IGaming operators are magnets for fraudsters – and there is no better stage to catch them than during the signup or digital onboarding process.
Let’s explore why it’s so crucial and the kind of risk management strategies you should deploy at that stage.
Why the iGaming Digital Onboarding Process Matters
iGaming operators have to be smart about how they acquire new users. Paid ads are still a touchy subject in many jurisdictions, and relying on affiliates while preventing affiliate fraud in iGaming can be challenging.
To make matters worse, bonuses attract fraudsters who create multiple accounts to exploit your marketing programs. But the consequences go beyond simply losing money.
Your company could face:
- losses to revenue
- higher rates of ID fraud
- AML and KYC fines and penalties
- licensing concerns related to compliance with AML and other legislation
- loss of customer trust – especially if collusive players infiltrate your tables
- chargebacks and issues with card networks
- skewed customer segmentation data that throws a spanner into your marketing efforts
- stalled growth
All of the above combined could seriously damage your operations, not to mention reduce your bottom line and make you less competitive – in an environment that’s already highly challenging too.
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What Makes a Safer iGaming Digital Onboarding Process?
Securing your iGaming company’s digital onboarding requires the deployment of a variety of tools and strategies. Let’s look at a few of them here:
- Data enrichment: When customers arrive on your site, they want to signup as quickly as possible. This creates a challenge: How do you learn more about who they are without putting in place friction that could lead to customer churn? The answer is to deploy data enrichment tools, which can take a single data point and return a treasure trove of information. An IP lookup tool, for instance, can point to suspicious or harmful connections. More importantly, looking at social media accounts can help you instantly flag users with a very small digital footprint – which is highly suspicious.
- Custom risk rules: All the data collected in the previous step is only good if you can leverage it as a risk management mechanism. This is precisely what custom risk rules allow you to do, going beyond simple static rules that trigger too many false positives.
- Dynamic friction: An advantage of customizable fraud prevention is that it allows you to measure risk however you see fit, and tweak it according to your risk appetite. This has another benefit: Low-risk users can signup without a hitch. Medium-risk users need to be manually reviewed with extra checks, while high-risk users are automatically blocked. This friction is dynamic because it is only applied when there is something to gain.
- Spotting connections between users: An advantage of collecting more data at the signup stage is that you can identify suspicious connections between players. Device fingerprinting is particularly effective here.
iGaming operators that are taking their onboarding security seriously will already be employing some, or all of these techniques.
Top 3 Custom Rules for Digital Onboarding in iGaming
Now that we’ve looked at general strategies and techniques, let’s dive deeper into specific risk rules you could deploy at your iGaming company today to keep your operations, systems and players safer.
#1 Identify Users Who Share the Same Password
When it comes to iGaming fraud, spotting multi-accounting is a key way to reduce bonus abuse, ID fraud, and even chargeback fraud. This is why establishing connections between users as soon as possible can stop potential fraud at the onboarding stage.
To detect connections, we look at similarities. For example, while there are legitimate reasons why users might share the same browser configuration, it becomes a lot more suspicious if their passwords are also identical.
Within the SEON admin panel, this is identified by looking at hashes – sets of encrypted data that act as unique identifiers. Here is an example of a user whose specific browser configuration and password already have already been seen on your site:
We might not want to automatically block the onboarding, but a manual review is strongly recommended. This is why we increase the fraud score – in this case, by 5 and 4.71 points, respectively, but these rules can be amended at will to suit your risk appetite.
#2 User Is Hiding Their Browser Cookies
Sometimes, fraudsters can draw attention to themselves by making mistakes (like in the example above). Other times, they are spotted trying to evade detection. This is precisely what happens if you deploy a rule that looks at a suspicious lack of browser cookies.
There are two potential scenarios here. One, your user is genuinely a privacy enthusiast who does not like being tracked across websites. Two, it is someone who is actively trying to hide their online traces, possibly using one of the following spoofing tools that fraudsters prefer.
Here again, you want to increase suspicion without instantly rejecting the onboarding. Your risk team should weigh the pros and cons of letting them sign up, ideally by taking into account several other parameters, as flagged by SEON.
#3: The Player’s Card Country and IP Do Not Match
We’ve looked at rules to be deployed during the signup stage. However, for many iGaming companies, the first money deposit is also considered a key part of onboarding – for a good reason.
This is a tremendous opportunity to weed out unwanted players whose card details reveal suspicious information. A good example is a Russian player who deposits funds with a prepaid US card.
These checks are the perfect job for a card BIN lookup tool. It will let you know the type of card they are using, the issuing bank country, and more.
What is deemed suspicious will depend on the idiosyncratic risk at your iGaming company, but it is safe to assume that the example above should raise flags for many operators.
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How SEON Helps iGaming with Digital Onboarding
SEON is quickly becoming the fraud prevention favorite for a number of iGaming leaders.
This is thanks to:
- our alternative to ID verification, which reduces friction and risk by looking at social signals
- the AML API, which lets you check key lists from the same dashboard
- powerful risk-scoring features, including machine-learning suggestions
- whitebox reasoning, which assists your manual reviews and improves your automatic risk mitigation
All of the above is available in a completely flexible package, allowing you to deploy SEON as a full end-to-end solution, or to augment your current risk management toolkit.
Want to learn more? Get in touch today