Identity Verification Using Online Offline Data Fusion
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Solution Overview
Problem
Online systems face challenges in verifying the identity and trustworthiness of users, as users can create fake identities and impersonate others, leading to difficulties in ensuring the authenticity and reliability of individuals participating in transactions.
Innovation Solution
An online system is configured to verify user identity and trustworthiness by combining online and offline information, including data from social networking systems, email servers, government-issued IDs, credit history, and criminal databases, using modules for identity verification and trustworthiness scoring.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If users are allowed to create online accounts with minimal verification, then ease of operation is improved, but reliability of user identity deteriorates
Solution Approach 1:
The system performs preliminary identity verification by collecting and storing verification data (government-issued ID information, credit history, education history, criminal database checks) during account creation or before transactions occur. This preliminary action ensures that when users need to conduct transactions, their identity has already been verified, resolving the contradiction between ease of operation and reliability.
2Reliability
If comprehensive identity verification is implemented, then reliability of user identity is improved, but device complexity increases
Solution Approach 1:
The system introduces intermediary verification modules that act as mediators between users and the online platform. These modules handle the complex verification processes by interfacing with external databases (government ID verification, credit history, education history, criminal records) and translating their responses into simplified verification decisions. This intermediary layer manages the complexity while maintaining high reliability.
Solution Approach 2:
The verification system is segmented into multiple independent modules, each responsible for a specific verification aspect (government ID verification, credit history check, education verification, criminal background check). This segmentation allows each module to specialize in one verification task, making the overall complex system manageable and maintainable while achieving comprehensive verification.
3Measurement precision
If multiple verification data sources are integrated, then measurement precision of user identity is improved, but loss of time in verification increases
Solution Approach 1:
The system performs verification actions in advance by pre-collecting and storing data from multiple sources (government IDs, credit history, education records, criminal databases) during account creation or periodic updates. This preliminary action ensures that when verification is needed, the data is already available, achieving high measurement precision without time loss during actual transactions.
Solution Approach 2:
The verification system implements feedback mechanisms where verification results from one data source inform the verification process of other sources. For example, if government ID verification succeeds, the system can use this feedback to reduce the stringency or time required for other verification checks, optimizing the overall verification time while maintaining precision.
Data Source
AI summary
Methods and systems for verifying the identity and trustworthiness of a user of an online system are disclosed. In one embodiment, the method comprises receiving online and offline identity information for a user and comparing them to a user profile information provided by the user. Furthermore, the user's online activity in a third party online system and the user's offline activity are received. Based on the online activity and the offline activity a trustworthiness score may be calculated.