Automated Risk Model for Entity Data Processing
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Solution Overview
Problem
Determining relative risk levels for entities from diverse data sources is a time-consuming and error-prone process, especially when dealing with numerous entities and varying types of data inputs such as structured, unstructured, and third-party sources.
Innovation Solution
A system and method that utilize a back-end application computer server to access and retrieve electronic files from a data store, execute an automated risk model based on structured, unstructured, and external data elements, and transmit risk scores for entities, facilitating faster and more accurate risk assessment across different types of data inputs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual risk assessment is performed, then accuracy can be maintained through human judgment, but processing time increases and error rates increase
Solution Approach 1:
The patent replaces manual human assessment with an automated risk model that processes data elements from multiple sources. The system automatically retrieves structured data, unstructured data, and third-party data, then executes the risk model to generate scores, eliminating the need for manual analysis while maintaining consistency and reducing errors.
Solution Approach 2:
The system performs self-service by automatically retrieving and processing data from multiple sources without requiring manual intervention. The automated risk model independently analyzes data elements, retrieves information from data stores and external sources, and generates risk assessments on its own, freeing human resources for higher-value tasks.
2Measurement precision
If comprehensive data from multiple sources is collected, then assessment accuracy improves, but processing time and system complexity increase
Solution Approach 1:
The system performs preliminary actions by pre-configuring data retrieval parameters and pre-processing data elements before risk assessment. The automated risk model is pre-trained with algorithms that efficiently process multiple data types, and the system pre-establishes connections to data stores and external sources, enabling rapid comprehensive analysis without manual setup time.
Solution Approach 2:
The automated risk model serves multiple functions simultaneously: it retrieves structured data from internal data stores, processes unstructured data from various formats, incorporates third-party data sources, and generates risk scores. This multi-functional approach consolidates what would otherwise require multiple separate processes into a single efficient operation.
3Productivity
If automated risk modeling is implemented, then processing speed increases, but system complexity and initial setup requirements increase
Solution Approach 1:
The system segments the risk assessment process into distinct modular components: data retrieval modules for structured, unstructured, and third-party data; data processing modules that standardize different data formats; and the core automated risk model that generates scores. This segmentation allows each component to be independently optimized, maintained, and scaled without increasing overall system complexity.
Data Source
AI summary
Mediums, apparatus, computer program code, and means may be provided to evaluate relative risks based at least in part on source inputs received via a distributed communication network by an automated back-end application computer server. According to some embodiments, the server may access a data store containing electronic files associated with a set of entities to retrieve, for each of a plurality of the entities in the set of entities, electronic files associated with that entity. The server may also retrieve structured data elements, unstructured data elements, and external, third-party data elements for that entity. The server may then execute an automated risk model to assign a risk score to that entity based on the electronic files, the structured data elements, the unstructured data elements, and the external, third-party data elements for that entity and transmit indications of the risk scores for the plurality of entities.