Feature-Flag Checkout Flows for Faster KYC Spending Approval
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Solution Overview
Problem
Existing online transaction processors face difficulties in guiding users to specific data processing flows for accessing spending limits and balances at merchant locations, requiring significant data entry and navigation, and failing to provide a streamlined user experience.
Innovation Solution
Implementing feature flag tracking and guided user data flows using a software development kit (SDK) to automate the process, allowing users to interact with merchants through mobile applications, retrieve feature flags, and perform KYC checks to determine merchant-specific spending limits efficiently.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If users manually navigate to data processing flows and enter data, then spending limits and balances can be accessed, but the process requires significant data entry and navigation time
Solution Approach 1:
The system performs preliminary actions by detecting merchant checkout entry points and automatically initiating the appropriate data processing flows before users need to access spending limits. Feature flags are pre-configured to identify user needs, and the system proactively guides users through streamlined flows without requiring manual navigation or extensive data entry.
Solution Approach 2:
The patent introduces an intermediary guided flow system that mediates between the user and the complex data processing requirements. This intermediary automatically detects user intent, selects appropriate processing flows, and manages data collection, thereby eliminating the need for users to manually navigate through multiple screens and enter data.
2Adaptability or versatility
If generic data processing flows are used, then all users can access the system, but the flows are not tailored to specific merchant, user request, or account data
Solution Approach 1:
The system applies local quality by configuring feature flags and data processing flows specific to each merchant, user request, and account type. Instead of using uniform generic flows, the system tailors the data collection and processing steps to match the specific context, ensuring that users encounter only the relevant fields and procedures for their particular situation.
Solution Approach 2:
The patent utilizes parameter changes by dynamically adjusting the features and parameters of data processing flows based on detected user needs and merchant contexts. Feature flags serve as parameters that control which specific flows are activated, allowing the system to adapt its behavior and presentation to match the specific requirements of each transaction scenario.
3Ease of operation
If automated feature flag tracking is implemented, then user navigation is streamlined, but the system requires tracking and processing of feature flags and deeplink data
Solution Approach 1:
The system implements self-service by enabling automated feature flag tracking and flow detection without requiring manual user configuration. The SDK automatically detects merchant checkout entry points, retrieves relevant feature flags, and guides users through appropriate flows based on real-time data, thereby simplifying user navigation while managing system complexity through automation.
Data Source
AI summary
There are provided systems and methods for checkout approval through feature flag tracking and guided user data flows. An online transaction processor may provide account establishment and/or know your customer (KYC) data verification at merchant checkout through use of different account processes and feature flags for mobile applications. A user may utilize their mobile device to scan a code at the merchant checkout, which may cause loading of an interface in the mobile application and a corresponding feature flag. Based on whether the user has previously used the application and/or has an account with the transaction processor, the user may be guided to a processing flow for data input, processing, and verification. The data may include KYC data, which may be used to perform a risk assessment of the user and determine a spending limit extendable to the user.