Cognitive Permit Assessment Prediction System
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Solution Overview
Problem
The process of preparing and submitting a work permit application is time-consuming and costly, with uncertainty about approval, leading to potential delays and penalties due to the lack of predictive tools for determining the likelihood of success.
Innovation Solution
A prediction system that utilizes a computing system to analyze discrete applicant data inputs and supporting documents against weighted criteria from previous profiles and external sentiment analysis to determine an overall probability of success, incorporating machine learning and natural language processing to assess the likelihood of approval.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a work permit application is prepared and submitted without predictive assessment, then the application process can be completed, but there is uncertainty about approval leading to potential delays and penalties
Solution Approach 1:
The system performs preliminary cognitive assessment of the work permit application before official submission by analyzing application content against governing authority criteria, historical data, and external factors to predict approval likelihood, allowing applicants to address issues before submission
Solution Approach 2:
The system provides feedback on the predicted probability of approval and identifies specific content elements that may lead to refusal, enabling applicants to modify their applications to improve approval chances before official submission
2Reliability
If comprehensive documents and supporting materials are prepared for work permit application, then the application completeness is improved, but the time investment and preparation cost increase significantly
Solution Approach 1:
The system performs preliminary analysis of application documents and supporting materials to assess completeness and quality before official submission, identifying missing or insufficient elements that need to be addressed
Solution Approach 2:
The system replaces manual review of application documents by cognitive computing technology that automatically analyzes application content, supporting documents, and criteria to assess completeness and predict approval likelihood
3Measurement precision
If manual review and assessment of work permit applications is performed, then detailed evaluation can be conducted, but the process is time-consuming and lacks predictive capability
Solution Approach 1:
The system replaces manual review processes with cognitive computing technology including natural language processing, machine learning models, and sentiment analysis to automatically evaluate applications with both precision and speed
Solution Approach 2:
The system enables self-assessment of application quality by automatically analyzing application content against criteria and providing predicted approval probability, allowing applicants to evaluate their own applications without manual review
Data Source
AI summary
A prediction system and method may include receiving a plurality of discrete applicant data inputs and a supporting document, the applicant data inputs and the supporting document being relevant to a permit application, providing a first predicted probability of approval of the permit application by comparing the discrete applicant data inputs with weighted criteria of previous applicant profiles stored in a first database, analyzing the supporting document to determine a second predicted probability of approval of the permit application by comparing the supporting document with previous applicant supporting documents stored in a second database, performing a sentiment analysis on external publically available information relevant to at least one aspect of the permit application to determine an impact score on the permit application, and determining an overall probability of success based on the first predicted probability, the second predicted probability, and the impact score.