Automated Data Processing System for Legacy Insurance Integration
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Legacy systems in various industries, such as insurance, store data in non-standard formats, making it difficult for organizations to share information across incompatible systems, leading to challenges in collaboration and data integration.
Innovation Solution
An automated data processing system that ingests data from disparate legacy systems, translates it into standardized formats using product rules, case rules, and workflows, and exports it in various formats, allowing seamless data sharing without requiring system updates, facilitated by an interactive API and versioning for tracking.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If data is stored in legacy systems with non-standard formats, then each organization can maintain its own data processing steps and formats, but information cannot be easily shared outside the organization
Solution Approach 1:
The patent introduces an intermediary translation layer that sits between legacy systems with non-standard formats and external systems. This translation layer automatically converts proprietary data formats into standardized formats (such as HL7, XML, or JSON) without requiring changes to the original legacy systems, thereby enabling data sharing while maintaining compatibility with existing infrastructure.
Solution Approach 2:
The system dynamically changes data format parameters by detecting the source system's proprietary format and automatically transforming it into a standardized format. This involves modifying data structure parameters, encoding schemes, and protocol parameters to ensure interoperability across different legacy systems while preserving the original data meaning and integrity.
2Loss of information
If a platform ingests data from many different legacy systems with different formats and schema, then data sharing capability improves, but system complexity increases
Solution Approach 1:
The patent implements a universal data ingestion platform that can handle multiple legacy systems, data formats, and schema types through a single standardized interface. The system provides multi-functional capabilities including automatic format detection, schema validation, data transformation, and error handling, allowing one platform to serve numerous different data sources without requiring separate integration solutions for each system.
Solution Approach 2:
The complex data integration process is segmented into distinct modular components: data ingestion modules for different legacy systems, schema validation modules, transformation rules engines, and output generation modules. Each component handles a specific aspect of the integration process, making the overall system more manageable and maintainable despite handling diverse data formats and schema.
3Productivity
If automated transformation is implemented to convert data from legacy formats to standardized formats, then data processing efficiency improves, but automation extent requires sophisticated algorithms
Solution Approach 1:
The system performs preliminary actions by pre-defining transformation rules, mapping schemas, and validation criteria for common legacy data formats. These pre-configured templates and rules are stored in a knowledge base, allowing the automated transformation process to quickly match incoming data against known patterns and apply appropriate transformations without requiring complex real-time decision-making algorithms.
Solution Approach 2:
The automated transformation system incorporates feedback mechanisms where transformation results are validated against expected schemas and business rules. Error feedback loops automatically detect and correct common transformation issues, log anomalies for review, and continuously improve transformation accuracy based on accumulated experience data, thereby enhancing productivity while managing automation sophistication.
Data Source
AI summary
A system and method process data transformation between disparate legacy systems of providers by maintaining databases of schema, rules and work flows applicable to the providers and allowing administrators to interactively customize data transformations from unique versions of data sets in one data type and format to other unique versions in other data types and formats in an automated manner, based on schema, rules and workflows. The process is controlled though an interactive user interface.