November 25th, 2020

Improve Outbound Dialing with This Fraud Prevention Technique

It is increasingly difficult to contact consumers via phone. Some consumers don’t answer unknown calls. Those who do are inundated with robocalls. Right-party-contact (RPC) rates, a key metric for professional call centers, have been decreasing for a few years. It is causing strain on functions that rely on the phone channel, including debt collections, healthcare notifications, and utility alerting. As COVID-19 has disrupted the economy for most of the year, many believe a large wave of collections is on the horizon. If consumers are not answering their phones now, how can debt collectors arrange for payment next year?

To combat depressed RPC rates, many firms have been investing in verification and modeling to help confirm that the intended call recipient is actually the person the outbound dialer wants to reach—and to determine which phone number to call and when to call it. As Neustar has developed several offerings in this space, we took a fresh look at this problem from the perspective of other business functions.

Many organizations consider risk, marketing, security, and telecommunications to be worlds apart. Neustar sees them as different parts of the same whole, all focused on consumer identity.

For example, a principle for combating synthetic identity fraud is useful for debt collection. Fraudsters synthesize identities from real identity data to open and drain lines of credit before disappearing. The mix of data—usually a combination of a social security number, phone number, physical address, or email address—can bypass fraud-detection tools. The scam is growing quickly right now.

Solutions used to identify synthetic identities depend on overlaying multiple data sources and then applying machine learning to detect anomalies. The signals on how consumers use their offline (address/phone/social security number) and online (email/device ID/IP address) personally identifiable information (PII) have become a critical element in detecting synthetic identities. Fraud prevention practitioners refer to this usage of PII as “signs of life.”

A synthetic identity will likely have anomalous behavior that diverges noticeably from normal signs of life. A legitimate identity should not exhibit such anomalies.

Signs of life help predict right-party contacts on outbound calls and texts. Such signs include a phone actively making calls or texts, other activity on a phone carrier network, or the phone’s participation in everyday transactions. These signs tend to be unique to each provider. They are not readily available.

This aligns with collectors’ experiences. If a consumer has a landline from their cable provider that they never use, they are unlikely to answer calls or texts to that phone number. The phone is active and linked to the consumer, but it is not used. The consumer is more contactable on a phone number that exhibits more signs of life.

By combining signs of life with proven identity verification solutions, outbound dialers can improve RPC rates by 20 percent so they can make more calls that count. Devices that consumers use in their everyday life are more contactable.

Take the next step to improve outbound dialing

The search for signs of life in a CRM database begins with an analysis of past dialing behavior. Some preliminary insights of value will probably appear in larger databases. However, a single database will always be limited in breadth and depth. Greater efficiency and effectiveness comes from tapping insights that span the entire telephony ecosystem. That’s where Neustar can help.

Neustar provides predictive phone behavior insights not found anywhere else by leveraging unique relationships with telecom providers, powering over 90 percent of caller ID in the U.S. Unique identity and device behavior insights from these relationships enable outbound communicators to reach consumers more efficiently and effectively with Neustar Phone Behavior Intelligence. The solution not only offers a more reliable way to correct and complete contact data, but also provides critical consumer phone behavior intelligence—including signs of life, the best phone number to use for each consumer, and the best time to call—to increase RPC rates 33 percent on average.

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