Transaction Prevalidation via APIs for Faster Fraud Checks
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Solution Overview
Problem
Existing transaction validation systems experience delays and inaccuracies due to the lack of real-time data integration and alignment with the user's intended objective, leading to potential fraud and non-compliant transactions.
Innovation Solution
Implementing a provider computing system with AI-driven application programming interfaces (APIs) to verify transaction data against user account information and intended objectives, using machine learning models for proactive validation and compliance with industry standards.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If extensive checks and procedures are performed to ensure payment accuracy and align purpose codes, then transaction validation accuracy is improved, but transaction processing time increases causing significant delays
Solution Approach 1:
The system performs preliminary validation of transaction data against the user's objective and account information before the transaction is executed. By pre-validating the transaction request using APIs to check purpose code alignment and fraud indicators, the system ensures accuracy upfront, allowing faster processing during actual transaction execution without repeating extensive checks.
2Measurement precision
If real-time data integration and objective alignment verification are implemented, then transaction validation accuracy is improved, but system complexity increases
Solution Approach 1:
The system introduces an intermediary validation layer that sits between transaction submission and execution. This intermediary component uses standardized APIs to fetch account information and verify objective alignment, acting as a mediator that simplifies the overall system architecture by centralizing complex validation logic in a dedicated module rather than distributing it throughout the entire transaction processing system.
3Reliability
If multiple verification steps using different APIs are performed, then fraud detection capability is improved, but processing overhead increases
Solution Approach 1:
The system performs a focused set of verification steps using specific APIs that are most relevant to the transaction type and risk profile. Rather than executing all possible verification checks uniformly, the system selectively applies verification methods based on the transaction characteristics and detected fraud indicators, performing only the necessary level of verification needed to ensure security while minimizing unnecessary processing overhead.
Data Source
AI summary
Systems and methods are described herein for prevalidating transactions using application programming interfaces (APIs). Such systems and methods may use a provider computing system to receive a transaction request from a user device associated with a user account held by a provider associated with the provider computing system. The user account may include account information, and the transaction request may include first transaction data and second transaction data. The provider computing system may determine an objective of the transaction request based on the account information. The provider computing system may perform a first verification including verifying, using a first API, the first transaction data based on the account information. The provider computing system may perform a second verification including verifying, using a second API, the second transaction data based on the objective. The provider computing system may validate the transaction request based on the first verification and the second verification.