7 Ways AI Reduces Payment Fraud in iGaming

AI is transforming how Malta's iGaming industry fights payment fraud. Here's a quick look at how AI tools are helping operators and players stay secure:

• Live Transaction Monitoring: AI analyses real-time gaming transactions, flagging unusual behaviour like sudden large deposits or logins from multiple locations.

• User Pattern Analysis: AI learns typical player behaviour to detect anomalies such as bot-like actions or multi-accounting.

• Unusual Activity Detection: Tracks deviations in deposits, withdrawals, or timing to spot suspicious activities.

• Risk Score Calculation: Assigns risk levels to transactions based on factors like user history, transaction size, and location.

• ID Verification: Combines document checks and biometrics (e.g., facial recognition) to prevent identity theft and fake accounts.

• Chargeback Prevention: Predictive tools identify potential fraud before it results in costly chargebacks.

• Smart Fraud Response: AI adapts and responds to new fraud tactics by monitoring and updating risk models in real time.

Malta's iGaming sector, processing millions of euros daily, benefits significantly from AI's ability to prevent fraud, reduce false positives, and protect both operators and players.

How Operators Can Stay Ahead of Fraud in iGaming

Common Payment Fraud Types in iGaming

Understanding the main types of fraud in iGaming is crucial, especially as fraud cases have risen by 30% year-over-year. Below are some of the most common fraud tactics affecting this industry.

Account Takeover (ATO) Fraud
This occurs when fraudsters use tools like VPNs, Tor browsers, and incognito modes to access player accounts without permission. Once inside, they steal account balances and misuse payment methods.

Multi-Accounting and Gnoming
Multi-accounting happens when individuals create multiple accounts to exploit bonuses or manipulate game outcomes. Gnoming is a variation where accounts are set up using fake or borrowed identities. Alarmingly, 92% of fraudsters use email addresses that have never appeared in a data breach.

Bonus Abuse
Bonus abuse can lead to major losses for operators, with research showing that up to 15% of revenue is lost to promotional misuse. Fraudsters often rely on multi-accounting and other evasion strategies to repeatedly claim bonuses.

Chargeback Fraud
This type of fraud is particularly expensive. For every €100 lost to chargebacks, the actual cost balloons to €207 when factoring in fees and refunds. Fraudsters often use synthetic identities, combining stolen personal data with credit card details.

"SEON significantly enhanced our fraud prevention efficiency, freeing up time and resources for better policies, procedures and rules." - Chief Compliance Officer, Soft2Bet

These types of fraud can lead to hefty fines, with penalties reaching €23.81 million in 2023. To safeguard both operators and players in Malta's growing iGaming industry, combining traditional security tools with advanced AI-driven solutions is essential. As fraud tactics evolve, AI-based detection and prevention remain critical.

1. Live Transaction Monitoring

In Malta's iGaming sector, live transaction monitoring powered by AI serves as a critical line of defence against payment fraud. This technology works by analysing player transactions in real time, identifying normal behaviour patterns and flagging anything unusual that might signal fraudulent activity.

How AI Transaction Monitoring Works

AI builds a unique profile for each player by studying key behaviours, as outlined below:

When a transaction deviates from these established patterns, the system flags it for review immediately - without delaying legitimate transactions. This ensures a balance between security and user experience.

Proven Results

One online casino reported a 30% drop in fraudulent transactions within just six months of using AI fraud detection tools. The system effectively differentiated between legitimate and suspicious activities, minimising false positives.

Adapting to New Threats

The AI system continuously refines its models by learning from new data, allowing it to spot emerging fraud tactics. For example, a sports betting platform successfully reduced bonus abuse by identifying subtle shifts in betting behaviour. This ongoing learning helps the system stay ahead of evolving threats.

Immediate Response Actions

When suspicious activity is detected, the AI system can take quick action to minimise risks, such as:

• Temporarily suspending transactions

• Requiring additional verification

• Alerting fraud prevention teams

• Blocking suspicious accounts

• Flagging transactions for manual review

These actions help protect both the platform and its users while ensuring smooth gameplay for legitimate players.

2. User Pattern Analysis

AI-powered tools are transforming the fight against iGaming fraud by analysing user behaviour. By studying data, AI creates a baseline for typical player actions, making it easier to spot unusual activity. Here's a breakdown of key behavioural metrics AI examines:

Real-World Impact

AI has proven its effectiveness in reducing fraud. A 2021 study showed that platforms using AI for pattern analysis cut suspicious transactions by up to 40%. Beyond just reducing flagged transactions, AI excels at uncovering intricate fraud schemes.

Advanced Detection Capabilities

AI can pinpoint complex fraud patterns, such as:

• Multiple accounts showing overlapping betting behaviours

• Bot-driven gameplay identified through consistent action timing and precision

• Unusual deposit and withdrawal behaviours

• Geographic access patterns that don't align with normal user activity

Learning and Adapting

AI systems continuously learn and adapt. For instance, a European betting platform used AI to detect coordinated suspicious bets and swiftly suspended the related accounts.

Behavioural Biometrics

AI also integrates biometric analysis to confirm user identity. By studying typing patterns, mouse movements, touchscreen interactions, and decision-making speeds, platforms can verify whether a user is genuine. This layer works alongside transaction monitoring. For example, AI can flag activities like "round robin" betting or large deposits followed by quick withdrawals, which may indicate money laundering. This dual approach strengthens overall platform security.

3. Unusual Activity Detection

AI systems are highly effective at spotting suspicious transactions by analysing and recognising deviations from a player's usual behaviour. These systems process vast amounts of real-time data, allowing them to detect even subtle anomalies. This works hand-in-hand with live transaction monitoring to enhance fraud detection.

Real-Time Analysis Components

AI evaluates various transaction factors simultaneously, making it easier to identify unusual patterns:

By analysing these elements, AI systems refine their models over time to keep up with changing fraud tactics.

Advanced Detection and Impact

AI-based detection tools have proven their value in fraud prevention. They enhance platform security by continuously monitoring activity and spotting complex patterns, all while keeping false positives to a minimum.

Continuous Learning and Adaptation

Modern AI systems tackle the challenge of evolving fraud tactics - known as concept drift. By constantly updating their understanding of unusual activity, they stay effective even as fraudulent methods change. This approach reflects a shift toward intelligence-driven security in iGaming.

Key behaviours monitored by these systems include:

• Transaction velocity: Sudden changes in deposit or withdrawal frequency

• Amount patterns: Unusual variations in transaction amounts

• Geographic anomalies: Transactions from unexpected locations

• Time-based irregularities: Activity outside typical playing hours

When suspicious activity is flagged, the AI system can act immediately. Responses may include temporary account suspension, extra verification steps, manual review alerts, or blocking transactions in real time. These measures are part of a broader AI-driven strategy to prevent fraud effectively.

4. Risk Score Calculation

AI-driven risk scoring systems in iGaming evaluate numerous data points to estimate the likelihood of fraud. This method refines earlier detection techniques, offering a more precise approach to fraud prevention.

Core Risk Factors

AI analyses several critical components when determining risk scores:

Dynamic Scoring System

AI systems constantly refine their scoring models with updated data. These scores adapt in real-time to detect new fraud trends. For example, one online casino saw a 30% drop in fraudulent transactions within six months of using AI-powered risk scoring.

Real-Time Assessment

The system evaluates transactions instantly by analysing:

• Historical transaction patterns and speed metrics

• Device fingerprinting to detect shared devices across accounts

• Location data to verify where transactions originate

Automated Response Thresholds

Based on real-time insights, transactions are categorised into risk levels. Low-risk transactions continue as usual with standard monitoring. Moderate-risk ones may require extra verification, while high-risk transactions are automatically blocked and flagged for manual review to investigate potential fraud.

5. ID Verification Improvements

AI plays a key role in securing the iGaming industry by verifying user identities and stopping unauthorised access. This method combines document checks, biometrics, and ongoing monitoring to combat fraud effectively.

Document Verification Made Smarter

AI examines identification documents to check their validity and detect built-in security features. This process ensures that requirements like age and residency are met almost instantly. For example, platforms such as Grand Casino Luzern use this automated system to swiftly validate documents and block illegal access attempts.

Adding Biometrics to the Mix

Biometric technology strengthens identity checks by introducing dynamic, hard-to-fake measures:

Keeping Watch in Real Time

In one case, a UK betting company uncovered a fraud scheme involving 5,900 fake document scans used to create false identities. This highlights how ongoing monitoring is crucial in detecting and stopping such activities.

Multi-Factor Authentication (MFA)

AI-powered MFA combines various layers of security - like passwords, one-time codes, and biometrics - to validate users. It also keeps an eye on unusual login behaviours, ensuring potential threats are flagged and addressed quickly.

Evolving Security Measures

AI systems improve with each verification, learning to detect new fraud techniques over time. The identity verification market is expected to grow to €21.07 billion by 2028, showing just how essential these tools have become for iGaming security.

6. Chargeback Prevention

AI is changing how iGaming platforms tackle chargeback fraud, moving from reactive steps to a more proactive approach. By processing large amounts of transaction data in real-time, AI can spot potential fraud before it escalates into expensive chargebacks.

Predictive Analysis

AI uses advanced algorithms to create behaviour profiles for each user. It looks at various indicators, such as:

This analysis provides a solid foundation for detecting irregularities in real-time.

Real-Time Monitoring

With real-time monitoring, AI processes vast amounts of data to detect even the smallest deviations in user behaviour that could indicate potential chargeback fraud.

Demonstrated Effectiveness

iGaming platforms using AI-powered detection systems have reported noticeable drops in fraudulent activities. These systems analyse player actions and transaction trends to catch fraud early.

Automated Responses

When suspicious activity is detected, AI takes immediate action by:

• Pausing transactions temporarily

• Flagging accounts for further review

• Requiring additional verification steps

• Blocking risky payment methods

Constantly Improving Detection

AI systems are designed to learn and adapt. They improve over time by:

• Identifying new fraud tactics

• Adjusting to new risks

• Enhancing detection accuracy

• Minimising false alarms

This continuous improvement ensures the system remains effective against evolving threats, making it a strong tool for fraud prevention in the iGaming sector.

7. Smart Fraud Response

AI has advanced beyond just detecting and verifying fraud - it now delivers intelligent responses to combat evolving schemes effectively.

Modern AI systems don't just spot fraud; they continuously learn from new patterns. This ongoing refinement helps platforms stay ahead of threats while keeping operations secure.

Continuous Learning

AI processes vast amounts of transaction data in real time, identifying new fraud patterns and adapting its strategies. This constant learning strengthens platform security and keeps it resilient against emerging risks.

Flexible Response Mechanisms

AI's response systems are designed to evolve. Here's how they work:

These mechanisms ensure fraud prevention strategies are effective across all transaction stages.

Improved Security Measures

The global online gambling market was worth €58.23 billion in 2022 and is projected to grow by 11.7% annually through 2030. AI plays a key role in bolstering platform security by:

• Analysing real-time transaction data

• Spotting new fraud patterns

• Automatically adjusting security protocols

• Using synthetic data to improve training models

Real-World Applications

AI's capabilities go beyond basic fraud detection. For example, a sports betting platform used AI for real-time tracking of betting activities, which significantly reduced bonus abuse and multiple account creation. By processing large datasets and acting immediately on suspicious behaviour, this system protects both operators and players from sophisticated fraud attempts.

Fluid's AI Fraud Prevention Tools

Fluid offers advanced AI tools designed to tackle fraud effectively. These tools use cutting-edge algorithms to detect suspicious activities, helping businesses reduce financial losses and maintain trust. By analysing vast amounts of data, the system can identify patterns and flag unusual behaviour in real-time.

This means businesses can act quickly to prevent fraud before any damage occurs, ensuring smoother operations and greater security for their customers.

Advantages of AI Fraud Prevention

AI-powered fraud prevention systems are changing the way businesses protect themselves against fraudulent activities. These systems leverage advanced algorithms to detect and stop threats more effectively than traditional methods.

AI can process vast amounts of data in real time, identifying unusual patterns or behaviours that might indicate fraud. For example, it can flag a suspicious transaction if it deviates from a customer's usual spending habits. This quick analysis helps businesses act immediately, reducing potential losses.

Another key advantage is the ability to continuously learn and improve. AI systems adapt to new fraud tactics, staying one step ahead of criminals. This makes them a reliable tool for combating ever-evolving threats.

Additionally, AI fraud prevention tools can reduce false positives. By accurately distinguishing between legitimate and suspicious activities, these systems save time and improve customer experience. This is especially important for industries like banking, where trust and efficiency are critical.

In short, AI fraud prevention offers businesses a smarter, faster, and more reliable way to protect themselves and their customers.

Malta-Specific Information

Malta, a small island nation in the Mediterranean, is known for its rich history, stunning architecture, and vibrant culture. Despite its size, Malta offers a unique mix of historical landmarks, modern attractions, and natural beauty.

The official currency is the euro (€), and the country follows the metric system for measurements. Temperatures are typically measured in Celsius, and Malta enjoys a Mediterranean climate with hot summers and mild winters. Time is observed in Central European Time (CET), with daylight saving time adjustments.

English and Maltese are the official languages, making communication easy for both locals and visitors. Malta's strategic location has shaped its history, with influences from various cultures, including Phoenician, Roman, Arab, and British. This blend is evident in its cuisine, traditions, and architecture.

From the iconic Azure Window (now collapsed but still a symbol of Malta) to the bustling streets of Valletta, Malta offers something for everyone. Whether you're exploring ancient temples or enjoying a sunny day at the beach, the island's charm is undeniable.

Conclusion

Wrapping up, we've explored the key points and insights presented in this discussion. Each element ties into the broader context, offering practical takeaways and a deeper understanding. Whether you're applying these ideas immediately or reflecting on them for future use, the information here is designed to support your goals effectively.

FAQs

How does AI detect and prevent fraudulent transactions in real-time within the iGaming sector?

AI leverages real-time monitoring to analyse transactions as they occur, identifying unusual activities such as abnormally large deposits or withdrawals that deviate from a player's typical patterns.

By employing behavioural analytics, AI can recognise subtle deviations from a user’s established habits, such as changes in login locations or device usage, which may indicate fraudulent activity. Additionally, advanced anomaly detection algorithms flag irregularities in payment data, helping to prevent unauthorised transactions before they are completed.

These capabilities allow AI to safeguard both users and operators in the iGaming industry by ensuring secure and seamless payment processes.

What challenges does AI face in keeping up with evolving fraud tactics in the iGaming industry?

AI in the iGaming sector faces several challenges when adapting to constantly evolving fraud tactics. One key issue is the need for high-quality data to train AI models. Without sufficient or accurate data, these systems may fail to identify new and sophisticated fraud patterns effectively.

Additionally, setting up and maintaining AI systems requires specialised technical expertise and resources. This can be particularly demanding for smaller gaming companies that may lack the infrastructure or budget to implement advanced AI solutions. Despite these challenges, AI continues to play a crucial role in enhancing security and reducing fraud in the industry.

How does AI-based ID verification improve security in iGaming, and are there any challenges?

AI-based ID verification strengthens security in iGaming by automating the process of confirming user identities. It uses tools like automated document checks and biometric verification, such as facial recognition, to detect and prevent fraud, including account takeovers and bonus exploitation. This ensures a safer environment for both players and operators.

However, challenges remain. Fraudsters may attempt to bypass these systems, and the effectiveness of AI-based verification depends on the quality and robustness of the technology in use. While highly effective, no system is entirely foolproof, making continuous updates and monitoring essential for maintaining security.

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