Post-paid Transaction Risk Assessment via Predictive Affordable Value
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Solution Overview
Problem
In buy-now-pay-later transactions, merchants face risks due to insufficient funds in users' e-wallets, leading to deduction failures and NSF losses, as information is not interoperable between merchants and third-party e-wallets, making it difficult to determine if users can afford purchases.
Innovation Solution
A post-paid transaction data processing method that analyzes payment channels by receiving risk search information, determining a predictive affordable value based on historical bill data and transaction behavior, and evaluating the default risk of transactions before they are concluded, allowing merchants to assess the payment possibility and reduce risks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If merchants allow buy-now-pay-later transactions without fund verification, then user convenience and transaction speed are improved, but the risk of deduction failure and NSF loss increases
Solution Approach 1:
The system performs preliminary fund verification by analyzing historical bill data and transaction behavior patterns before the buy-now-pay-later transaction is completed. This advance assessment determines whether the user's payment channel will have sufficient funds at the deduction time, allowing merchants to identify and reject high-risk transactions before they result in NSF losses, while still permitting convenient transactions for low-risk users
2Reliability
If merchants verify user funds in real-time, then deduction failure risk is reduced, but information interoperability requirements and system complexity increase
Solution Approach 1:
The system introduces an intermediary risk assessment mechanism that analyzes user payment capabilities through historical data patterns rather than requiring direct real-time communication with multiple payment channels. This intermediary layer processes transaction behavior data to predict fund availability, reducing the need for complex real-time interoperability systems while maintaining high deduction success rates
3Reliability
If merchants perform comprehensive risk assessment, then transaction risk is reduced, but processing time and computational resources increase
Solution Approach 1:
The system pre-processes and stores user transaction behavior patterns and historical bill data during off-peak periods, building predictive models in advance. When a buy-now-pay-later transaction occurs, the system quickly queries these pre-built models rather than performing comprehensive analysis in real-time, thereby maintaining high risk assessment accuracy while minimizing transaction processing time
Solution Approach 2:
The system performs risk assessment selectively based on transaction characteristics and user profiles. For users with established good payment histories, the system applies simplified verification processes rather than comprehensive analysis, reducing processing time for low-risk cases while maintaining thorough assessment for higher-risk transactions
Data Source
AI summary
A post-paid transaction data processing method includes: receiving risk search information via a wireless or wired interface, the risk search information including a transaction amount and a transaction user identifier of a post-paid transaction; acquiring, according to the transaction user identifier, a payment channel corresponding to the transaction user identifier; determining a predictive affordable value of the payment channel for the transaction amount based on the payment channel and the transaction amount; and determining a default evaluation result of the post-paid transaction according to the predictive affordable value.