Machine Learning and Gesture Biometrics to secure online assessments: 2-year Case Study

Track: Security, Records and Data Management

Session Number: 6143
Date: Thu, Nov 21st, 2019
Time: 9:30 AM - 10:30 AM

Description:

Case Study: Online courses need to be secure. We wanted flexibility and verifiability. Is this possible?  How did Nationwide Mortgage Licensing System (NMLS) select and use Gesture Biometrics and machine learning for ID Verification of Mortgage Originators in the USA? Come learn what impact this has had on security, the course content providers and the industry.  

NMLS is the system of licensure for state-licensed individuals and mortgage companies used by all states.

 

Longer Description:

Case Study: How did Nationwide Mortgage Licensing System (NMLS) select and use Gesture Biometrics for ID Verification of Mortgage Originators in the USA? NMLS is the system of licensure for state-licensed individuals and mortgage companies used by all states, the District of Columbia, Puerto Rico, Guam, and the U.S. Virgin Islands. During this session we’ll explain the role Gesture Biometrics and the impact it has on the mortgage industry and for the for the 125,000 state-licensed individuals and 35 course providers who are using it.  Also to be discussed: Gesture Biometrics and how it compares to other biometrics? How does machine learning help uncover fraudulent access? Presentation will address key learnings, suggestions and data that reveals how well the ID verification is working after 2+ years.  

Session Type: Concurrent Session

Session Type: Concurrent Session