One effective approach is leveraging digital footprint analysis to spot fraud patterns often linked with bonus abuse, such as the use of VPNs, proxies or Tor networks, which may indicate attempts to evade detection. Additionally, device intelligence, which involves the continuous analysis of real-time device and behavioural data points can be employed to identify and block users who create multiple accounts from the same device or use suspicious setups.
By analysing sign-up patterns, deposits and withdrawals, operators can detect deviations from normal player activity that may signal potential abuse. Implementing advanced identity verification, such as document checks, biometrics and proof of liveness, adds another layer of protection. Of course, the challenge here is to ensure that these systems don’t add unnecessary friction to the sign-up process.
Tis is where the concept of dynamic customer friction through varying levels of Know Your Customer (KYC) checks based on risk assessment can be highly effective. With these systems in place, higher-risk activities or behaviours would trigger additional verification steps, making it harder for abusers to slip through. At the same time, genuine players can interact with the site as normal. Finally, using data analytics combined with machine learning algorithms – both blackbox and whitebox models – enables operators to identify patterns associated with bonus abuse that
might go unnoticed by the human eye. Over time, these systems improve detection as they learn from new data, becoming more adept at catching abuse early. Investing in these modern technologies is a great way to stay ahead of evolving bonus abuse tactics.
Why is it so important for bonus abuse to be tackled within the iGaming industry?
Bonuses are an important aspect of how providers promote themselves. Te sector carefully designs bonuses to appeal to a wide range of player profiles and market segments, considering regional preferences, regulatory requirements and technological advancements. Ultimately, these programs represent a significant investment and they must be protected.
Leading operators allocate up to 18 per cent of their gross revenue to bonuses, while for smaller operators, bonus programmes can make up an additional 25 per cent to 45 per cent of their overall spending. With such significant investment, it’s crucial that these programmes deliver value by driving customer acquisition and retention.
However, bonus abuse can severely undermine these efforts, causing operators to face serious financial losses.
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FRAUD PREVENTION
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