Fraud Prevention Casinos Face Rising Costs from Over-Blocking

Aggressive fraud checks hurt high-value players

On 23 October 2026, Frogo CEO Volodymyr Todurov warned that tightening fraud controls can backfire on operators that rely on high-spending customers. Todurov said that players who travel frequently, deposit large sums, or use multiple cards often trigger the same alerts that flag stolen-card tests. When a casino blocks such accounts, it loses a significant revenue stream and forces players to seek competitors.

KYC is the most targeted layer

Todurov highlighted that KYC checks are now the primary target for fraudsters. AI-generated documents and deepfake face-swapping allow criminals to mimic legitimate identities with increasing precision. Operators that rely on static document checks are vulnerable to these sophisticated attacks.

The hidden cost of loss prevention

Fraud controls are often measured by the amount of money stopped. Todurov argues that this metric ignores the resources required to achieve it. Manual checks drain staff time, and automated systems that block too many transactions can erode customer trust. A single false positive on a high-value account can cost more in lost revenue than the fraud prevented.

Operational efficiency matters

Todurov proposes a three-pronged model: direct loss prevention, analyst throughput, and the impact on legitimate customers. The second metric—monthly active users per analyst—shows whether automation frees specialists to tackle complex threats. The third metric, “automated withdrawals built on the presumption of innocence,” links smoother payouts to higher lifetime value.

Real-world consequences for operators

Operators that over-block see delayed withdrawals, which can trigger player complaints and regulatory scrutiny. In jurisdictions where instant withdrawal guarantees are a selling point, any delay can damage an operator’s reputation and trigger licensing reviews.

A call for balanced risk models

Todurov warns against a “guilty until proven innocent” mindset. He suggests that operators treat every player as innocent until proven otherwise, using contextual data to differentiate legitimate high-value behaviour from fraud. This approach could reduce false positives and improve player retention.

Practical steps for casino operators

1. Audit KYC workflows to identify where AI-generated documents slip through.
2. Implement contextual risk scoring that accounts for travel patterns, deposit spikes, and card usage.
3. Measure withdrawal times as a KPI alongside fraud loss metrics.
4. Allocate analyst time to complex investigations rather than routine checks.

The broader industry impact

If operators ignore the cost of over-blocking, they risk losing top-spenders to competitors that offer faster withdrawals and more lenient checks. Regulators may also tighten scrutiny on operators that fail to balance fraud prevention with player experience, potentially leading to licensing sanctions.

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