I designed the ID Verification experience for a digital investment platform — an essential step in the account activation process. Without passing this step, users couldn’t start their investment journey. This case study explores how we simplified a compliance-heavy process to reduce friction, activate the investing account as fast as possible, build trust, and leverage machine learning for smarter document validation.
New users were dropping off during the ID verification step—a mandatory process for regulatory compliance. Our data showed a 59% failure rate in automatic activation, which delayed users from starting their trading and investing journey. Many users entered incorrect KYC information, leading to further verification failures. This critical flow needed to securely collect sensitive information, guide users through document and biometric capture, and establish trust—while ensuring full compliance.
Problem Statement: How might we reduce drop-off and increase auto-activation during the ID Verification process while ensuring regulatory compliance and a secure, trustworthy experience?
To understand user needs and pain points, we broke down the ID verification process into discrete tasks:
01.
Before verification
Choose a document type to upload (e.g., passport, driver’s license).
Locate and prepare the required documents.
02.
During verification
Use the mobile camera to photograph or scan the selected document.
Capture the reverse side of the document if required.
Perform a selfie ID scan to complete biometric verification.
03.
After verification
Review a summary of the uploaded documents and selfie.
Validate the information by comparing it with the KYC details provided by the user.
Designed key product features through a data-informed process that combined task analysis and vendor interviews. By mapping user workflows and identifying friction points, I uncovered critical opportunities to streamline operations and improve efficiency. Insights from vendor interviews validated real-world needs and technical constraints, ensuring that each feature was both user-centered and operationally feasible. This approach aligned design decisions with stakeholder goals while delivering measurable impact on usability and performance.
Mobile camera interface
Clear visual guidance for aligning ID and face within the frame.
Real-time feedback on scan quality.
QR Code and Magic link
Easy-to-scan QR code displayed on the desktop.
Instant redirection to the mobile verification interface.
Synchronization
Real-time progress updates on the desktop view.
Notifications for successful steps or errors requiring attention.
Accessibility features
Multilingual support for instructions.
Alternatives for users without access to mobile cameras (e.g., manual upload).