Targeted Content Delivery via Anonymized Financial Data Broker
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Solution Overview
Problem
Current Internet advertising technologies, such as behavioral targeting, are limited in their ability to accurately target consumers based on their financial capabilities and spending habits, as they rely on website tracking and do not account for purchases made outside of the advertiser's own platforms, leading to ineffective ad delivery.
Innovation Solution
A system and method that utilizes a database and processor to classify consumers based on financial information, creating targeted lists for delivering personalized content, including advertisements, by associating anonymous identification codes with financial data from financial institutions, allowing for targeted content delivery to devices used by consumers after they log onto affiliated applications.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If behavioral targeting based on website tracking is used, then advertising can be targeted to users based on their browsing habits, but the targeting accuracy is limited because it does not account for users' actual purchasing power and spending habits
Solution Approach 1:
The patent introduces financial institutions as intermediaries that bridge the gap between advertisers and consumers. These institutions provide anonymized financial data (income, spending habits, creditworthiness) to a data broker, which then enables more accurate advertising targeting without requiring advertisers to directly access sensitive financial information. This intermediary approach resolves the contradiction by making financial capability information available for targeting purposes while maintaining appropriate privacy boundaries.
Solution Approach 2:
The patent replaces the mechanical website tracking system with a data broker system that aggregates and analyzes financial information. Instead of tracking user behavior through cookies and website visits, the system substitutes a centralized data broker that processes anonymized financial data from multiple financial institutions to create comprehensive consumer profiles for advertising purposes.
2Productivity
If individual retailers track purchasing habits on their own websites, then they can provide targeted advertising to returning customers, but the tracking is limited to only their own platform and cannot capture overall consumer spending patterns
Solution Approach 1:
The patent merges data from multiple independent sources (financial institutions) into a unified consumer profile through a data broker. By combining financial data from various institutions, the system creates a comprehensive view of consumer spending patterns across different retailers and platforms, not just within individual retailer ecosystems. This merging enables advertisers to target consumers based on their overall spending behavior rather than isolated platform-specific data.
3Measurement precision
If detailed consumer financial information is collected for targeted advertising, then advertising relevance to consumers' financial capabilities is improved, but consumer privacy and anonymity may be compromised
Solution Approach 1:
The patent extracts only the necessary financial information elements needed for advertising targeting (income range, spending habits, creditworthiness categories) while leaving out sensitive personal identifiers. The data broker receives anonymized financial data from institutions, processes only the relevant targeting attributes, and provides this extracted information to advertisers without exposing complete financial records or personal identities, thus reducing privacy risk while maintaining advertising relevance.
Solution Approach 2:
The patent applies different levels of data detail to different parties in the system. Financial institutions provide anonymized aggregate data to the data broker, the data broker processes this into targeted advertising profiles, and advertisers receive only the specific financial attributes needed for their campaigns. Each entity in the chain receives and processes only the local quality of data appropriate to its function, minimizing overall privacy exposure while enabling effective targeting.
Data Source
AI summary
A system for delivering targeted content to a device includes a database and a processor. The database stores anonymous identifications for a plurality of customers of at least one financial institution. Each anonymous identification is associated with financial information for a respective customer of the at least one financial institution. The processor includes software that is configured to classify consumers, create a targeted list of content viewers, and deliver a targeted advertisement over a network to a device used by a content viewer on the targeted list. The classifications can be based on the financial information associated with each anonymous identification. The target list of content viewers can be based on at least one selected classification. The advertisement can be delivered to a device used by a content viewer on the targeted list after the device has been used to log onto an application offered by the at least one financial institution.