Category: KYC

  • How to Reduce Drop-offs in KYC Without Compromising Risk

    How to Reduce Drop-offs in KYC Without Compromising Risk

    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.