Resolving Conflicts Between BotRefund and Your Existing Fraud Rules

If BotRefund conflicts with your existing fraud rules, the system allows you to set priority levels so you control whether BotRefund’s signals or your internal rules take precedence. Conflicts often occur when BotRefund’s behavioral analysis flags a session as fraudulent, but your existing system has already approved it based on different criteria. Audit logs record every decision, making it easy to review and adjust priorities.

This article explains how to diagnose and resolve these conflicts step-by-step. We cover why conflicts happen, how to investigate them, and how to configure your settings to prevent future issues.

Why Rule Conflicts Matter in Fraud Prevention

When multiple fraud detection systems run together, they can produce contradictory outcomes. For example, BotRefund might block a conversion it sees as bot traffic, while your internal rules approve it because it meets other criteria like IP reputation. Ignoring these conflicts can lead to false negatives (letting fraud slip through) or false positives (blocking legitimate users). Resolving them ensures consistent protection and reduces manual review overhead.

Symptoms Indicating a Conflict Between BotRefund and Fraud Rules

Watch for these signs that a conflict exists:

• Inconsistent transaction statuses: A session marked “Approve” in BotRefund but “Reject” in your system, or vice versa.
• Increased manual reviews: Your team spends more time resolving discrepancies between the two tools.
• Gaps in audit trails: You can’t trace why a decision was made because logs are fragmented.
• Unexpected refund or payout changes: Affiliates complain about held commissions, or ad spend recovery efforts stall.

These symptoms often point to mismatched priority settings or overlapping rule logic.

Diagnostic Sequence: How to Investigate Conflicts

Follow this order to pinpoint the root cause:

1. Collect evidence: Export decision logs from both BotRefund and your existing fraud system for the same time period. Look for sessions where outcomes differ.
2. Compare signals: Check which specific signals triggered each decision. BotRefund uses behavioral signals like click patterns, motion analysis, and session behavior (e.g., ghost click detection or honeypot interactions). Your rules might rely on IP lists, device fingerprints, or transaction thresholds.
3. Review priority settings: In BotRefund’s dashboard, verify your priority configuration. If BotRefund is set to high priority, it may override your rules, and vice versa.
4. Test in isolation: Temporarily disable one system to see if the conflict resolves. This helps isolate whether the issue is priority-related or due to rule logic overlap.
5. Check integration health: Ensure data flows correctly between BotRefund and your other tools. Sync issues can cause lag in signal sharing.

Likely Causes of Rule Conflicts

Conflicts typically arise from three areas:

• Priority misconfiguration: If both systems are set to enforce rules simultaneously without clear hierarchy, they can clash. BotRefund’s rule engine lets you assign weight to its signals—e.g., make its AI prediction take precedence over manual thresholds.
• Overlapping detection criteria: Your existing rules might flag the same behavior as BotRefund. For instance, both could target rapid form submissions, but use different thresholds or evidence standards.
• Data discrepancies: BotRefund captures UTM parameters and click IDs from traffic (as noted in S1), while your system might use different attribution sources. If data mismatches, decisions can diverge.

Setting Priorities: BotRefund vs. Internal Rules

When configuring priorities, consider these trade-offs:

• BotRefund-first priority: Use this if you want its AI-based behavioral analysis to lead. It’s effective for catching sophisticated fraud like attribution path manipulation (e.g., last-click hijacking). However, it may override nuanced internal rules that account for business context.
• Internal rules-first priority: Choose this if your existing system handles critical custom logic, such as refund policies or affiliate agreements. This keeps manual controls in charge but might miss fraud that BotRefund detects through motion or session analysis.
• Hybrid approach: Set BotRefund to “Review” or “Hold” status by default, allowing its signals to flag issues without auto-enforcing. This gives your team evidence to decide, but requires more manual work.

Audit logs (referenced in the brief) are essential here—they record which system acted on what data, helping you adjust priorities over time.

Corrective Actions to Resolve Conflicts

Once you’ve diagnosed the issue, take these steps:

1. Adjust priority levels in BotRefund’s dashboard: Define whether BotRefund signals or internal rules take precedence. For example, if affiliate commissions are being held incorrectly, set BotRefund to defer to your payout rules.
2. Align rule criteria: Review your existing fraud rules for overlaps with BotRefund’s signals. If both target similar behaviors, consolidate or differentiate thresholds. BotRefund provides granular evidence like attribution path analysis (S1), which can help refine your rules.
3. Use audit logs for continuous improvement: Regularly review conflict logs to spot patterns. If a specific rule consistently clashes, consider retiring or modifying it.
4. Test changes incrementally: After adjusting priorities, monitor a small segment of traffic to ensure conflicts decrease without reducing fraud detection efficacy.

Scenarios: Affiliate Fraud and Ad Click Conflicts

Here are practical examples:

• Affiliate commission dispute: Your internal rules approve a commission based on a conversion event, but BotRefund flags it as cookie stuffing (S1). Setting BotRefund to “Hold” with manual review lets you investigate without auto-rejecting. Use BotRefund’s evidence dashboard to see the attribution path.
• Ad click fraud: BotRefund detects superhuman input speed or grid-aligned movements (S2, S4), but your ad platform’s rules pass it as valid. Prioritize BotRefund’s signals here to block invalid clicks early, then use its audit-ready reports to request refunds from Google or Meta (S5).

Key Facts About BotRefund’s System

Limitations and When This Advice May Not Apply

This guide assumes you have administrative access to both BotRefund and your existing fraud systems. It may not cover:

• Legacy systems: If your fraud rules are hardcoded or lack API access, priority adjustments might be limited.
• Real-time enforcement conflicts: Some rules operate in real-time, while others batch-process—this timing difference can cause temporary mismatches.
• Non-BotRefund signals: The advice focuses on BotRefund; conflicts with other third-party tools (e.g., separate bot detectors) require similar diagnostic steps but might involve different integration points.

Always consult BotRefund’s support for system-specific guidance.

Frequently Asked Questions

1. How do I check which system is causing a conflict?
Start by comparing decision logs for identical sessions. BotRefund’s audit logs show evidence like behavioral signals, while your system may log different criteria. Differences in signal interpretation often reveal the source.

2. Can I set BotRefund to ignore certain rules in my existing system?
Yes, BotRefund’s priority settings allow you to define precedence. You can configure it to defer to your internal rules for specific scenarios, such as affiliate payouts, by setting BotRefund to “Review” or “Hold” status.

3. What if my fraud rules are more critical than BotRefund’s AI?
Set your internal rules to high priority in BotRefund’s configuration. This ensures they override BotRefund’s signals, but you’ll rely on your system’s detection capabilities. Regularly review audit logs to ensure no gaps.

4. How does priority configuration affect refund claims?
If BotRefund is prioritized, its evidence can strengthen refund disputes with ad platforms like Google or Meta (S5). If your rules are prioritized, ensure they generate compatible evidence for claims.

5. Are there best practices for ongoing conflict prevention?
Conduct monthly reviews of conflict logs, update rule thresholds based on evidence, and train teams on BotRefund’s dashboard to interpret signals correctly.

How BotRefund Can Help Resolve Conflicts

BotRefund provides a structured rule engine with priority levels that you can configure to align with your existing fraud rules. The system captures detailed evidence—like attribution paths and behavioral signals (S1)—and logs all decisions for review. This transparency helps you adjust settings, reduce conflicts, and maintain robust fraud protection without overhauling your current workflows. For affiliate contexts, it offers approval, review, and hold statuses that give your team control before payouts.