DHS RFI: ICE Automated or Machine Learning System for Complexity Scoring Model of Applicant Pipeline

Notice ID: HSICE-10152020

“THIS IS A REQUEST FOR INFORMATION (RFI) to identify sources that can provide an automated system or machine-learning system which can provide a complexity score for each applicant to the US Immigration and Customs Enforcement (ICE), either federal or contractor, at the initial pre-employment decision to authorize personnel to enter on duty with ICE. ICE requests a platform where workload and staffing resources can be leveraged based on an applicant’s complexity score. This will allow for a predictability model for ICE’s federal and contractor applicant pipeline.”

“ICE is exploring methods to improve its operational efficiency beyond its current resources and available technology. Due to increased workloads, the adjudicative workforce in ICE has experienced bottlenecks and backlogs. As a result of these backlogs, predicting case complexity has become a focus point for improving the Personnel Security Unit’s efficiencies.”

“ICE is seeking an existing artificial intelligence or IT system to compile and analyze data included in the Questionnaire for National Security Positions (SF86) and the Questionnaire for Public Trust Positions (SF85/SF85P/SF85P-S) in order to visibly determine the complexity of the disclosed information within. Also included in this complexity rating is the inclusion of additional background checks (Credit report, fingerprint results, and the like). Further analysis to include polygraph results and background investigation reports of investigation will follow, with the same intent of identifying a complexity score.”

“Due to the large workload the Personnel Security Unit experiences, the need for automated technology to depict a complexity score will far exceed the current practice of reviewing the contents manually prior to adjudication. Additionally, having the ability to accumulate data reports for performance management, reporting, predictability, and timeliness will be a key requirement in this effort.”

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