How to Detect Fraudulent Chargebacks in the iGaming Industry

iGaming companies are no strangers to credit card fraud. Unscrupulous fraudsters and organized crime rings use them to abuse bonuses, create fake accounts, and exploit your games.

This is all linked to one main challenge: chargeback fees. Let’s look at why fraudulent chargebacks are a problem for the iGaming industry and explore potential solutions.

Why Are Chargebacks a Problem for the iGaming Industry?

Chargebacks are expensive. This is troublesome in every industry, but particularly in the iGaming industry, which is already considered high-risk by card networks – and, in fact, it tends to attract fraudsters in the first place.

Here is why reducing chargebacks is crucial:

  • You have to pay admin fees: The card networks’ liability shift means that you have to pay for chargeback fees.
  • Disputes are time-consuming: You’ll need a dedicated payment team’s time to claim your innocence when processing payments from stolen debit and credit cards.
  • Card operators may increase their processing fees: Cross the chargeback ratio for card payments, and you could potentially see yourself having to pay higher processing fees for all transactions – or even losing the ability to accept card payments.
  • You could even be blocked from the network: This is the worst-case scenario. If you fall afoul of the specific card issuer’s chargeback rules too often, you may have to look at alternative payment methods.

And this is before we even explore the problem of friendly fraud. Players familiar with the chargeback process will have no qualms about making a deposit, iGaming, and then claiming that their card was stolen or misused so they can recover all the funds they paid into their account with you.

While it’s possible to dispute the claims through the representment process, to be successful you will need to be armed with granular data logs and an in-depth knowledge of the appropriate card scheme policies and regulations. Winning a chargeback dispute can be as damaging as losing one.

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How Do You Detect Chargebacks in the iGaming Industry?

So how does an iGaming company detect these chargebacks before they happens? It must prepare itself with the right data and fraud prevention features. For example, you may consider the below:

  • A more thorough digital onboarding process: Chargeback fraud often follows a fraudulent signup, so preventing the latter can make a world of difference. You must be able to identify suspicious players before they begin depositing money into their accounts – and ideally before they even claim their signup bonus in the first place.
  • Better data at the signup and deposit stage: The card that’s used by a player can reveal a treasure trove of data about how risky your customer is. For instance, you can run a card BIN lookup and combine it with the person’s digital footprint, stemming from data enrichment, to get a complete user profile, complete with explainable assessment of how likely they are to pose a risk of fraud. This is also invaluable data to have on hand if you need to file a dispute.
  • Flexible and customizable risk rules: When it comes to chargeback fraud, a one-size-fits-all approach is the surest way to trigger too many false positives and upset legitimate players as a result. This is why taking control of your risk-scoring strategy via custom rules can let you automate fraud management with better results.
  • Machine learning for bespoke fraud rules: Finally, it’s also worth investigating if machine learning analysis can help reveal insights about fraudulent cases that analysts may have missed. Are they more likely to be fraudsters if they sign up with a bonus? What about the affiliate that brought them to your site? By looking at your past transactions, machine learning will come up with rules that serve to protect you in particular. You will also be presented with a confidence score for each rule.

Top 3 Custom Rules for Chargebacks in the iGaming Industry

We’ve looked at the ideal strategy. Let’s now examine concrete examples of risk rules you could deploy today to get a better handle on your iGaming chargeback fees.

#1: Credit Card and IP Location Don’t Match

Any fraud manager worth their salt will know how to leverage IP analysis. But it’s even more powerful when combined with a card BIN lookup, which can help you identify inconsistencies – specifically those relating to geolocation.

BIN Lookup

Below is how we would structure the SEON rule designed to look at a specific combination of data points: A card issuing bank in the US used by someone with a Russian IP.

Of course, this doesn’t necessarily mean we’re dealing with a fraudster. But sending the transaction to a manual review seems like the safest option, as a fraud analyst will be able to look at other factors, or may even decide to speak directly to the customer to verify their identity.

Card Country IP Mismatch

#2: Customer Is Quickly Increasing Their Number of Deposits

What would you do if you were an iGaming fraudster who found that a stolen credit card number in your possession is good for spending? You’d probably start betting more and more in order to extract your winnings as soon as possible.

This is why this custom rule looks at a 200% increase in deposits over a 24-hour period.

Here, again, it would be foolhardy to automatically block the next transaction, as there is always a chance this is a legitimate player. This is why we’d suggest having it increase the risk score by 20 points.

If other rules push the score over a certain threshold, you could then automatically freeze the account. In other words, it is not enough to ban the person in isolation, but paired with more red flags, it may provide sufficient justification.

200% Increase in transaction value

#3: User Has No Registered Social Media Profiles

In many cases, the best way to protect yourself from fraudulent payments is to identify suspicious accounts at the login stage. This is precisely what SEON’s email and phone lookup modules are designed to do, with a strong emphasis on gathering social signals to create a complete digital footprint.

This is the thesis: If a new player registration registers with an email address or phone number that has never been seen online, it is highly likely that the address was created specifically to commit fraud, and thus the profile is fraudulent.

This is why SEON helps iGaming leaders augment their risk screening by looking at 90+ social media and digital platform accounts to better gauge if the person appears legitimate.

Social Media Profiles
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How SEON Helps iGaming with Fraudulent Chargebacks

As a fully-fledged fraud detection and customer intelligence solution, SEON protects iGaming leaders against bonus abuse, multi-accounting, identity fraud, and, of course, chargeback fraud.

Here is why it works:

  • Create complete player profiles without friction: A single email address, phone number, card number, or device can reveal hundreds of important data points, including social signals unique to SEON, as well as fraud prevention mainstays.
  • Score risk transparently to streamline your protection: Automate approvals, declines, and manual reviews based on your unique risk management strategy. You can see in detail why a risk score was reached, including all the triggered rules. You can also easily add custom rules, or change the actions their trigger.
  • Improve your accuracy with machine learning: Feed the labeled results to our machine learning engine to receive better suggestions about risk signals you might have missed. It learns from your historical data to identify threats and patterns unique to your platform.

All this is available via flexible and modular APIs, so you can set up an entire iGaming fraud protection solution from scratch using SEON, or even add it to your existing stack to improve the accuracy of your current strategy.

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Author avatar
Tamas Kadar

Tamás Kádár is the Chief Executive Officer and co-founder of SEON. His mission to create a fraud-free world began after he founded the CEE’s first crypto exchange in 2017 and found it under constant attack. The solution he built now reduces fraud for 5,000+ companies worldwide, including global leaders such as KLM, Avis, and Patreon. In his spare time, he’s devouring data visualizations and injuring himself while doing basic DIY around his London pad.


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