Payment Graphic Code Risk Control via Feature Comparison
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Solution Overview
Problem
Existing payment systems for public transportation face risks such as account theft and deduction failures, particularly in scenarios where network connectivity is poor, necessitating a robust risk control method to ensure secure transactions.
Innovation Solution
A payment risk control method that involves generating a payment graphic code on a mobile terminal device, which includes preset risk control features like a payment account, current location, and station entering/exiting features, and detects transaction risks by comparing historical and real-time data to prevent unauthorized transactions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If real-time risk detection and prevention mechanisms are implemented, then transaction security is improved, but system complexity increases
Solution Approach 1:
The system performs preliminary risk assessment by comparing real-time transaction features against historical risk patterns before completing the transaction. Risk control features including payment account information, location data, and station entering/exiting records are pre-analyzed to identify potential threats, allowing security measures to be activated only when necessary rather than blocking all transactions uniformly.
Solution Approach 2:
A risk control server acts as an intermediary between the payment system and potential threats. This intermediary component receives transaction requests, performs risk analysis by comparing features against historical data, and mediates whether to allow or block transactions. This separates the security function from the core payment processing, managing system complexity through functional decomposition.
2Reliability
If frequent risk detection is performed, then transaction security is improved, but processing time increases
Solution Approach 1:
The system skips detailed risk analysis for transactions that match normal patterns by rapidly comparing real-time features against established baselines. When transaction characteristics align with historical normal behavior, the system rushes through the verification process with minimal delay. Detailed analysis is only performed when anomalies are detected, reducing average processing time while maintaining security.
Solution Approach 2:
The system performs partial risk detection by focusing only on critical risk control features such as location consistency, payment account validity, and station entering/exiting patterns rather than analyzing every transaction detail equally. This selective approach applies sufficient detection action to identify threats while avoiding excessive analysis of normal transactions, balancing security with processing speed.
3Measurement precision
If comprehensive risk control features are collected, then detection accuracy is improved, but data processing load increases
Solution Approach 1:
The system applies different levels of analysis to different risk control features based on their importance and reliability. Critical features such as location data and payment account information receive more rigorous validation, while less critical features undergo lighter checking. This localized quality approach ensures high detection accuracy for key risk indicators without uniformly processing all data at maximum intensity, reducing overall processing load.
Solution Approach 2:
The system collects and analyzes only the necessary risk control features required for effective risk detection rather than gathering all possible data. By selecting essential features including payment account details, location information, and station entering/exiting records, the system achieves sufficient detection accuracy without the excessive energy consumption that would result from processing comprehensive datasets including redundant or low-value information.
Data Source
AI summary
A method for payment risk control includes: receiving a request for payment graphic code generation from a mobile terminal device, the request carrying preset risk control features, the risk control features including a payment account feature of an account, a current location feature, and a station entering and exiting feature; obtaining pre-stored historical risk control features of the account according to the payment account feature in the request; detecting whether there is a transaction risk for the mobile terminal device by comparing the obtained historical risk control features with the risk control features carried in the request; and sending a risk control detection result to the mobile terminal device to generate and display a payment graphic code.