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How to Reduce Drop-offs in KYC Without Compromising Risk

Discover how AI-driven document checks and passive footprinting reduce friction while enhancing fraud controls

KYC 14 Aug 2025 Admin
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Table of contents

The Problem: KYC Kills Conversions

KYC is critical—but also painful. Every additional step in identity verification increases user friction, which directly impacts conversion rates, especially in onboarding-heavy industries like fintech, BNPL, and neobanking.

  • Users abandon when upload fails
  • They quit when video liveness takes too long
  • They hesitate when asked for too much too soon

But removing checks is risky. So the real question is: How can platforms improve completion rates without compromising fraud detection or compliance?

The Solution: Intelligent, Friction-Less KYC

Here’s how smart platforms are reducing drop-offs while still managing identity risk:

1. Replace Liveness Video with Image-Based Verification

Videos take time to record, fail in poor networks, and intimidate users. ATNA uses image-only checks—verifying document integrity and facial consistency without requiring a selfie video.

Impact:

  • 30% reduction in dropout during selfie stage
  • Works well in Tier-2/3 markets with low bandwidth

2. Pre-Fill What You Can from the Document

Instead of asking users to manually type their name, DOB, and address, extract those directly from the uploaded ID and auto-fill the form. ATNA’s AI-KYC does this in real time.

Impact:

  • Reduces user effort
  • Prevents mismatches due to typos

3. Skip Extra Documents Using ATNA Score

Instead of asking for additional documents when you’re unsure, use ATNA Score to calculate real-time onboarding risk based on document quality, digital footprint, and passive behavior signals.

Impact:

  • 25% reduction in document re-request
  • Better user experience without cutting risk coverage

4. Start with Passive Signals First

Before even asking the user for a document, analyze device, IP, network, and behavioral traits using ATNA’s Digital Footprinting.

Impact:

  • Identify suspicious users before asking for verification
  • Personalize the level of KYC required

5. Use Conditional Workflows Based on Risk Tier

All users don’t need full KYC. ATNA lets you adjust flows:

  • Low-risk: Document + image validation
  • Medium-risk: Add footprinting + extra ID
  • High-risk: Redirect to manual review

Impact:

  • Right-sized effort for every user
  • Reduces over-verification and under-verification risks

Conclusion

Reducing KYC drop-offs isn’t about removing checks—it’s about making them smarter, faster, and invisible where possible. ATNA delivers adaptive KYC without compromising.

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