Wednesday, May 1, 2019

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How machine learning can help organizations catch identity fraud
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An all-digital world amplifies the classic threats of service misuse, identity impersonation and money laundering. Thankfully, artificial intelligence and machine learning techniques have finally matured—and with them, we can improve online identity management. Download this white paper to learn more.
Why traditional identity verification methods are no longer enough
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In an all-digital world, ID theft is everywhere. With the data of hundreds of millions of consumers compromised, personally identifiable information can no longer be the cornerstone of online identity verification (IDV) methods. Read on to explore why traditional IDV solutions are failing to defeat identity fraud and how a hybrid IDV can help.
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Forgeries. Imposters. Counterfeit documents. You can't afford to let fake identities slip through the cracks and put your company—and your customers—at risk. Learn how to detect the 7 most common types of ID fraud, and how advanced identity verification technology can turn things around.
3 ways to combat identity fraud
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There are countless ways fraudsters can slip through the net. That's why organizations need to be able to recognize and analyze all of them to keep ahead competitively. Download this white paper for 3 simple steps to combat identity fraud today.
How to detect identity fraud and verify your users
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A user's name, date of birth, and address are all data points that can be easily stolen to create fake bank accounts. But, fraudsters committing these crimes can't get past all security tools. Download this case study to find out how Revolut used Onfido to successfully verify users and keep their customer accounts secure.
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