Since the advent of the internet, we’ve been grappling with a trust problem. How do you do business with someone when you can’t meet them face-to-face? Over the past 30 years there have been numerous proposed solutions, including SSNs, credit databases and knowledge-based authentication.
But nothing has struck the right balance between security and user experience.
This guide covers the different historical approaches to the identity problem, risk modelling, new generation remote IDV, how automation can be powered by machine learning, and modern fraud techniques and how to detect them.
Read this whitepaper to learn about the modern approaches to identity verification and what you should consider when analyzing the various options you have as a business.
The report covers:
- Key modern approaches to remote identity verification
- How automation can help decrease operating costs
- Common attack vectors and how to detect them
- Biometric verification and how it can deter impersonation fraud
- Machine learning’s role in powering remote IDV
- The future of digital identity
