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Imperium Supercharges Industry-Leading Anti-Fraud Solution

Upgraded RelevantID® tool provides powerful 360-degree response to escalating problem of survey dupes and frauds

Data quality solutions specialist Imperium (www.imperium.com) today announced the release of a significantly upgraded version of its flagship ID-validation tool RelevantID®.

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This major release is designed to help market research and panel organizations combat the rise of highly sophisticated synthetic identity frauds that are becoming increasingly difficult to catch using conventional fraud-detection models.

From today, the company’s powerful fraud-blocking tool Fraudience® will be integrated into RelevantID® as standard. New and existing clients will now automatically enjoy access to Fraudience®, which monitors respondents’ behavior patterns against a proprietary research-based algorithm, quickly identifying potentially fraudulent respondents.

New RelevantID® additionally includes FraudProbabilityScore, a machine-learning model that assesses passive and behavioral data, returning an extremely precise fraud assessment that detects fraud, bots, and jumpers/ghost completes in surveys.

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“We’re confident that RelevantID® offers a genuinely multi-level approach to fraud detection, combining passive machine data with behavioral data to provide a detailed picture of respondents’ fraud potential, while fully complying with stringent privacy laws like GDPR,” said Tim McCarthy, General Manager, Imperium.

McCarthy adds: “Businesses rely on us to consistently deliver top-level tools that assure data quality. Since supercharging RelevantID® with Fraudience® and FraudProbabilityScore, we’re seeing fraud capture scores skyrocket—on average by more than 5x—from 2.5% to 13.8%. Because we’re using a machine-learning model, our tools are recognizing new behavior patterns every day, making it easier to stay ahead of determined fraudsters.”

The announcement chimes with the findings in a report on the subject of synthetic identity fraud published this year by the Federal Reserve. The authors of the paper referred to an ID Analytics study estimating that traditional fraud-detection models lacked effectiveness in 85-95 percent of likely synthetic identity frauds.

The extensive link-analysis process that’s a core part of Imperium’s survey data quality solutions mirrors Federal Reserve recommendations that businesses adopt a ‘layered fraud mitigation approach’ incorporating ‘manual and technological data analysis’ to combat the most sophisticated fraud technologies.

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