Remote Attribute Definition System for Credit Data Automation
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Solution Overview
Problem
Current systems for credit and marketing data retrieval from credit bureaus are inefficient, requiring manual programming by bureau staff, leading to increased costs, delays, and compliance issues due to inconsistent attribute definitions across different bureaus, and lack of automation for real-time data inquiries and decision-making.
Innovation Solution
A system that allows users to define and manage data queries and attributes for credit and risk decisions, enabling automated data searches and decision-making within credit bureaus, while minimizing the transfer of sensitive data, and providing tools for tracking query performance and compliance with regulations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual programming by bureau staff is used to define data inquiry attributes, then data retrieval can be performed, but time consumption and costs increase
Solution Approach 1:
The system performs preliminary actions by pre-defining and storing attribute definitions, decision rules, and data inquiry parameters in a database before actual data retrieval operations. Users can create and save attribute templates that can be reused across multiple inquiries, eliminating the need for manual programming each time a data retrieval is performed.
Solution Approach 2:
The system creates and stores copies of attribute definitions, decision rules, and inquiry parameters in a centralized database. These copied definitions can be retrieved and reused for subsequent data inquiries, eliminating redundant manual programming work while maintaining consistency across different bureau staff operations.
2Productivity
If manual attribute programming is performed at each bureau, then data inquiries can be made, but attribute consistency across different bureaus deteriorates
Solution Approach 1:
The system creates a universal attribute definition database that serves multiple bureaus and data providers simultaneously. The standardized attribute definitions, decision rules, and inquiry parameters stored in this database can be accessed and applied across different bureaus, ensuring consistent attribute interpretation and data retrieval capabilities while maintaining bureau-specific operational flexibility.
Solution Approach 2:
The system enforces homogeneity by requiring all attribute definitions, decision rules, and data inquiry parameters to follow standardized formats and structures stored in the centralized database. This standardization ensures that the same attribute definitions are applied consistently across different bureaus and data providers, eliminating variations that arise from manual programming by different bureau staff.
3Reliability
If bureau staff program attributes manually, then data retrieval is possible, but business flexibility and speed of response to market changes decrease
Solution Approach 1:
The system introduces dynamics by enabling users to easily modify, update, and adapt attribute definitions, decision rules, and inquiry parameters in the database in response to changing business conditions. The system allows for dynamic creation of new attribute templates, modification of existing ones, and rapid deployment of updated definitions across all bureaus without requiring manual reprogramming, thus maintaining reliability while enhancing adaptability to market changes.
4Productivity
If automated systems are implemented for data inquiries, then efficiency improves, but system complexity increases
Solution Approach 1:
The system introduces an intermediary layer - a centralized database storing standardized attribute definitions, decision rules, and inquiry parameters - that mediates between users and the complex data retrieval operations. This intermediary database abstracts the complexity of automated data inquiries, allowing users to efficiently perform sophisticated queries without directly managing the underlying system complexity, thus improving productivity while containing perceived complexity.
Data Source
AI summary
A system of the invention comprises a design module, execution engine, and performance management module. A first computer hosts the design module which enables a user to define attributes, queries, and decision rules transmitted to the execution engine hosted on a second computer remote to the first computer. The second computer can be located at a credit bureau, credit reporting agency, or other data provider. The second computer runs the execution engine to query a data repository with the user-defined attributes and queries, and applies the user-defined decision rules to produce result data transmitted to a third computer hosting the performance management module for monitoring performance of a benefit or offering made with the result data and the corresponding attributes, queries, and decision rules that generated the result data.