Geolocation Fraud Detection Using Driver Low-Access Time Windows
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Solution Overview
Problem
Current methods fail to timely and confidently detect unauthorized online activities, particularly during times when a vehicle driver is unlikely to access web resources, leading to potential financial fraud and increased losses for institutions.
Innovation Solution
A system that determines ranges of time when a vehicle driver has a low likelihood of accessing a web resource using driving data, including geolocation, IP addresses, and biometric data, to identify potentially unauthorized activities and trigger protective measures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional fraud detection methods are used, then detection coverage is provided, but detection timeliness and confidence are insufficient
Solution Approach 1:
The system performs preliminary actions by determining the driver's schedule and identifying time ranges when the driver is unlikely to access web resources before fraud detection occurs. This allows the system to proactively establish baseline expectations for driver behavior patterns, enabling faster and more confident detection of unauthorized activities when they occur during these identified time ranges.
Solution Approach 2:
The patent introduces a temporal dimension to fraud detection by analyzing when online activities occur relative to the driver's schedule. Instead of only detecting fraud based on what activities occur, the system adds the dimension of when activities occur, comparing detected online activities against predetermined time ranges when driver access is unlikely, thereby improving both detection confidence and timeliness.
2Reliability
If comprehensive driving data analysis is performed, then fraud detection accuracy improves, but system complexity increases
Solution Approach 1:
The system segments the analysis by dividing the driver's schedule into distinct time ranges based on when the driver is unlikely to access web resources. This segmentation allows the fraud detection system to focus analysis on specific temporal segments rather than continuously analyzing all activities, improving detection accuracy while managing system complexity through targeted analysis of divided time periods.
Solution Approach 2:
The patent changes the parameter of analysis from general activity monitoring to time-range-specific activity monitoring. By transforming the detection parameter to consider whether activities occur during predetermined time ranges when driver access is unlikely, the system improves fraud detection accuracy without proportionally increasing complexity, as the same infrastructure is used with an added temporal filtering parameter.
Data Source
AI summary
Methods, computer-readable media, software, and apparatuses may retrieve, from a computing device at a vehicle, driving data, and determine, based on the driving data, a range of time when a driver of the vehicle has a low likelihood of accessing a web resource over a network. An online activity may be detected for an account associated with the driver. In some aspects, a time of the online activity may be compared to the range of time. Based upon a determination that the time of the online activity is within the range of time, a potentially unauthorized activity may be identified. In some aspects, in response to the potentially unauthorized activity, one or more steps may be triggered to protect the driver from the potentially unauthorized activity.