Lines of code with magnifying glass
The truth behind financial identity crimes in the U.S.

Research from Aite Group shows that 43% of U.S. consumers experienced financial identity theft – application fraud in their name or account takeover (ATO) – in the past two years1.

These attack patterns are a concern for consumers and for financial executives and only part of the ever-changing landscape. What is the truth behind these types of fraud and what does this mean for financial institutions – today and tomorrow? Join industry thought leaders from Aite Group and Early Warning® and get an exclusive first look at the key takeaways from the latest Aite report, Financial Identity Crimes in the U.S.: The Stark Reality.

During this webinar, you will learn:

  • How modern fraudsters are attacking consumers and the harsh reality it puts on those impacted
  • Why the sum of these problems are much greater than the individual attacks
  • Practical ideas for managing and mitigating the risk for your business and your customers

1Financial Identity Crimes in the U.S.: The Stark Reality. Aite Group, July 2021.

Watch the Webinar
Blog hero image
Blog Article

Picture this: a fraudster writes a check for $5,000 from his account at a credit union and walks over to his local branch of a nationwide bank, depositing the check by scanning it in at the ATM. It’s a large check, so the bank

An infographic with icons in blue tones and red accents showcases Early Warning’s National Shared DatabaseSM resource in the middle with an icon made up of three stacked rectangles with dots it them. The 4 Vs of big data analytics in banking surround it: “Volume” in the top left corner shows two stacked cylinders with the right one being taller ; “Velocity” in the top right corner has a stopwatch icon with an arrow that gives it a sense of motion; “Value” in the bottom left corner shows an outstretched hand

When it comes to mitigating risk, reducing fraud and reaching growth goals, Early Warning® enables banks and credit unions to leverage big data analytics through a “give-to-get” model with the National Shared DatabaseSM resource.