Online Transaction Authentication via Risk Parameter Analysis
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current online transaction systems lack effective methods to authenticate transactions and detect fraudulent requests, particularly in social networking platforms, where third-party applications often rely on user data, leading to potential fraud through credit card chargebacks, stolen or hacked credit card usage, and other malicious activities.
Innovation Solution
A transaction authenticating system that determines a risk parameter for users based on their profile parameters and peer associations within a networking platform, using a combination of profile data analysis and predefined criteria to assess the likelihood of fraud, thereby authenticating or denying transactions accordingly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If online transaction systems allow third-party applications to leverage user data for monetization, then the economic value and functionality of the platform increase, but the risk of fraudulent transactions and malicious activities increases
Solution Approach 1:
The system performs preliminary actions by establishing user profiles and collecting behavioral data before transactions occur. This proactive approach enables the system to have authentication mechanisms ready and to identify potential fraud risks in advance, rather than reacting after fraudulent activities have already compromised platform functionality
Solution Approach 2:
The patent introduces an intermediary authentication system that acts as a mediator between third-party applications and user transactions. This intermediary layer analyzes user profiles and transaction patterns to verify authenticity, allowing the platform to maintain versatility while filtering out fraudulent activities before they can exploit the system
2Productivity
If the system implements traditional authentication methods, then the transaction processing is simple and fast, but the system cannot effectively detect fraudulent transactions
Solution Approach 1:
The system performs preliminary actions by establishing user profiles and collecting behavioral data before transactions occur. This proactive approach enables the system to have authentication mechanisms ready and to identify potential fraud risks in advance, rather than reacting after fraudulent activities have already compromised platform functionality
Solution Approach 2:
The patent implements feedback mechanisms where transaction outcomes and user behaviors are continuously monitored and fed back into the profile system. This allows the authentication system to learn from past transactions and improve its fraud detection accuracy over time while maintaining efficient processing speeds through refined decision-making algorithms
3Measurement precision
If the system collects and analyzes extensive user profile data for authentication, then the fraud detection accuracy improves, but the system complexity and data processing requirements increase
Solution Approach 1:
The patent segments the authentication process into distinct components: profile data collection, behavioral pattern analysis, and transaction verification. This segmentation allows each component to be optimized independently and processed through modular systems, reducing overall complexity while maintaining high detection accuracy through specialized analysis at each stage
Data Source
AI summary
The present invention generally relates to authenticating online transactions, and more specifically, to method and system for determining a potentially fraudulent online transaction request based on a risk parameter associated with a user in a networking platform such as, a social networking platform. The method comprises receiving an online transaction request from a user. Thereafter, determining the risk parameter of the user based on one or more profile parameters associated with the user or one or more peer users associated with the user in the community. Based on the risk parameter of the user the online transaction request of the user is authenticated.