Real-Time Challenge Question Generation for Fraud Authentication
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Solution Overview
Problem
Current computer systems lack effective real-time authentication methods to differentiate between genuine users and fraudsters attempting to access financial services, particularly in online applications where personal data can be easily obtained from public databases.
Innovation Solution
A system that generates user-specific challenge questions in real-time based on user-inputted data elements, utilizing potential user-specific knowledge information from databases to authenticate users, combining answer scores and behavioral analysis to determine fraudster activity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If real-time user-specific challenge questions are generated based on user-inputted data, then authentication accuracy is improved, but system complexity increases
Solution Approach 1:
The system performs preliminary actions by collecting user-inputted data elements and identifying potential knowledge information from databases before generating challenge questions. This advance preparation enables real-time accurate authentication without requiring complex processing during the authentication moment itself.
Solution Approach 2:
The system introduces an intermediary layer of potential knowledge information that bridges user inputs and challenge questions. This intermediary layer processes and structures data from multiple sources, simplifying the overall system architecture while enabling precise authentication through structured knowledge matching.
2Reliability
If multiple data sources are integrated for user verification, then fraud detection capability is improved, but processing time increases
Solution Approach 1:
The system maintains continuous useful action by integrating multiple data sources in a seamless workflow where user inputs continuously feed into knowledge identification, which continuously generates challenge questions. This continuous processing eliminates idle time between verification steps while maintaining comprehensive fraud detection across multiple data sources.
3Adaptability or versatility
If user-specific knowledge information is retrieved from databases, then challenge question relevance is improved, but data retrieval complexity increases
Solution Approach 1:
The system applies universality by creating a multi-functional data retrieval mechanism that handles multiple user inputs, searches multiple databases, and generates various types of challenge questions through a single integrated process. This universal approach retrieves user-specific knowledge information efficiently while maintaining high challenge question relevance across different authentication scenarios.
Data Source
AI summary
A method and system include receiving, by a processor of a server, from a computing device associated with a user, real-time user activity data identifying at least one activity performed on the computing device. User-inputted data elements from a plurality of elements of a graphical user interface displayed on the computing device are received, which identify user-specific data attributes. Potential user-specific knowledge information is identified from databases based on at least one user-specific data attribute. User-specific challenge questions based on the potential user-specific knowledge information are generated and displayed on the user's computing device. Answers to the user-specific challenge questions by the user are received. An answer score based on correct answers and a behavioral score based the real-time user activity data of the user are determined. The processor determines whether the user is or is not a fraudster based on the answer score and the behavioral score.