Thwarting True Name Fraud Like Never Before
Identity theft impacts over 15 million US consumers a year, at a cost to businesses of over $50 billion annually. Many of us are worried about our identities being stolen. Can more be done to protect the consumer? Absolutely. More also needs to be done to protect businesses from fraud and theft based on identity misuse.
True-name fraud analytics, packaged together with identity data, help provide maximum protection against fraud based on identity misuse. We have identified four data sources that, when combined together, can effectively predict true-name identity fraud:
1) A business’s own data identifying location, time, and channel of past fraudulent incidents
2) credit data for the consumer
3) collections data for the consumer
4) other proprietary information, like fraud consortium data
These data sources can be particularly useful in screening for suspicious activity, and predicting identity fraud. Technology helps streamline the data collection and integration process for feeding this data into the fraud model, and tracking the effectiveness of the analytics. Most importantly, when the model identifies suspicious activity, authentication software can deploy out-of-wallet questions against the suspicious inquiries, automating the process of verifying whether a consumer is who they say they are in real-time. Working together, the analytics and technology thwart fraudsters like never before.
A fraud validation will determine the lift you can get from deploying a true-name fraud solution. If you want to learn more about these predictive data sources, analytics, and fraud mitigation solutions, let us know.
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