Telephony Platform Fraud Scoring for Cross-Account Abuse Detection
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Solution Overview
Problem
Telephony fraud, particularly toll fraud and other illicit uses, have become prevalent due to the ease of access to disposable phone numbers and the development of new telephony platforms, affecting users, telephony platform providers, and legitimate applications, with developers lacking access to necessary information to prevent such fraud.
Innovation Solution
A fraud scoring system integrated with a multitenant communication platform that applies fraud-based heuristics, monitors account usage, and takes action to prevent illicit behavior, utilizing data sources like communication history, billing information, and application configuration to detect and mitigate fraud across multiple accounts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If telephony platforms enable wider access and developer creativity, then product innovation and service diversity improve, but vulnerability to fraud and illicit use increases
Solution Approach 1:
The patent introduces a fraud detection service as an intermediary component between the telephony platform and users/developers. This service acts as a mediator that analyzes usage patterns, communicates fraud risks to developers, and enables them to implement protective measures in their applications, thereby resolving the contradiction between platform accessibility and fraud vulnerability
Solution Approach 2:
The system performs preliminary fraud detection and risk assessment before fraudulent activities can cause significant harm. By continuously monitoring usage patterns and providing early warnings to developers, the system enables preventive actions to be taken before fraud escalates, thus protecting the platform while maintaining its versatility
2Reliability
If fraud detection capabilities are enhanced, then security against illicit use improves, but system complexity and resource requirements increase
Solution Approach 1:
The fraud detection service is designed to be self-contained and autonomous, continuously monitoring platform usage without requiring complex external systems. It independently analyzes usage patterns, detects fraud indicators, and provides recommendations, thereby achieving high fraud prevention capability while minimizing additional system complexity
Solution Approach 2:
The fraud detection service performs multiple functions including usage pattern analysis, fraud risk assessment, developer notification, and application-level protection guidance. By consolidating these diverse functions into a single service, the system achieves comprehensive fraud prevention without proportionally increasing complexity
3Measurement precision
If comprehensive monitoring of usage patterns is implemented, then fraud detection accuracy improves, but processing time and computational resources increase
Solution Approach 1:
The system implements partial monitoring by focusing on specific usage patterns and metrics most indicative of fraud rather than analyzing every possible data point. This selective approach maintains high detection accuracy for fraudulent activities while reducing overall processing time and computational resource requirements
Solution Approach 2:
The fraud detection service continuously scans usage patterns in real-time, rapidly identifying and flagging suspicious activities without delay. By prioritizing speed in detecting critical fraud indicators and processing only essential data, the system achieves both high detection accuracy and efficient processing
Data Source
AI summary
A system and method for preventing illicit use of a telephony platform that includes enrolling a plurality of accounts on a telecommunications platform, wherein an account includes account configuration; at a fraud detection system of the telecommunications platform, receiving account usage data, wherein the usage data includes at least communication configuration data and billing configuration data of account configuration and further includes communication history of the plurality of accounts; calculating fraud scores of a set of fraud rules from the usage data, wherein at least a sub-set of the fraud rules include conditions of usage data patterns between at least two accounts; detecting when the fraud scores of an account satisfy a fraud threshold; and initiating an action response when a fraud score satisfies the fraud threshold.