AI in Fraud Detection and Prevention in Online Gaming

How AI Helps Detect Fraudsters in Online Gaming

Fraud prevention is an integral part of online gaming platforms. It helps protect players and the platforms from data loss and financial setbacks. Artificial intelligence is now a powerful tool for anti-fraud measures. The technology makes it safe for players to use online gaming platforms and payment options. Methods like casino PayForIt and others ensure players can transact safely.

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“The benefits of artificial intelligence in the gambling industry are multifaceted”, says Jessica Langille, an expert in the online gambling sector at Slotozilla. From identifying false positives to improving efficiency and player experience, the technology has many advantages. Here is an in-depth perspective.

Current Trends in Online Gaming Fraud

The online gaming market is rapidly growing, with a projected revenue of US$29.48 billion in 2025. Despite regulatory hurdles and threats from cyberthefts, the industry shows great resilience and potential.

A Sumsub report reveals that the maximum number of frauds (41.9%) occurs at the deposit stage, and the fraud rate has doubled since 2023. Some of the recent trends in online gaming fraud include:

Account hijacking: This is a persistent threat that hackers use to steal personal info, currency, and in-game items.
In-game currency theft: Hacking, botting, and scams are used by cybercriminals to steal in-game currency.
Deepfakes: AI (Artificial Intelligence) is a highly valued tool used in casinos for risk management and analysis of real-time trends. However, deep fake, a manipulated media created with AI, can create false hacking or cheating episodes. It can impersonate developers or support personnel, causing havoc.

How AI Detects Fraud

Various methods are used for fraud detection using artificial intelligence. Here are some of the popular and proven methods.

Machine Learning & Pattern Recognition: AI analyses user actions, like their login frequency, game abandonment, and other patterns. The technology compares the actions with established normal behaviour profiles to identify deviations. Cheating, bot activity, and other fraudulent activities are flagged by these deviations.
Real-Time Monitoring & Alerts: User data is analysed by AI models in real-time, and they are compared with learned patterns. This helps to identify suspicious events quickly and take immediate action.
Identity Management and Verification: Player identities are verified using metadata analysis of ID documents. The technology also checks for digital tampering.
Detecting Synthetic / Generated Threats: Artificial intelligence systems can help identify forgery in identity documents. The technology compares the data with biometric details to ensure authenticity. Fraudsters are thus prevented from using synthetic identities and generating threats.

Benefits of Using AI in Fraud Detection

You can gain many advantages by using AI in detecting fraudulent activity in online platforms. Here are a few of the important benefits.

Minimize false positives: By using data to continuously learn user patterns, AI models increase their accuracy. It also reduces the flagging of legitimate users as fraudulent. This helps in bolstering security.
Detect fraud in real-time: By real-time monitoring, AI helps to flag malicious activities, which helps in the timely prevention of financial losses.
Improve efficiency: Data monitoring is an automated process that frees humans to concentrate on complex cases and fraud investigations.
Improve user experience: With a safe and fair gaming atmosphere, platforms can increase the trust players have in them. This increases retention and encourages responsible gaming methods.

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Challenges & Risks

Although the benefits are several, AI comes with its own set of challenges that need to be addressed. These include:

Privacy

Since huge amounts of user data is used for analysing patterns and detecting fraud, it can cause doubts regarding data protection and other privacy related rules like GDPR.

Fairness

It is vital to train the AI models properly, failing which it can lead to discriminatory decisions. This could target specific players in an unfair manner.

Compliance

Not all jurisdictions accept the use of AI for compliance-related safety measures. Clear-cut frameworks for regulations are necessary to ensure safety.

Implementation Considerations for Gaming Platforms

The upsides of using AI for fraud detection and prevention are plenty. However, due to risks like privacy, fairness, and compliance, the method should be used cautiously. Platforms should address risks like user privacy and algorithmic bias.

It is important for gaming platforms to use ethical methods of deployment. This will help protect user privacy while ensuring strong fraud prevention measures. The use of AI also involves consistent monitoring and optimization of algorithms. This will improve fairness and effectiveness.

Case Example

Gaming companies can receive plenty of benefits by adopting AI and ML technologies. Here is an example.

Quago is a gaming company that uses artificial intelligence to reduce cheating and fraudulent activity. It uses a behavioural analytics platform that analyses sensor data of the players’ devices. The data reveals patterns that help the company identify and provide actionable insights. The company has registered a significant performance boost and scalability.

Low cost and savings: They were also able to achieve 4x faster SQL queries, leading to low server costs for users and saving 10 million dollars and more costs by reducing in-app purchase loss due to fraud. Nearly a 25% reduction in server costs of customers was possible as fraudulent activities churn more than normal player activity, which requires more energy from the gaming server.
Scalability: Due to the accurate and quickly available results, it is easier for a platform to make analytical insights and provide efficient real-time results.
Improved UX: User experience is vastly improved thanks to the mitigation of fraud and instilling confidence in players. This will increase loyalty.

Future Outlook

In the future, more advanced artificial intelligence processes will be used to future-proof strategies that platforms use for fraud prevention. Some of the future trends that shape the sector include:

Real-time action: In this era of instant payment methods, it is more important than ever to use real-time fraud prevention methods. AI systems will be equipped to analyse transactions as they happen, identify threats and suspicious activities immediately, and prevent fraud.
Robotic processes: The combination of AI with RPA (Robotic Process Automation) and advanced analytic systems can improve automation. This can reduce manual participation and retain accuracy while leaving fraud teams to concentrate on complex issues.
Risk scoring: The dynamic scoring system used by AI systems is more reliable than conventional models. The system will be able to adapt to varying behaviour patterns and transactions. By this advanced method, it is easier to integrate fraud detection processes with market trends and customer behaviour patterns.
Pooling resources: Businesses can share user data and analytical insights via fraud networks. This can detect fraud patterns and help protect a wide range of industries by enhancing the collective defence system.
Scalability: To ensure fraud prevention measures are geared up to the changing player environment, scalable and integrated platforms need to be built. Constant learning and adaptation will help platforms stay a step ahead of the competition.

Conclusion

Emerging technologies help us combat the growing threat of fraudulent activities in online gaming. Advanced technologies, such as AI, are a significant boon to the industry. They can help build a strong defensive mechanism that works in multiple ways. Besides preventing fraud, it can boost efficiency and build customer confidence.