Automated Risk Prioritization System Using Knowledge Base
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Solution Overview
Problem
Current risk prioritization systems rely on manual and subjective analyses, leading to time-consuming and inaccurate evaluations, making it difficult for organizations to effectively manage and prioritize risks while maintaining profitability.
Innovation Solution
An automated and objective risk prioritization system that utilizes a knowledge base to store and update risk data, allowing for precise analysis and re-evaluation of risk items based on likelihood, exposure, and mitigation costs, with a scoring system that adjusts for external and internal drivers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If manual and subjective risk analysis is used, then risk evaluation can be performed with simple systems, but the process becomes time-consuming and highly subjective
Solution Approach 1:
The system performs preliminary actions by pre-storing risk data, mitigation costs, and organizational information in a knowledge base before actual risk analysis is needed. This allows the automated risk prioritization system to quickly retrieve and process information without requiring complex real-time data collection, thus increasing automation while managing system complexity.
Solution Approach 2:
The patent introduces a knowledge base as an intermediary component that stores structured risk information, mitigation strategies, and organizational data. This intermediary layer enables the automated risk analysis system to access and process information systematically without requiring direct complex interactions between analysis components, thereby facilitating automation while controlling complexity.
2Productivity
If individual manual evaluation of each risk is performed, then detailed subjective analysis can be conducted, but significant time expenditure is required
Solution Approach 1:
The system creates copies of risk analysis frameworks and methodologies within the knowledge base, storing standardized approaches for evaluating different risk types. When new risks are identified, the system can retrieve and apply these pre-established analysis templates, enabling rapid automated evaluation without requiring time-consuming manual analysis for each individual risk while maintaining consistent detailed assessment quality.
Solution Approach 2:
The patent implements parameter changes by transitioning from subjective manual assessment parameters to objective quantitative parameters stored in the knowledge base. The system uses numerical data for risk probabilities, impacts, and mitigation costs, which can be automatically processed and compared, dramatically improving productivity while reducing the time required for risk evaluation compared to manual subjective analysis.
3Reliability
If comprehensive risk mitigation is implemented for all risks, then all potential damages can be addressed, but profitability is compromised due to costs
Solution Approach 1:
The system applies local quality by prioritizing risk mitigation resources based on specific risk characteristics and organizational context. The automated system evaluates each risk individually using stored data and assigns priority levels, enabling the organization to focus mitigation efforts and resources on the most critical risks rather than treating all risks equally, thus maintaining reliability for essential risks while controlling overall mitigation costs.
Solution Approach 2:
The patent implements partial action by enabling organizations to address only the most critical risks identified through automated prioritization rather than implementing comprehensive mitigation for all risks. The system calculates risk priorities based on quantitative analysis of potential damages, likelihoods, and mitigation costs, allowing organizations to selectively apply mitigation resources to high-priority risks, thereby maintaining adequate protection while preserving profitability.
Data Source
AI summary
Methods and systems for risk prioritization allow a user or organization to prioritize various risk items using a knowledge base. The knowledge base may be continually updated and/or improved based on newly available historical data (e.g., cost of mitigation, actual effects), new forecasts or predicative analyses (e.g., costs for mitigation), expert community consensus and/or new priority information. As new information is updated in the knowledge base, new and existing risk items may be evaluated and/or re-evaluated to determine a risk priority. Risk priority may be determined based on a remediation cost score as well as a risk score. The prioritization system may further develop recommendations for prioritizing and mitigating a risk item.