Change Convergence Risk Mitigation via Temporal Event Aggregation
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Solution Overview
Problem
Current risk assessment methods for businesses, particularly financial institutions, are inadequate in effectively identifying and mitigating change convergence risks associated with multiple events occurring across various time periods.
Innovation Solution
A system comprising a processor and memory with a risk mitigation module that receives event information, determines event risk scores, aggregates these scores to assess risk levels across time periods, identifies risk mitigation events, and recommends altering their timing to reduce overall risk levels, thereby providing a proactive approach to risk management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional risk assessment methods are used to evaluate individual events, then the assessment process is simple, but the system cannot identify change convergence risks associated with multiple events occurring across various time periods
Solution Approach 1:
The system segments risk assessment into individual event evaluations and aggregate convergence analysis. Each event is assessed separately for its risk score, then combined to evaluate overall convergence risk across time periods, enabling precise multi-event risk measurement without overwhelming system complexity
Solution Approach 2:
The system adds a temporal dimension to risk assessment by evaluating events across multiple time periods and aggregating risk scores chronologically. This dimensional expansion allows identification of convergence patterns that traditional single-point assessments cannot detect, improving measurement precision while maintaining manageable complexity through structured temporal analysis
2Reliability
If the system aggregates event risk scores across multiple time periods to determine risk levels, then change convergence risks are identified, but the complexity of processing and analyzing event data increases
Solution Approach 1:
The system performs preliminary risk score determination for each individual event before aggregation. By pre-calculating and storing risk scores for discrete events, the system reduces the complexity of real-time aggregate analysis while ensuring reliable risk mitigation through comprehensive multi-event evaluation across time periods
Solution Approach 2:
The system uses event risk scores as an intermediary metric between individual event characteristics and overall convergence risk assessment. These standardized scores serve as a mediator that simplifies the aggregation process, enabling reliable risk level determination without directly processing complex raw event data across multiple time periods
3Reliability
If businesses react to risks after events occur, then the response is straightforward, but the ability to proactively mitigate change convergence risks is reduced
Solution Approach 1:
The system performs preliminary identification of high-risk time periods by aggregating event risk scores before events actually occur. This advance risk visualization enables businesses to proactively implement mitigation strategies during planned interventions, improving operational stability while reducing the time needed for risk response compared to reactive approaches
Solution Approach 2:
The system provides feedback by identifying specific time periods where planned interventions would result in unacceptable risk levels. This feedback mechanism guides businesses to reschedule events to lower-risk periods, enabling proactive risk mitigation that enhances operational stability without requiring complex real-time decision-making during event execution
Data Source
AI summary
Disclosed is a change convergence risk mitigation system. The change convergence risk mitigation system typically includes a processor, a memory, and a risk mitigation module stored in the memory. The change convergence risk mitigation system is typically configured for: receiving information associated with a plurality of events; determining an event risk score for each of the plurality of events; aggregating the event risk scores of the plurality of events and, based on the event risk scores, determining a risk level for each of the plurality of time periods; identifying a risk mitigation event; determining a risk mitigation time period from the plurality of time periods such that the risk mitigation time period would not have a predefined level if the risk mitigation event occurred during the risk mitigation time period; and providing a recommendation that the risk mitigation event occur during the risk mitigation time period.