Online gaming fraud problem is more pressing than ever

Dmitry Starostenkov talks about the basic anti-fraud rules and mechanics that should be taken into account by online poker operators.

Opinion.- Is fraud still an issue in online poker? EvenBet Gaming CEO Dmitry Starostenkov speaks on the basic anti-fraud rules and mechanics that must be used nowadays by online poker operators.

For Starostenkov, right now, the online gaming fraud problem is more pressing than ever. With the massive influx of unskilled players during the COVID-19 pandemic, iGaming has become an attractive target for different sorts of scammers.

Even in the mature markets, the frequency of fraudulent behaviour has increased: for example, in the USA, in Q2 2021, the industry saw 262 per cent more fraud attempts than in Q2 2020, according to anti-fraud company TransUnion data.

According to the executive, any emerging iGaming markets are leading in the global fraud targets ranking: Brazil, Mexico, Colombia, and Argentina often become homes for fraudsters to both steal and launder money.

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“Unfortunately, online gaming plays a notable role in their activity. That’s why at EvenBet Gaming, we have decided to turn to operators to explain how to prevent and fight these crimes harmful to users and reputation.”

Common fraud types

Starostenkov explained that the types of scams used in poker depend on the market. For example, in the mature and highly regulated markets, compliance fraud is becoming more and more regular.

A player who has previously reported gambling addiction problems and demanded self-restriction, registers under a new account to break the restriction rules and then blackmail an operator. If such a complaint reaches gambling authorities, an operator risks a notable fee or even a licence revocation.

In this context, he said that in the emerging online poker markets where the compliance rules are still to be set, the fraud types are more well-known:

• Payment scam (phishing, card payment fraud, account hacking, etc.)
• Multi-accounting
• Colluded games and team play
• Using bots

Know Your Customer: golden anti-fraud tool

“We suggest that every online poker operator introduce at least some basic KYC procedures even if the regulation and compliance policies don’t demand that.” He highlighted that verifying player location, age, and ID details before allowing playing for money can save an operator from specific fraud types such as multi-accounting and using bots and ease further investigation of the more complicated cybercrimes.

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For small projects, even manual verification by the moderator is sometimes enough if coupled with a good CRM that comes with the software. For the bigger ones, an automated KYC solution is necessary. “For example, our platform supports both simple KYC procedures made by the documents uploaded directly in the app and the integration with third-party solutions with a wide range of options – video verification, 3D verification, etc.”

Ensuring Fair Play: No Colluding

For this, Starostenkov recommended using at least two different tools:

• Automatic monitoring of players using the same IP, device, or location and reporting each suspicious case.
• Automatic monitoring of user behaviour to detect potential cases of chip dumping, groups of users that always play together, etc. This monitoring can prevent potential fraudsters from playing at the same table until a moderator verifies the players’ details.

“It is crucial to prevent illegal operations and money laundering through poker rooms (one user makes a deposit, dumps chips to another one, and the second makes a withdrawal). And indispensable to protect honest and especially new players from team play of the skilled poker fans using unfair methods to gain an advantage.”

Deep Behaviour Analysis to Detect Bots

According to the EvenBet Gaming CEO one of the most complicated and fruitful tools used in online poker is machine learning for behaviour patterns search. “It’s far from perfect and common now, but this is definitely the future must-have for online poker operators.”

“We can use machine learning to fight advanced bots using human-like logic: they can make mistakes, for example, lose money, even send messages in the chat. However, in the long run, there are clear patterns in their betting and interaction behaviour that are often unnoticed by simple anti-fraud engines and live moderators.”

According to Starostenkov, machine learning in online poker and iGaming, in general, can be used for other purposes as well: identifying risky behaviour to prevent addiction, collecting deep information on gaming habits for analytics and improvement, creating recommendations engines, and so on.

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“If we know that, for example, active high-bettors in poker often play roulette, participate in the tournaments at least once a week, tend to log into the game after 8 pm, rarely chat with other players, and go all-in having four of a kind or a better hand, we can do a lot to develop an even better gaming experience.”

Some companies are already implementing engines allowing them to analyse similar data, and this will become a trend in the months and years to come.

Basic Safety Rules

He explained that relying on automatic monitoring and using technology is an advantage. But he said that it shouldn’t replace basic account safety rules that must be forced by all the operators, no matter the size and the market.

As there are a lot of unskilled players now, it is necessary:

• strong password,
• verified and safe email,
• providing the true identity information to be able to fight criminal activities,
• keeping the financial information and bank card data secure.

As long as playing online is connected with paying online, all the safety rules apply to iGaming the same way as to e-commerce.