COMPLIANCE TECHNOLOGY
Accelerometers and Gyroscopes: These sensors track movement and orientation. If a device’s reported location suggests it’s stationary in a regulated zone, but the accelerometer data shows erratic motion inconsistent with natural movement, that discrepancy could indicate spoofing attempts. Sensors: Magnetometers can detect anomalies in magnetic fields that differ from what would be expected in a claimed geographic area, while barometers can help determine a user’s altitude. Coupled together, they paint a three-dimensional picture of the user’s surroundings, making it much harder for fraudsters to fake location data. Magnetometers and Barometric Wi-Fi and Bluetooth Signals: Triangulating Wi-Fi access points or analyzing nearby Bluetooth beacons offers another layer of assurance. Many urban areas have known Wi-Fi topographies that, when cross-referenced with a player’s claimed GPS location, help confirm precision down to tens of meters – or even better in some environments. By intelligently blending these signals, an advanced geolocation solution can effectively “fingerprint” a location. This ensures the platform can differentiate between a user inside a casino- residing state boundary and one just outside it or detect suspicious inconsistencies that signal location spoofing. Automated integration: letting the system do the heavy lifting One common challenge operators face is deciding when to perform geolocation checks. Should they verify a player’s location only at account creation, or before every bet? What if the player moves from one jurisdiction to another mid- session? Very few geolocation companies have automated geolocation solutions that removes this guesswork. The system continuously monitors and validates player location in the background – only stepping in when the data suggests something has changed or doesn’t fully add up. Operators no
longer need to hard-code triggers or run manual checks; the platform’s intelligent scheduling ensures location is always validated at the right times. For example, if a player starts a session in an allowed region and then physically crosses into a restricted area, the system can detect this shift in real-time – no operator intervention needed – and prevent further bets until the player returns to an authorized zone. This automated approach reduces operational complexity, streamlines compliance, and frees the operator’s IT and compliance teams to focus on more strategic initiatives. Fraud prevention through machine learning and AI Where money flows, criminal behavior and fraudsters follow. This often presents significant money laundering issues that require strong AML initiatives. Location spoofing, identity theft, and bonus abuse are just a few of the schemes that plague online gaming. While robust location-checking layers make it harder to feign being in a permissible area, advanced fraud detection requires recognizing patterns that aren’t immediately obvious to human eyes. This is where machine learning (ML) and artificial intelligence (AI) step in. Modern geolocation and compliance platforms analyze vast datasets of player behavior, environmental sensor data, and historical transactions. By training ML models on this aggregated information, the system can identify suspicious patterns – such as a single device logging in from multiple purported locations within impossibly short intervals, or betting patterns that do not match any legitimate player profile. Over time, these ML-driven systems become more adept at identifying subtle signals of fraudulent activity. For instance, they might detect that devices connected to certain clusters of VPN endpoints are far more likely to produce suspicious activity. As the system refines its understanding, it can preemptively flag suspicious accounts or freeze transactions before fraud has a chance to escalate.
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IMGL MAGAZINE | JUNE 2025
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