Company Filing History:
Years Active: 2020
Title: Paul Dolby Zaich: Innovator in Continuous Background Check Monitoring
Introduction
Paul Dolby Zaich is an accomplished inventor based in San Francisco, CA. He is known for his innovative approach to continuous background check monitoring, which enhances the security and reliability of candidate evaluations. With a focus on technology and data management, Zaich has made significant contributions to the field of background checks.
Latest Patents
Zaich holds a patent for a system that enables continuous background check monitoring. This system allows for the ongoing electronic monitoring of data sources related to a candidate's background. It identifies any changes or updates to the candidate's information until they are no longer enrolled in the program. The process includes an identity matching mechanism to assess the probability that any new record pertains to the candidate. If the probability falls below a certain threshold, or if a manual review is warranted, the system triggers a manual review of the record. This innovative approach ensures that any relevant changes are promptly addressed, enhancing the overall integrity of the background check process.
Career Highlights
Zaich is currently employed at Checkr, Inc., a company that specializes in background check technology. His work at Checkr has allowed him to apply his inventive ideas in a practical setting, contributing to the development of advanced solutions for background screening.
Collaborations
Some of his notable coworkers include Benjamin Jon Jacobson and Jason Scott Dougherty. Their collaboration within Checkr, Inc. fosters an environment of innovation and creativity, driving the company forward in the background check industry.
Conclusion
Paul Dolby Zaich is a notable inventor whose work in continuous background check monitoring exemplifies the intersection of technology and security. His contributions to Checkr, Inc. and the field of background checks highlight the importance of innovation in enhancing candidate evaluation processes.