Automated Risk Relationship Transaction Analysis
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Solution Overview
Problem
Manual analysis of risk relationships and resource allocations across multiple systems and entities is complex, time-consuming, and prone to errors, especially when dealing with numerous inter-related factors.
Innovation Solution
A risk relationship transaction automation tool that uses a back-end application server to retrieve electronic records, execute predictive models and business rules, and provide a graphical user interface for faster and more accurate resource allocation decisions, leveraging machine learning and artificial intelligence.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual analysis methods are used to review risk relationship transactions, then human judgment and flexibility are maintained, but the process becomes time-consuming and error-prone
Solution Approach 1:
The patent replaces manual mechanical review processes with an automated computer-based system that retrieves transaction data, executes predictive models and business rules, and generates likelihood scores automatically. This substitution eliminates human error and acceleration of the review process while maintaining consistent application of analysis criteria.
Solution Approach 2:
The system enables self-service automation where the computer server independently retrieves data, executes models, and generates analysis results without requiring manual intervention at each step. The automated workflow processes transactions through predictive models and business rules autonomously, reducing both time and potential for human error.
2Reliability
If comprehensive data from multiple systems and entities is analyzed, then more complete risk assessment is achieved, but the complexity of the analysis process increases
Solution Approach 1:
The patent segments the complex analysis process into distinct modular components: data retrieval from multiple systems, execution of predictive models, application of business rules, and generation of likelihood scores. Each module handles specific aspects of the analysis independently, making the overall complex process manageable and maintainable while comprehensively processing data from multiple sources.
Solution Approach 2:
The system implements a universal platform that can analyze transactions across multiple systems and entities through a single integrated architecture. The computer server executes the same predictive models and business rules regardless of the data source, providing consistent comprehensive risk assessment across diverse data sources without proportionally increasing complexity.
3Productivity
If traditional manual methods are used for resource allocation decisions, then human oversight is maintained, but productivity and speed of decision-making decrease
Solution Approach 1:
The patent implements continuous automated processing where the system continuously retrieves transactions, executes predictive models, and generates likelihood scores without interruption. This continuous automated action eliminates the intermittent nature of manual review and significantly increases productivity while reducing the time required for resource allocation decisions.
Solution Approach 2:
The system replaces manual decision-making mechanics with automated computer-based execution of predictive models and business rules. This substitution accelerates the decision-making process while maintaining consistent application of allocation criteria across all transactions.
Data Source
AI summary
A system to provide a risk relationship transaction automation tool via a back-end application computer server of an enterprise. The system may include a risk relationship data store that contains electronic records representing transactions associated with requested resource allocations between the enterprise and a plurality of entities. The server may receive an indication of a selected requested resource allocation transaction and retrieve, from the risk relationship data store, the electronic record associated with the selected requested resource allocation transaction. The server may then execute a medical code decision model. According to some embodiments, the system may also support a graphical interactive user interface display via a distributed communication network, the interactive user interface display providing resource allocation transaction data.


