Fraudulent Transaction Identification Using Hash Codes and Geocodes
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Solution Overview
Problem
Current methods fail to effectively identify suspicious or fraudulent transactions when repeated orders are shipped to the same address or location within a certain time interval, lacking a reliable mechanism to detect such patterns.
Innovation Solution
A method and system that create a hash code from an address and query a database to determine if the transaction is suspicious, using geocodes to identify potential fraud by associating each location with a unique geocode, allowing for the detection of repeated transactions and flagging suspicious activity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional transaction monitoring methods are used, then system simplicity is maintained, but fraudulent transactions cannot be detected when repeated orders are shipped to the same address within certain time intervals
Solution Approach 1:
The system performs preliminary actions by creating hash codes from addresses and geocodes before transactions occur, storing them in advance in a database. This allows the system to quickly compare incoming transaction addresses against pre-stored hash codes and geocodes to detect fraudulent patterns, rather than analyzing addresses in real-time during transaction processing.
Solution Approach 2:
The system introduces hash codes and geocodes as intermediary elements between the address and the fraud detection logic. Instead of directly analyzing raw addresses, the system converts addresses into hash codes for database lookup and geocodes for location-based comparison, enabling efficient and accurate detection of repeated transactions to the same location without requiring complex address parsing and comparison algorithms.
2Reliability
If address comparison methods are used to detect repeated orders, then fraud detection improves, but processing time increases due to database queries and geocode calculations
Solution Approach 1:
The system pre-calculates and stores hash codes and geocodes in the database before transactions occur. When a transaction is submitted, the system only needs to perform a quick hash code lookup and potentially a single geocode comparison, rather than calculating geocodes in real-time or performing complex address comparisons during transaction processing.
Solution Approach 2:
The system extracts only the essential elements (hash code and geocode) needed for fraud detection from the complete address information. By separating the address into its core identifying components and storing them independently in the database, the system can perform rapid lookups without processing the entire address string, significantly reducing query time while maintaining detection accuracy.
Data Source
AI summary
Embodiments of the present invention are directed to methods, systems and computer program products for identifying fraudulent transactions. In general, transaction information is inputted into the system and an address is received from such information. A database is then queried to determine if the address already exists in the database. A determination is made whether or not the transaction is suspicious in response to the address existing in the database entry. Alternatively, in response to the address not existing in the database entry, a determination is made as to whether or not the transaction is suspicious based on a geocode. A geocode is a geographic location or coordinates of an address.