Transaction-Based User Profile Scoring for Credit Assessment
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Solution Overview
Problem
Individuals with a history of high income, low payment requirements, and high cash flow in transaction accounts often lack a credit score that accurately reflects their creditworthiness, leading to difficulties in borrowing money and higher lending rates, prompting unnecessary efforts to increase their credit score.
Innovation Solution
A user profile scoring platform analyzes transaction logs to determine a transaction-based score using a machine learning model trained on historical data, comparing it to existing user scores to perform actions that enhance creditworthiness, such as pre-authorizing credit products and offering them to users.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional credit scoring methods are used, then credit scores are determined by credit account history, but individuals with high income and cash flow in transaction accounts cannot have their creditworthiness accurately reflected
Solution Approach 1:
The patent creates a unified scoring system that can process and evaluate data from multiple account types (credit accounts and transaction accounts) using the same machine learning model. The transaction log analysis model is designed to handle diverse financial data sources, making the creditworthiness assessment system universally applicable across different account categories rather than being limited to traditional credit account history.
Solution Approach 2:
The patent changes the input parameters of the credit scoring system from traditional credit account metrics to transaction account metrics (transaction volume, frequency, types, timing). By transforming the data parameters and feeding them into a machine learning model, the system can accurately assess creditworthiness based on transaction account behavior patterns, thereby improving measurement precision for individuals whose financial activity is primarily in transaction accounts.
2Measurement precision
If individuals engage in atypical financial activities to increase their credit score, then their credit score may improve, but they waste resources on unnecessary credit enhancements
Solution Approach 1:
The patent enables the system to automatically generate accurate credit scores based on actual transaction account data without requiring users to engage in artificial credit-building activities. The machine learning model processes real transaction logs and autonomously produces creditworthiness assessments, eliminating the need for users to perform atypical financial activities just to improve their scores. This self-service approach allows the system to accurately reflect true creditworthiness directly from natural financial behavior.
3Measurement precision
If a transaction log analysis model is implemented, then creditworthiness can be assessed based on transaction data, but the device complexity increases
Solution Approach 1:
The patent replaces traditional mechanical credit scoring methods (manual review, rule-based systems) with a machine learning-based transaction log analysis model. This substitution allows the system to automatically process complex transaction data patterns and generate accurate creditworthiness assessments without requiring complex manual evaluation procedures. The machine learning model handles the computational complexity internally, providing accurate results through automated data processing rather than complex system structures.
Data Source
AI summary
A user profile scoring platform may analyze a transaction log of a transaction account of a user to determine, based on transactions of the transaction log, a qualification status of the user, wherein the qualification status indicates that a characteristic of the user satisfies a threshold qualification metric. The user profile scoring platform may determine, based on the qualification status, a transaction-based score associated with the user, wherein the transaction-based score is determined using a transaction log analysis model. The user profile scoring platform may obtain, based on receiving the access information, a user score associated with a user transaction history that is associated with a plurality of transaction accounts that are associated with the user and different from the transaction account. The user profile scoring platform may perform an action based on the transaction-based score and the user score.