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CASE STUDY

Top Global C2C Marketplace Bans 99.2% of Bad Actors Instantly with Incognia

The marketplace partnered with Incognia to stop ban evasion at the source while keeping the onboarding experience frictionless for legitimate users.

Case Study Snapshot

The Platform

The Platform

A global mobile-first C2C marketplace with 60M+ monthly active users.

The Challenge

The Challenge

Professional fraudsters repeatedly evaded bans using emulators, app tampering, and device resets, often operating for weeks and harming legitimate users before being detected.

The Solution

The Solution

The platform ran a controlled 50/50 live test, splitting new registrations between their existing fraud stack and Incognia to compare performance . After demonstrating superior performance, Incognia was deployed to block high-risk devices instantly at onboarding, stopping repeat offenders before they could interact with the marketplace.

The Results

99.2%

of bad actors were banned instantly at onboarding

~50%

reduction in user reports related to bad actors

~48%

reduction in bad actor listings

Less than 1.5%

impact on legitimate user onboarding conversion

Results From 50/50 Live Split Test

Test Group

99.2%

of bad actors banned instantly With Incognia, fraudsters were identified and blocked immediately at onboarding, compressing response time from weeks to day 1.

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Using internal ML models

Bans were spread over weeks, allowing fraud to occur in the meantime.

Results From 50/50 Live Split Test

THE CHALLENGE

Ban Evasion at Scale

As a top global marketplace with over 60 million monthly active users (MAU), the platform faced a critical challenge with professional fraudsters evading bans. Bad actors were using sophisticated techniques, like emulators, app tampering, and device resets, to bypass security checks and get back on the platform so they could keep scamming legitimate users.

The marketplace’s existing solution, a market-leading device fingerprint provider, struggled with device ID persistence, particularly on mobile devices which accounted for 80% of the platform's traffic.

Because the previous vendor failed to persistently identify returning offenders, fraudsters were able to:

Evade Bans

Evade Bans

Create multiple accounts immediately after being blocked.

Delay Detection

Delay Detection

Operate for weeks before internal ML models could catch them, giving them time to run scams.

The platform needed a proactive solution that could detect and block high-risk devices at the exact moment of registration, preventing fraud before it could happen.

THE SOLUTION

Superior Device Intelligence + Tamper Detection

The marketplace deployed Incognia’s solution to secure the Onboarding flow on both Mobile and Web. They implemented a rigorous performance analysis to compare Incognia against their legacy fraud prevention stack.

Legacy Approach

Legacy Approach

Relied on internal models, often resulting in delayed bans. 

Incognia Approach

Incognia Approach

User registration was automatically actioned based on Incognia’s risk assessment. High-risk devices were immediately banned.

Key Differentiator

The marketplace used Incognia’s Device Intelligence + Tamper Detection. Incognia outperformed the customer’s internal models by delivering a resilient Device ID that persists through app reinstalls. When combined with device integrity checks that flag factory resets, emulators and other high-risk signals, this allowed the platform to persistently recognize and block returning bad actors that previously evaded detection.

RESULTS

The Results

The analysis demonstrated that Incognia successfully closed the loop on ban evasion, leading the client to move Incognia’s solution fully into production.

1. Drastic Compression of Fraud Response Time

The most significant win was the speed of detection. Previously, bans were spread out over weeks, allowing fraudsters time to attack legitimate users. With Incognia, detection became immediate.

99.2% of bad actors were identified and banned instantly at onboarding.

99.2% of bad actors were identified and banned instantly at onboarding.

This shift prevented bad actors from interacting with good users on the platform.

This shift prevented bad actors from interacting with good users on the platform.

2. Reduction in Downstream Fraud

By stopping bad actors at the front door, the marketplace saw a ripple effect of safety throughout the platform, reducing the burden on their support and trust and safety teams.

~50% reduction in user reports related to bad actors, meaning fewer users were being scammed.

~50% reduction in user reports related to bad actors, meaning fewer users were being scammed.

~48% reduction in listings created by bad actors

~48% reduction in listings created by bad actors.

3. Negligible Impact on Growth

A major concern for the marketplace was friction. They needed to ensure that aggressive fraud blocking did not hurt their acquisition of legitimate users.

Despite blocking nearly half of the platform's fraud, the impact on legitimate user onboarding conversion was less than 1.5%.

Despite blocking nearly half of the platform's fraud, the impact on legitimate user onboarding conversion was less than 1.5%.

The data validated that Incognia could distinguish between high-risk bot farms and genuine users with high precision, securing the platform without harming growth.

The data validated that Incognia could distinguish between high-risk bot farms and genuine users with high precision, securing the platform without harming growth.

INCOGNIA’S IMPACT:

Massive Fraud Reduction vs Negligible Growth Impact

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