various combinations of data sources and weigh the relative predictive value of each one—for example, the number of fraudulent transactions or losses prevented—over its cost, before settling on the sources data that are right for you.

Once you have identified the most appropriate data sources, here comes the hard part. How do you integrate that third-party data into your systems and processes and make the data you need available in real-time? First you must negotiate contracts with each data provider, managing each as a separate vendor with its own terms of use and payment. Then, your team must appropriately label it so that it can be effectively identified. Finally, you must overcome the technological complexities required to integrate data from different sources and in different formats—setting up data connectors, buying ETL software, defining necessary data transformations, and so on.

You could fund a lengthy, costly project to accomplish these tasks, or you could leverage a technology partner that manages all the integration of third-party data for you. Enova Decisions has packaged up its 15+ years of fraud detection and prevention know-how into decisioning technology solutions that include pre-integrated, best-in-class data sources. With Enova Decisions, you can seamlessly integrate third-party data to make your fraud detection and prevention even more effective.

Coming up next we’ll examine Machine Learning and a Decision Management Service into your fraud strategy, or contact us today to get better fraud detection and prevention up-and-running quickly.

 

Enova Decisions

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Enova Decisions is an analytics and decision management technology company that was formed in 2016 to enable businesses in various industries, including financial services, healthcare, and telecommunications, to automate and optimize operational decisions, in real-time and at scale, through data, machine learning, and the cloud.