Identity Validation via Knowledge Based Authentication
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current identity verification methods for online transactions are inadequate in preventing credit card fraud and identity theft, as they rely heavily on complex algorithms with minimal user interaction, leading to significant financial losses despite the use of technologies like Verified by VISA and credit file reporting.
Innovation Solution
A process that collects minimal personal data from individuals conducting online transactions, matches it with validated public and private databases to generate Knowledge Based Authentication (KBA) questions, which are presented to the consumer for validation, providing an additional automated layer of protection and allowing for stringent vetting in online communities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If complex algorithms with minimal user interaction are used for identity verification, then automation is improved, but reliability of fraud prevention deteriorates
Solution Approach 1:
The patent introduces a third-party identity validation engine as an intermediary between the online merchant and the user. This mediator performs Knowledge Based Authentication by generating and evaluating KBA questions based on credit reporting data, thereby improving fraud detection reliability while maintaining automation. The third-party validator acts as a neutral arbiter that enhances trust without requiring manual intervention.
2Ease of operation
If minimal personal data is collected for identity validation, then ease of operation is improved, but measurement precision of identity verification deteriorates
Solution Approach 1:
The patent changes the parameter of data collection from extensive personal information to minimal data combined with dynamically generated KBA questions. The system collects only necessary identifiers (name, address, phone) and validates identity through knowledge-based questions derived from credit reports. This parameter change maintains verification accuracy by using unique knowledge facts while improving user convenience by minimizing direct data collection.
3Reliability
If Knowledge Based Authentication questions are generated from credit reporting data, then reliability of fraud detection is improved, but device complexity increases
Solution Approach 1:
The patent segments the identity validation system into distinct modular components: an online merchant engine, a third-party identity validation engine, and a credit reporting engine. Each module performs a specific function (transaction processing, KBA generation and evaluation, credit data provision), which reduces overall system complexity by allowing independent development, testing, and maintenance of each component while maintaining high fraud detection reliability through their coordinated interaction.
Data Source
AI summary
A process is proposed that collects minimal personal data of an individual who is conducting a transaction online, either directly or from a third party. The data collected is then matched to a known and validated public profile stored in public and private databases, and a set of Knowledge Based Authentication (KBA) questions are generated from the identified databases and presented to (e.g., displayed or read to via computer generated voice) the consumer for validation of the consumer's identity. Once the individual's identity has been validated, the online transaction by the person can then be authorized.