Fraud Location Analyzer for Compromised Transaction Detection
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current systems lack an efficient method to determine where payment account breaches occur and to adjust fraud scoring for transactions at potentially compromised locations, making it difficult to identify and flag compromised payment accounts.
Innovation Solution
A computer-implemented method and system that uses a fraud location analyzer to determine a list of potentially compromised transaction locations, flag compromised payment accounts, and adjust future transaction fraud scores based on these locations by analyzing historical transaction data and calculating confidence scores for transaction locations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional fraud detection methods are used, then fraud scoring is performed based on limited transaction data, but the accuracy of fraud detection is insufficient and compromised locations cannot be identified
Solution Approach 1:
The patent segments the fraud detection process into multiple components: (1) identifying compromised transaction locations by analyzing patterns across multiple accounts, (2) segmenting accounts that transacted at compromised locations, and (3) applying enhanced fraud scoring specifically to these segmented accounts. This segmentation allows the system to focus resources on high-risk accounts and locations, improving detection accuracy without processing all transactions uniformly.
Solution Approach 2:
The system performs preliminary actions by proactively identifying and flagging compromised transaction locations before fraudulent transactions occur at those locations. By analyzing historical transaction data and identifying locations associated with compromised accounts, the system prepares a list of compromised locations in advance, enabling faster and more accurate fraud detection when new transactions are submitted.
2Reliability
If comprehensive transaction analysis is performed across all accounts, then fraud detection coverage is improved, but system complexity and computational resources increase
Solution Approach 1:
The patent applies partial action by focusing fraud analysis on specific high-risk segments rather than all accounts. The system identifies compromised locations and then applies enhanced scrutiny only to accounts that transacted at those locations. This partial approach maintains high reliability for detecting fraud at compromised locations while avoiding the excessive complexity of analyzing every transaction across all accounts with the same level of intensity.
Solution Approach 2:
The system introduces an intermediary layer between transaction processing and fraud scoring. The intermediary component identifies compromised locations and creates a mapping between locations and accounts, which then feeds into the fraud scoring system. This intermediary structure simplifies the overall system by decoupling the complex location analysis from the transaction processing, making the system more manageable and scalable.
3Speed
If real-time fraud scoring adjustment is implemented for all transactions, then fraud detection responsiveness is improved, but processing time and computational load increase
Solution Approach 1:
The system performs preliminary analysis to identify compromised locations and pre-calculates risk associations before real-time transaction processing. By preparing the list of compromised locations and identifying accounts that transacted there in advance, the system reduces the computational burden during real-time processing. When a transaction is submitted, the system only needs to check against the pre-identified compromised locations and adjust scores for affected accounts, significantly reducing processing time.
Solution Approach 2:
The patent applies local quality by implementing enhanced fraud scoring adjustments only for transactions at compromised locations rather than uniformly across all transactions. The system identifies specific locations and accounts that require enhanced scrutiny and applies localized fraud score adjustments only to those specific cases. This localized approach improves responsiveness for high-risk transactions while minimizing the impact on overall processing time for low-risk transactions.
Data Source
AI summary
A computer-implemented method for enhancing fraud detection based on transactions at potentially compromised locations is provided. The method includes determining a list of potentially compromised transaction locations, storing the list of potentially compromised transaction locations, and receiving from a first transaction location a first authorization request message for a first transaction. The first authorization request message is associated with a first payment account. The method also includes determining the first transaction location based on the first authorization request message, determining if the first transaction location is in the list of potentially compromised transaction locations, and if the determination is that the first transaction location is included in the list of potentially compromised transaction locations, flagging the first payment account as potentially compromised so that a fraud score for a future transaction is associated with the first payment account is adjusted based on the potentially compromised flag.