Advanced Common Controls Framework for Real-Time Enterprise Risk Validation
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Solution Overview
Problem
Current risk management programs are decentralized, static, and reactive, focusing on governance and process rather than real-time risk identification and quantification, which hampers boards' ability to make forward-looking risk mitigation decisions and investments due to manual assessments that do not keep pace with evolving enterprise threats and challenges.
Innovation Solution
A computerized advanced common controls framework (ACCF) that integrates risk identification, quantification, and mitigation engine delivery platform, combining multiple Control Frameworks (CFs) for real-time, enterprise-wide risk assessment and compliance reporting, utilizing AI and machine learning for proactive risk monitoring and management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual assessments and audits are used for risk identification, then governance and process focus is achieved, but real-time risk identification and quantification capability is lost
Solution Approach 1:
The patent replaces manual mechanical assessment processes with an automated computerized risk management system that continuously monitors risk indicators, substitutes human judgment with algorithmic analysis, and eliminates manual audit cycles in favor of automated real-time evaluation
Solution Approach 2:
The system transitions from periodic manual audits to continuous automated monitoring that operates without interruption, maintaining constant surveillance of risk factors and providing ongoing risk profiles rather than discrete snapshots in time
2Adaptability or versatility
If decentralized risk management programs are implemented, then organizational flexibility is improved, but centralized enterprise-wide risk view is lost
Solution Approach 1:
The system provides universal functionality by simultaneously serving decentralized local risk assessments and centralized enterprise-wide risk views, enabling the same platform to operate at multiple organizational levels without requiring separate systems for each function
3Stability of the object's composition
If static risk management programs are used, then process stability is maintained, but adaptability to evolving enterprise threats is reduced
Solution Approach 1:
The system transforms static risk management processes into dynamic, self-adjusting systems that automatically update risk profiles, modify monitoring parameters, and adapt assessment criteria in response to changing organizational conditions and emerging threats
4Reliability
If reactive risk management approaches are implemented, then response to identified risks is improved, but proactive risk identification capability is lost
Solution Approach 1:
The system performs preliminary actions by continuously monitoring risk indicators and identifying potential risks before they materialize, enabling proactive detection and assessment rather than waiting for risks to manifest and then responding reactively
Data Source
AI summary
In one aspect, a computerized advanced common controls framework (ACCF) method for all risk domains of cyber security as prescribed in each framework comprising: providing a risk identification, quantification, and mitigation engine delivery platform of an entity; obtaining a set of Control Frameworks (CFs) related to a risk identification, quantification, and mitigation engine delivery of the entity; creating an ACCF from the set of CFs, wherein the ACCF comprises a collection of CFs that when combined enable a commingling of individual controls; and with the risk identification, quantification, and mitigation engine delivery platform of an entity, applying the ACCF to perform an operational and compliance risk reporting.


