Identify & Reduce Digital Ad Fraud with AI

Q: How do we quantify cost protection?

Measure blocked impressions/clicks, refunded media, and budget reallocation to verified supply; compare ROAS and CPA before and after implementation.

Q: Will fraud prevention reduce reach?

Temporary reach may decline as invalid supply is removed, but qualified reach and conversion efficiency typically improve.

Q: How often should we refresh rules and lists?

Review rules weekly, refresh allowlists/blocklists monthly, and update immediately during spikes or emerging threats.

Q: What governance is required?

Maintain audit logs, document rule changes, and align with privacy regulations and platform policies.

Executive Summary

AI-powered verification and anomaly detection identify and block fraudulent impressions and clicks across programmatic, social, display, search, CTV, and mobile. Replace 10–16 hours of manual checks with 30–60 minutes of automated detection and enforcement, raising campaign integrity and protecting media spend.

How Does AI Reduce Digital Ad Fraud?

AI analyzes traffic patterns, device fingerprints, publisher signals, and engagement anomalies to distinguish humans from bots and detect spoofed inventory. It then enforces pre-bid and post-bid rules automatically, reducing waste and improving ROAS.

Agentic AI monitors exchanges and placements continuously, correlates invalid traffic with creative, audience, and placement variables, and recommends remediation—blocking sources, adjusting allowlists, or shifting budgets to verified supply.

What Changes with AI Ad-Fraud Detection?

🔴 Manual Process (6 steps, 10–16 hours)

Manual fraud pattern research and identification (2–3h)
Manual detection methodology development (2–3h)
Manual monitoring system setup and configuration (2–3h)
Manual validation and testing (1–2h)
Manual implementation and integration (1–2h)
Documentation and monitoring procedures (1h)

TIME-INTENSIVE & REACTIVE

🟢 AI-Enhanced Process (2 steps, 30–60 minutes)

AI-powered real-time fraud detection with automated prevention (20–40m)
Intelligent campaign protection with continuous monitoring (10–20m)

90%+ FASTER & ALWAYS-ON

TPG standard practice: Apply pre-bid verification, maintain authenticated supply paths, and quarantine suspicious traffic for analyst review to sustain accuracy and compliance.

Key Metrics to Track

95%

Fraud Detection Accuracy

90%

Cost Protection

92%

Campaign Integrity

85%

Performance Improvement

Core Detection Capabilities

Invalid Traffic (IVT): Detect bots, click farms, emulators, and data-center traffic via device/behavioral fingerprints.
Inventory & Identity Spoofing: Identify forged domains, app IDs, and manipulated user agents across SSPs/DSPs.
Viewability & Interaction Integrity: Flag auto-refresh, stacked ads, hidden iframes, and synthetic scroll/click patterns.
CTV & Mobile Protection: Expose SSAI fraud, out-of-geo delivery, and SDK spoofing to safeguard premium spend.

Which AI Tools Enable Fraud Prevention?

DoubleVerify Authentic Brand Safety

Pre-bid and post-bid verification to block IVT and ensure viewable, brand-safe impressions.

Integral Ad Science (IAS)

Real-time fraud detection, contextual classification, and optimization signals.

White Ops (HUMAN) Bot Detection

Identity-based bot mitigation for web, mobile, and CTV across the ad supply chain.

Moat Analytics

Attention and viewability analytics with IVT filtering for media quality assurance.

These platforms integrate with your existing marketing operations stack to deliver continuous verification and budget protection.

Implementation Timeline

Phase	Duration	Key Activities	Deliverables
Assessment	Week 1–2	Audit traffic quality, map supply paths, identify high-risk channels	Fraud risk assessment & policy
Integration	Week 3–4	Implement pre/post-bid tags, connect DSP/SSP APIs, configure rules	Verified media pipeline
Calibration	Week 5–6	Tune thresholds, define allow/blocklists, validate against baselines	Calibrated detection models
Pilot	Week 7–8	Run side-by-side tests, measure cost protection and lift	Pilot results & rollout plan
Scale	Week 9–10	Roll out to all campaigns, activate alerts and automated enforcement	Production fraud prevention
Optimize	Ongoing	Refine rules, expand channels (CTV/mobile), refresh allowlists	Continuous improvement

Frequently Asked Questions

What types of digital ad fraud does AI catch?

Common types include GIVT/SIVT, bot and emulator traffic, domain/app spoofing, SSAI fraud in CTV, stacked/hidden ads, and manipulated interaction signals.

How do we quantify cost protection?

Track blocked impressions/clicks, refunded media, and reallocated budgets to verified supply. Compare pre- and post-implementation ROAS and CPA.

Will fraud prevention reduce reach?

Short-term reach may decrease as invalid supply is removed, but qualified reach and conversion efficiency typically improve as spend shifts to quality inventory.

How often should we refresh rules and lists?

Weekly rule reviews with real-time alerts; monthly refresh of allowlists/blocklists; immediate updates during spikes or new threat patterns.

Does this work across CTV and mobile apps?

Yes—verification tags, SDK signals, and SSAI heuristics extend protection to CTV and mobile with dedicated detection models.

What governance is required?

Maintain audit logs, document rule changes, and implement approval workflows. Align with privacy regulations and platform policies.