Merchant Credit Approval Integration With Cached Data Normalization
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Solution Overview
Problem
Merchant credit applications require extensive data retrieval from various sources, often involving non-standardized formats and frequent changes, leading to inefficiencies and high network latency, increased I/O operations, and security risks due to multiple external system interactions.
Innovation Solution
A centralized integration service using a volatility-based decomposition architecture that standardizes and consolidates data from multiple sources, reducing the need for multiple external interactions and minimizing network latency and security vulnerabilities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If multiple external data sources are queried for merchant credit applications, then data completeness is improved, but network latency and I/O operations increase
Solution Approach 1:
The system performs preliminary actions by caching external data sources and their responses in advance. When a merchant credit application is processed, the system checks the cache first to retrieve data without performing new external I/O operations, thus reducing network latency while maintaining data completeness through pre-fetched information.
Solution Approach 2:
The system creates copies of external data source responses and stores them in a cache. Instead of repeatedly querying external sources for the same data, the system uses cached copies, significantly reducing network latency and I/O operations while preserving complete merchant credit information.
2Measurement precision
If multiple external systems are interacted with for data retrieval, then data accuracy is improved, but security risks increase
Solution Approach 1:
The system introduces a cache as an intermediary layer between the merchant credit application processing and external data sources. This intermediary stores validated data copies, allowing the system to maintain data accuracy by using verified external sources while reducing security risks by minimizing direct interactions with external systems.
3Loss of information
If data formats from external sources are maintained as-is, then data fidelity is improved, but system complexity increases
Solution Approach 1:
The system applies homogeneity by standardizing data formats from various external sources into a unified cache structure. Instead of maintaining disparate data formats as-is, the system transforms all external data into a consistent format, reducing system complexity while preserving data fidelity through structured normalization.
Data Source
AI summary
The present disclosure comprises systems, methods, and computer readable media that allows processing of merchant credit applications. An integration service is provided herein that retrieves external information regarding the merchant credit application. The integration service provides for normalizing an external information and mapping it to the businesses and entities within its own database. Additionally, the integration service is able to compile a dataset for a decision service to efficiently analyze the merchant credit application.