Fraud Detection via Multi-Machine Transaction Timing Analysis
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Solution Overview
Problem
Existing fraud prevention systems in casino environments face challenges in accurately distinguishing between legitimate and illegitimate transactions, often leading to erroneous determinations of fraudulent acts such as money laundering, particularly when illegal bills are inserted into gaming machines and quickly converted into bar code tickets or IC cards.
Innovation Solution
A fraud prevention system and information processing device that communicate with gaming machines to track and analyze the insertion and payout times of game values associated with unique information cards, determining fraudulent activity by identifying intervals between insertion and payout times across multiple machines, thereby preventing erroneous determinations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If fraud determination is performed based on information from a single gaming machine, then the device complexity is reduced, but the measurement precision of fraudulent act detection deteriorates leading to erroneous determinations
Solution Approach 1:
The patent merges data from multiple gaming machines into a unified fraud detection system. The information processing device collects insertion information and payout information from multiple gaming machines, associates them with the same information card identification, and performs comprehensive fraud determination by analyzing patterns across machines rather than isolating single-machine data.
Solution Approach 2:
The patent adds a temporal dimension to fraud detection by analyzing the time intervals between insertion and payout across multiple machines. Instead of only spatial analysis (single machine), the system examines the time sequence of transactions to identify suspicious patterns such as rapid insertion and payout cycles that indicate money laundering.
2Measurement precision
If the system monitors transactions across multiple gaming machines, then the fraud detection accuracy improves, but the loss of time for data processing increases
Solution Approach 1:
The system performs preliminary actions by continuously collecting and storing insertion information and payout information from multiple gaming machines in real-time. Data is pre-associated with information card identification and stored in a structured format before fraud analysis is needed, enabling rapid query and comparison when fraud detection is triggered without performing time-consuming data aggregation at the moment of analysis.
3Reliability
If the system collects detailed insertion and payout information from multiple machines, then the reliability of fraud determination improves, but the quantity of data to be processed increases
Solution Approach 1:
The system extracts only the essential elements needed for fraud detection from the transaction data. Instead of processing all transaction details, the system focuses on extracting information card identification, insertion amounts, insertion times, payout amounts, and payout times. This selective extraction reduces data volume while maintaining the reliability needed to identify fraudulent patterns such as money laundering.
Data Source
AI summary
In a fraud-prevention system used with gaming machines, fraud is detected using information as to amounts of value added to a gaming machine and the amount of time between adding the value and cashing out. Sequential instances of adding large amounts of value followed quickly by cashing out may be used to trigger a fraud alert, particularly where such behavior is repeated at multiple different machines in sequential order within a predetermined period of time.