Credit Analysis Unit for Real-Time Banking Data Access
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Solution Overview
Problem
Existing digital banking systems lack proactive features for improving credit standing, as third-party credit repair services lack access to real-time transaction data and often resort to risky tactics that damage credit scores.
Innovation Solution
A digital banking system provides a framework for analyzing all customer financial data, setting achievable credit goals, and offering rewards upon goal achievement, with continuous monitoring and communication to improve credit standing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If third-party credit repair services manually collect and update customer information, then credit improvement goals can be established, but real-time transaction data access is lost and information completeness deteriorates
Solution Approach 1:
The patent introduces a credit repair system that acts as an intermediary between customers and financial institutions. This system automatically accesses and analyzes real-time transaction data from multiple financial institutions through automated connections, eliminating the need for manual information collection while ensuring complete and up-to-date data availability for credit improvement strategies
Solution Approach 2:
The system enables self-service by automatically collecting, updating, and analyzing customer financial data without requiring manual intervention. The automated data collection processes continuously monitor transaction accounts and update credit profiles in real-time, allowing the system to independently maintain complete and current information
2Quantity of substance
If default tactics are used to coerce settlements, then outstanding debt may be reduced, but credit history and score are severely damaged
Solution Approach 1:
The patent converts the harmful effect of debt into a beneficial credit improvement opportunity by analyzing the root causes of financial distress and creating personalized improvement strategies. Instead of using harmful default tactics, the system identifies spending patterns, budget opportunities, and repayment strategies that simultaneously reduce debt and improve credit scores through positive financial behavior
Solution Approach 2:
The system implements continuous feedback loops that monitor customer progress toward credit improvement goals and adjust strategies in real-time. By providing ongoing feedback on spending patterns, payment progress, and credit score changes, the system guides customers toward sustainable debt reduction while maintaining or improving credit history through responsible financial behavior
3Measurement precision
If comprehensive financial data analysis is implemented, then credit goals can be precisely defined, but system complexity increases
Solution Approach 1:
The patent segments the complex credit analysis process into distinct functional modules: data collection from multiple sources, transaction pattern recognition, credit goal formulation, strategy development, and progress monitoring. Each module handles specific aspects of the analysis independently, reducing overall system complexity while maintaining comprehensive data analysis capabilities for precise credit goal definition
Solution Approach 2:
The system implements a universal credit analysis platform that handles multiple functions through integrated processes. The same data infrastructure supports various credit improvement strategies, the analysis engine handles different types of financial data uniformly, and the goal formulation process adapts to different customer situations, reducing complexity through standardized multi-functional components
Data Source
AI summary
A framework for client credit authorization level analysis criteria, communication and actions in a digital banking system. A client with past credit problems enters a credit improvement program at a financial institution. The client's financial asset and liability information, along with credit history are provided via the digital banking system. The client identifies objectives, such as paying off debt or qualifying for a car loan. Roadblocks and opportunities are identified from the financial data and the credit history. Goals are programmatically defined based on the client background data, along with a reward to be earned upon achievement of the goals. Conventional algorithms and machine learning techniques may be used for computing the goals and rewards in a manner which is amendable to the client and the financial institution. Progress toward the goals is monitored in the digital banking system, and communications are provided to the client, particularly positive reinforcement messages.