Fraud Prevention Tool Using Environmental Data Analysis
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Solution Overview
Problem
Financial institution customers, especially seniors, are vulnerable to fraudulent schemes where they are coerced or tricked into executing transactions, and existing technologies lack effective methods to detect such fraudulent activities in real-time.
Innovation Solution
A computer-implemented system and method that utilizes sensors on user computing devices and wearable devices to capture environmental data, such as biometric and image/audio data, to detect anomalous conditions during transactions, which can indicate coercion or false pretenses, and sends this data to a financial institution system to block potentially fraudulent transactions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If environmental data collection (biometric and image/audio data) is implemented to detect fraudulent transactions, then fraud detection capability is improved, but device complexity and data processing requirements increase
Solution Approach 1:
The fraud detection system is segmented into multiple independent components: sensor modules for data collection, processing modules for analyzing biometric and environmental data, and decision modules for determining fraudulent activity. This segmentation allows each component to specialize in specific tasks, improving overall detection capability while managing system complexity through modular architecture.
Solution Approach 2:
The patent introduces intermediary processing layers that mediate between raw sensor data and fraud detection algorithms. These intermediaries pre-process and filter environmental data before it reaches the core detection system, reducing the complexity burden on the main system while maintaining high detection reliability through multi-stage analysis.
2Reliability
If real-time environmental data analysis is performed to prevent fraudulent transactions, then transaction security is improved, but processing time and computational resources increase
Solution Approach 1:
The system performs preliminary analysis of environmental data by continuously monitoring baseline biometric and environmental conditions before transactions occur. This preliminary action establishes normal patterns in advance, enabling faster real-time fraud detection during actual transactions without requiring extensive processing during the critical transaction moment.
Solution Approach 2:
The patent implements partial processing by analyzing only the most critical and relevant environmental data elements in real-time, while deferring less critical analysis. This selective approach maintains high transaction security for the most important detection factors while reducing overall processing time and computational burden.
Data Source
AI summary
Various examples are directed to systems and methods for detecting fraud. A financial institution system may receive, from a transaction device, a transaction authorization request describing a transaction to be drawn on an account of a user. The financial institution system may also receive, from the user computing device, environmental data describing an environment of the user and determine that the environmental data indicates an anomalous condition. Based at least in part on the determining, the financial institution system may decline the transaction.