Automated Conversation Agent for Scam Call Interception
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Users face disruptions and data risks due to frequent scam calls, which are often made by automated bots or convincing humans, making it difficult to distinguish legitimate from illegitimate communications, and existing methods lack effective means to manage or reduce the number of scam calls.
Innovation Solution
A system that employs a scam detection mechanism to identify scamming entities and transfers incoming communications to an automated conversation agent using machine-learning models and natural language processing techniques, which interacts with scammers to occupy their time without revealing personal user information, thereby reducing the frequency of scam calls.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Object-affected harmful factors
If traditional methods are used to handle scam calls, then users can answer or ignore calls, but users experience frequent disruptions and data risks without effective reduction in scam call frequency
Solution Approach 1:
An automated conversation agent is introduced as an intermediary between the scammer and the user. The agent receives scam calls, engages scammers in extended conversations using natural language processing, and prevents direct access to user information. This intermediary captures scammer attention without exposing the user, thereby reducing both disruptions and data risks while maintaining call frequency at acceptable levels.
Solution Approach 2:
The system enables self-service by automatically detecting scam calls through analysis of caller ID, call patterns, and behavior, then autonomously routing them to the conversation agent without user intervention. The conversation agent independently manages the entire interaction with scammers, including engagement and termination, freeing users from having to manually handle or filter scam calls.
2Productivity
If automated conversation agents are deployed to engage scammers, then scam call frequency decreases, but system complexity increases
Solution Approach 1:
The automated conversation agent is designed as a multi-functional system that performs scam detection, call routing, natural language processing, conversation management, and call termination all through a single integrated platform. This universal agent handles diverse scamming techniques and languages, reducing the need for multiple specialized systems and thereby managing complexity while maintaining effectiveness in reducing scam call frequency.
Solution Approach 2:
The system replaces manual user actions (answering, filtering, and managing scam calls) with an automated electronic system using machine learning and natural language processing. This substitution eliminates the need for users to manually evaluate and handle each scam call, and the automated agent efficiently manages complex interactions that would be difficult for humans to handle at scale, thereby reducing scam call frequency without proportionally increasing user burden.
Data Source
AI summary
One embodiment provides a method, the method including: receiving, at an information handling device, an active communication; determining, using a scam detection system, the active communication is received from a scamming entity; transferring, using the scam detection system, the active communication to an automated conversation agent; and interacting, using the automated conversation agent, with the scamming entity.