Caller ID Augmentation via Intermediary Data Enrichment
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current caller ID systems from switched telephone networks (STNs) often provide limited or inaccurate information, such as truncated names or missing data like email addresses, making it difficult for recipients to verify callers and leading to potential fraud and poor customer experiences.
Innovation Solution
A method and system that augment caller ID information by searching data storages for additional data elements, such as names, email addresses, and geographic information, and transmitting these augmented data elements to devices or saving them for later use, allowing for enhanced verification and improved customer interactions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If traditional STN caller ID systems are used, then the system complexity is low and communication protocols are simple, but the information completeness is insufficient and accuracy is poor
Solution Approach 1:
The patent introduces an intermediary system that sits between the STN and the callee's device. This intermediary receives caller ID information from the STN, enriches it by searching external data sources (social media, business databases, etc.), and then transmits the augmented information to the callee's device. This mediator approach allows information enrichment without requiring changes to the core STN infrastructure.
Solution Approach 2:
The system segments the caller ID information delivery process into distinct components: (1) receiving basic caller ID from STN, (2) searching external data sources for additional information, (3) augmenting and formatting the data, and (4) transmitting to the device. This segmentation allows each component to be optimized independently and facilitates integration with multiple data sources.
2Measurement precision
If additional data sources are searched to augment caller ID information, then the information accuracy and completeness improve, but the time required to retrieve information increases
Solution Approach 1:
The system performs preliminary actions by pre-fetching and caching caller information from external data sources before calls occur. When a caller's number is observed in outgoing calls or other activities, the system proactively retrieves and stores associated information (social media profiles, business details, etc.) in advance. This way, when an incoming call occurs, the augmented information is already available or can be quickly retrieved.
Solution Approach 2:
The system implements partial action by selectively searching for additional information based on the call context. Not all calls require the same level of augmentation - the system can adjust the depth of information retrieval based on factors like caller frequency, time of day, and user preferences. This partial approach balances information quality with retrieval time constraints.
3Reliability
If comprehensive caller information is made available, then fraud mitigation capability improves, but the privacy concerns and data security risks increase
Solution Approach 1:
The system applies local quality by providing different levels of information augmentation to different users based on their specific needs and contexts. Rather than uniformly providing all possible information to everyone, the system can tailor the level of augmentation - for example, providing more detailed information for business calls versus personal calls, or adjusting based on user privacy settings. This localized approach balances fraud mitigation with privacy protection.
Solution Approach 2:
The system implements feedback mechanisms where user responses to augmented caller information are tracked and used to refine future information provision. If users consistently reject calls based on augmented information (indicating accurate fraud detection) or provide feedback about privacy concerns, the system adjusts its information retrieval and presentation strategies accordingly. This feedback loop allows the system to optimize both fraud mitigation and privacy protection over time.
Data Source
AI summary
Disclosed are methods and systems for obtaining and transmitting augmented telephonic entity data to a device or data storage. An example method includes providing a telephonic switching and computing framework, providing access to a data storage, receiving a telephone call from a switched telephone network (STN), receiving caller ID information from the STN, then in response to a trigger, searching for and retrieving within the data storage an augmented data record, and further in response to the trigger event, transmitting the augmented data element to a device. An example system generally comprises a data storage, a telephonic apparatus configured to receive a call with caller ID information from a switched telephone network (STN), a network-connected computing apparatus configured to, in response to a trigger, search for and retrieve an augmented data element associated with the caller ID information, and transmit the augmented data element to a device over a network.