Merchant Reliability Scoring via Intermediary Mediation
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Solution Overview
Problem
Consumers lack confidence in unknown e-commerce sites due to insufficient assurance of merchant reliability, as existing security measures like SSL Certificates only address data security and not merchant behavior or trustworthiness.
Innovation Solution
A system that collects data from various sources to generate a merchant reliability metric, known as a 'web score,' which predicts the reliability of an online merchant, including customer feedback and transaction history, to provide consumers with a trustworthy assessment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If SSL Certificates are used to provide data security, then data transmission security is improved, but consumer confidence in merchant reliability is not sufficiently addressed
Solution Approach 1:
The patent introduces a third-party scoring service as an intermediary between merchants and consumers. This independent scoring service collects data from multiple sources (merchant-provided information, third-party data, transactional information) and generates objective reliability scores that mediate the trust relationship, allowing consumers to assess merchant reliability beyond just data security credentials
Solution Approach 2:
The scoring service performs multiple functions: collecting merchant information, verifying credentials, analyzing transaction history, gathering customer feedback, and generating comprehensive reliability scores. This multi-functional approach addresses various aspects of merchant reliability (security, honesty, reputation) in a unified system, rather than relying on separate security certificates alone
2Measurement precision
If EV SSL Certificates are implemented to identify legal entities, then identity verification is improved, but assurances about merchant behavior and trustworthiness are excluded
Solution Approach 1:
The patent segments the assessment of merchant reliability into distinct components: identity verification (from SSL certificates), financial credibility (credit data), operational history (transactional data), and reputation (customer feedback). Each component is evaluated separately and aggregated into an overall reliability score, allowing precise measurement of identity while also capturing behavioral aspects that SSL certificates exclude
Solution Approach 2:
The reliability score is constructed as a composite metric combining multiple data types and sources: merchant-provided information, third-party verification data, credit bureau data, transactional history, and customer feedback. This composite approach integrates identity verification with behavioral assessment, creating a more comprehensive reliability indicator than SSL certificates alone
3Measurement precision
If comprehensive data collection from multiple sources is performed, then merchant reliability assessment accuracy is improved, but system complexity increases
Solution Approach 1:
The patent employs multiple intermediary services to simplify data collection: credit reporting agencies for financial data, domain registration services for identity verification, payment processors for transactional data, and customer feedback systems. These intermediaries handle the complexity of data gathering and verification, allowing the scoring service to focus on aggregation and analysis without managing the underlying complexity of each data source
Solution Approach 2:
The system transforms diverse data from multiple sources into a standardized numerical scoring format. Different data types (credit scores, transaction histories, feedback ratings) are converted into comparable parameters and weighted according to their reliability and relevance, enabling accurate assessment while managing complexity through parameter standardization
Data Source
AI summary
A merchant scoring system predicts and reports the likelihood that a merchant is reliable (e.g., trustworthy, honest, and reputable), which is expected to translate into a positive consumer experience. The system collects data from a variety of data sources, including combinations of the merchant, third-parties, and/or customers who have transacted with the merchant. A scoring model is executed on this collected data to determine an independent and objective merchant reliability metric that predicts the expected reliability of a merchant within a range. The system may also track transactions of individual merchants, populating a transaction history database with information about each merchant for use in this collection and scoring process. The transaction history data and other data may also be accessible to a prospective customer to build his or her confidence in and understanding of the merchant reliability metric and his or her trust of the merchant.