AI Automation for Legacy Administrative Processes Using Unified Data
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Solution Overview
Problem
Current administrative systems, such as insurance policy administration systems, rely on legacy technologies with siloed and unscalable data structures, leading to error-prone and difficult-to-scale manual processes.
Innovation Solution
The implementation of AI-enabled systems that transform core business processes by generating shared database structures and automating processes using AI and RPA techniques, thereby creating unified data structures and improving operational efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual processes are used in legacy administrative systems, then system complexity is reduced and ease of operation is maintained, but productivity is low and error rates are high
Solution Approach 1:
The system enables self-service automation where AI models automatically perform administrative tasks such as document processing, data extraction, and decision-making without human intervention. The automated system serves itself by learning from historical data and executing processes independently, thereby increasing productivity while managing complexity through standardized AI components.
Solution Approach 2:
Manual mechanical processes are replaced with intelligent automated systems using AI and machine learning technologies. The patent substitutes human-operated manual workflows with automated AI models that can process documents, extract information, and make decisions, thereby significantly improving productivity while the complexity is managed through modular AI architecture.
2Reliability
If manual processes are used in legacy administrative systems, then ease of operation is maintained, but reliability is low due to error-prone manual operations
Solution Approach 1:
The system implements feedback mechanisms where AI models continuously learn from processed data and improve their accuracy over time. The system provides feedback loops that allow automated processes to refine their performance, reduce errors, and increase reliability. Historical data is used to train models that progressively improve their decision-making accuracy.
Solution Approach 2:
The system creates standardized digital copies and templates for recurring administrative tasks. By copying proven successful process patterns into automated AI workflows, the system eliminates manual errors while maintaining operational simplicity through standardized, repeatable processes that can be easily replicated across different tasks.
3Adaptability or versatility
If legacy siloed data structures are used, then device complexity is low, but adaptability is poor and processes are difficult to scale
Solution Approach 1:
The patent implements universal data structures and standardized schemas that can serve multiple functions across different administrative processes. The unified data model allows the same data structure to support various AI tasks including document processing, data extraction, analytics, and decision-making, thereby improving adaptability and scalability without proportionally increasing complexity.
Solution Approach 2:
The system segments data processing into modular AI components that can independently handle specific tasks such as document classification, information extraction, and validation. This segmentation allows each component to work with standardized data structures while maintaining independence, improving scalability by allowing individual modules to be added or modified without redesigning the entire system.
Data Source
AI summary
Methods, systems and apparatuses, including computer programs encoded on computer storage media, are provided for converting legacy administration systems by transforming core business processes identified from the legacy administration systems and building unified data structures among the integrated administration systems within an organization. The legacy systems are analyzed to determine common and/or needed system configuration, including common core business processes and specific processes, data structures, data definitions, calculation modules, product rules, etc. The legacy systems are then transformed by converting core business processes one by one and additional specific processes. A unified data structure, such as a customer-centralized data model, is created to be used by all administrative systems within an organization to improve operation efficiency, result accuracy, and process transparency.