Fraud Detection via Video Location Verification
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Solution Overview
Problem
Existing fraud detection and prevention systems are inadequate as they often fail to detect fraudulent transactions in real-time, allowing perpetrators to complete multiple fraudulent transactions before being suspected.
Innovation Solution
A system that utilizes video-based monitoring techniques to verify the location of a customer by comparing the transaction location to historical data and using facial recognition from security camera footage to estimate travel time and execute fraud prevention steps if the time exceeds an allotted period.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional fraud detection systems wait for customer awareness of identity theft, then false positives are reduced, but fraud detection speed deteriorates allowing perpetrators to complete multiple fraudulent transactions
Solution Approach 1:
The system performs preliminary fraud detection by analyzing transaction location against historical data and video footage before authorizing transactions. This preliminary action enables the system to identify fraudulent patterns early, preventing multiple fraudulent transactions from being completed while maintaining high detection accuracy through pre-established customer profiles and location verification protocols
2Loss of time
If video-based monitoring is implemented to verify customer location in real-time, then fraud detection speed is improved, but device complexity increases
Solution Approach 1:
The system uses video capture devices and image processing algorithms as intermediaries to automatically verify customer location. These intermediaries bridge the gap between physical customer presence and digital transaction authorization, enabling real-time fraud detection without requiring complex manual verification processes. The video-based intermediary system processes location verification automatically, reducing overall system complexity despite the addition of video monitoring capabilities
Data Source
AI summary
Systems and methods for fraud detection and prevention is disclosed. The system may receive a transaction request for a first customer including a transaction location, transaction time stamp, and merchant type code. The system may determine whether the transaction location is expected for the first customer. When the transaction location is unexpected, the system may identify a last-known video detection having a last-known time stamp and last-known location. The system may determine a travel time estimate between the last-known location and the transaction location and determine a buffer based on the merchant type code. The system may compare the travel time estimate to an allotted time that includes a difference between the transaction time stamp and last-known time stamp less the buffer. When the travel time estimate exceeds the allotted time, the system may execute one or more fraud prevention steps.