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The Challenge

A top 10 financial institution observed that a high manual review rate for new customer applications was cutting into account opening numbers and lifetime value metrics. The organization experienced decreasing applicant lifetime values and the hard costs associated with conducting a high volume of manual reviews. A reduction in manual review could prevent ~3,000 accounts per month from abandoning the current application process.

The financial institution used verification data for the application-approval process but was not using IP address attributes. The goal was to decrease manual review while maintaining or lowering the observed fraud rates on approved applications.

The Neustar Solution

Neustar conducted a 12-week pilot of Digital Identity Risk to identify which applications should be flagged for manual review and which could be approved through a frictionless process. In real time, the organization recoded results to understand how Digital Identity Risk could impact application process. Using a host of online, offline, and device-based elements—including IP, browsing behavior, phone activity, and the connections between digital footprints and people or households—Neustar corroborated applicants’ digital information against authoritative offline and online consumer data. If Neustar scored an application as low-risk, the customer would not review the application manually and risk frustrating the applicant. If the application scored as high-risk, the customer would route the application into a manual review for additional verification steps.

The Outcome

The pilot showed Neustar Digital Identity Risk could positively affect two points of the application process:

1. Applications that were manually reviewed and incurred no fraud - Neustar reduced manual review by 35%, saving the customer operational cost and decreasing application attrition due to friction-filled experiences.

2. Applications that were approved through a frictionless process and incurred fraud (“false negatives”) - Neustar identified high-risk signals on 5% of auto-approvals, which would eliminate 50% of the total incurred fraud from this population

Test results showed overwhelmingly positive results for both fraud prevention and operational efficiency gains. By introducing Neustar data into existing checks, the financial institution could reduce manual review populations by 35% while reducing incurred fraud by 11%.

Financial institutions take pride in providing great service to their customers, and reductions in manual review will lead to increased customer satisfaction in new account openings. By accurately identifying and segmenting low-risk applicants from high-risk applicants, incoming potential customers can be treated as valued individuals, rather than as potential fraudsters.

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