Outcome

Deploying device fingerprinting, affiliate traffic monitoring, and payment method linkage analysis identified a coordinated network of 2,600 fraudulent accounts. The accounts were closed, the responsible affiliates were removed from the program, and bonus abuse reduced to a level that delivered €500,000 in annual savings.

Client Context

An online casino operator was registering an increase in bonus abuse volumes and a pattern of low-value depositing users who were not converting into the behavioral profile of normal players.

The operator’s affiliate program was generating traffic. The problem was that a portion of that traffic was not organic acquisition. It was structured, coordinated, and designed to extract bonus value at scale.

The affiliate fraud was not visible at the individual account level. Each account, in isolation, could be read as a marginal player. The pattern only became legible at the network level, across devices, payment methods, and affiliate source attribution simultaneously.

The operator engaged KYZEN to identify whether the abuse was coordinated, trace it to its source, and build the detection infrastructure to prevent recurrence.

Challenges

Affiliate fraud operates below the threshold of account-level risk detection. Individual accounts do not trigger standard fraud rules because individually, they are not behaving fraudulently at scale.

This created several compounding constraints:

• No device-level linkage analysis in place, making it impossible to identify shared device infrastructure across accounts registered under different identities.
• Affiliate traffic not segmented or monitored by quality metrics, leaving no visibility into which affiliate sources were generating abuse-pattern behavior.
• Payment method relationships not mapped across accounts, concealing the shared financial infrastructure that coordinated fraud networks rely on.
• Bonus abuse volumes rising without a traceable origin, making remediation reactive and incomplete.

This resulted in:

• Coordinated accounts operating undetected within the affiliate traffic stream.
• Bonus budgets being systematically extracted without conversion value.
• Affiliate program costs running against traffic that was generating negative margin.
• No mechanism to identify or remove the affiliate sources responsible for fraud network referrals.

The Approach

Detection was rebuilt at the network level, not the account level. The investigation was structured to surface coordination patterns rather than individual account flags.

Key changes included:

• Device Fingerprinting: A fingerprinting tool was deployed to establish device-level identity linkage across the account base, identifying shared hardware and browser infrastructure used to register and operate multiple accounts under different identities.
• Affiliate Traffic Monitoring: Structured monitoring reports were built to segment affiliate traffic by behavioral and risk metrics, making the quality and fraud-pattern concentration of each affiliate source visible for the first time.
• Payment Method Linkage: Accounts were cross-referenced by payment method usage, surfacing links between accounts through shared payment method usage.

The combination of device identity, affiliate source attribution, and payment method linkage made the network structure visible in a way that single-signal detection could not.

Results

The detection framework identified the network, enabled a structured remediation, and produced measurable financial impact.

• A coordinated network of 2,600 fraudulent user accounts was identified and closed.
• Affiliate sources responsible for the fraud network traffic were removed from the program.
• Bonus abuse reduced to a level that delivered €500,000 in annual savings.
• Detection infrastructure remained in place to identify recurrence or new network formation.

Operational Takeaway

Affiliate fraud is a procurement problem disguised as a fraud problem. The operator is purchasing traffic. Some of that traffic has been structured to extract value rather than generate it. Standard account-level risk controls will not catch it because the fraud is not in the account. It is in the network that produced the account.

The operators who close these networks are the ones who monitor affiliate traffic as a risk surface, not just an acquisition channel. Device linkage and payment method clustering are not fraud tools in isolation. They become fraud tools when they are applied across the affiliate source layer simultaneously. Until that analysis exists, the program continues to fund the abuse.