Mobile Wallet Provisioning Fraud Risk Assessment
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Solution Overview
Problem
Conventional methods of provisioning a mobile wallet face challenges in authentication and fraud prevention, particularly in computer networks, where the risk of fraud is high due to the difficulty in verifying the identity and ownership of mobile devices and accounts, often requiring costly call center authentications and being vulnerable to fraud.
Innovation Solution
A system and method that utilize a risk determination system to assess fraud risk by correlating device ownership and account ownership information, applying business rules and statistical modeling techniques to generate a fraud risk level, and performing out-of-band verification when necessary, to authenticate and authorize provisioning requests in real-time, reducing the need for costly call center interventions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional authentication methods are used for mobile wallet provisioning, then identity verification can be performed, but the process is vulnerable to fraud and requires costly call center interventions
Solution Approach 1:
The system performs preliminary risk assessment and data aggregation before the actual provisioning decision. By pre-calculating fraud risk scores using statistical modeling and correlating device/account ownership information in advance, the system prepares authentication outcomes ahead of time, reducing the need for complex real-time verification and costly call center interventions.
Solution Approach 2:
The patent introduces an intermediary risk determination system that acts as a mediator between the provisioning request and the final authentication decision. This intermediary layer aggregates data from multiple sources, applies business rules and statistical modeling, and provides risk-based authentication recommendations, thereby simplifying the overall authentication process while improving fraud detection capabilities.
2Reliability
If out-of-band verification is performed for high-risk provisioning requests, then fraud risk is reduced, but the provisioning time increases
Solution Approach 1:
The system dynamically adjusts the level of verification required based on the calculated fraud risk score. For low-risk requests, provisioning is expedited with minimal verification, while high-risk requests trigger additional out-of-band verification steps. This dynamic approach ensures that time is not lost on low-risk transactions while maintaining strong security for high-risk ones.
Solution Approach 2:
The patent applies different verification intensities to different portions of the provisioning process based on local risk assessments. Rather than uniformly applying complex verification to all requests, the system identifies specific high-risk elements (such as device-account ownership mismatches) and applies targeted verification only where needed, thereby reducing overall provisioning time while maintaining detection accuracy.
3Measurement precision
If data aggregation from multiple sources is implemented, then fraud risk prediction accuracy is improved, but system complexity increases
Solution Approach 1:
The risk determination system is designed as a universal platform that handles multiple data sources, business rules, and statistical modeling techniques through a single integrated architecture. This multi-functional system aggregates device information, account information, and ownership data while applying various analysis methods, thereby improving prediction accuracy without proportionally increasing system complexity through modular design.
Solution Approach 2:
The system manages complexity by parameterizing the data aggregation process, allowing configuration of which data sources to access, what business rules to apply, and which statistical models to use. By making these parameters adjustable rather than hard-coded, the system can adapt to different fraud detection needs without requiring structural changes, thus improving accuracy while controlling complexity through flexible parameter management.
Data Source
AI summary
A method including receiving an inquiry from a provider to authenticate a provisioning of an account to a mobile wallet. The method also can include determining device ownership information for a mobile device that operates the mobile wallet, account ownership information for the account, device risk information associated with the mobile device, and account risk information associated with the account. The method additionally can include determining an ownership correlation between the device ownership information and the account ownership information. The method further can include generating a fraud risk level by applying business rules and one or more statistical modeling techniques. The method additionally can include providing a response to the provider based on the fraud risk level. Other embodiments are provided.