AI-assisted verification for direct deposit setup

Overview

My role & goal

As the Senior UX Designer, I led the design of a new verification flow for direct deposit setup. The existing experience required manual banking entry with no validation, leading to frequent errors, failed deposits, and increased support needs.

The goal was to add a AI-assisted verification flow to help members enter banking information correctly and reduce failed direct deposit reimbursements.

The team

  • Senior UX Designer

  • Project Managers

  • Business Analyst

  • Developers

  • Quality assurance

Understanding the problem

User group: Members (employees enrolled in their company’s health benefits plan who use the application to review coverage and submit health claims.)

Methods: Indirect user feedback from the PM and exploration of current workflow.

The previous experience required manual banking entry with no validation. Errors were common, especially with long account numbers and inconsistent formats across financial institutions. Failed deposits created delays, frustration and significant support overhead.

Introducing AI-assisted verification offered an opportunity to reduce errors—but also introduced new UX challenges, including varying document quality, AI misreads and the need for clear actionable feedback.

Defining key design goals

With the defined challenges in mind, I established the following high-level goals:

  • Improve banking information entry accuracy to reduce failed deposits

  • Present AI findings clearly, with helpful warnings

  • Support edge cases gracefully through fallback and override paths

  • Ensure visual consistency across web and mobile

Ideation & exploration

Methods: Competitive analysis of direct deposit setup flows in the market.

I created several flow variations that explored:

  • When AI should run

  • How verification results should be presented

  • How override or manual correction paths should work

Iterative design

Method: Internal design reviews with the PM, BA, and developers

Approach: high-fidelity mockups → interaction flows → iterative refinements

Through internal reviews with the PM, BA, and developers, we refined the flow to account for key constraints:

  • Adjusting messaging based on different AI results

  • Clarifying the mismatch states to avoid user confusion

  • Ensuring AI delays didn’t block or trap users

  • Supporting manual continuation if the AI struggled to read the document

Final design solution

I delivered polished, developer-ready designs for all key verification flows, including:

✓ AI-assisted verification: After uploading their document, members see extracted banking details compared with what they entered.

✓ Clear mismatch and warning states: Contextual messaging explains when fields don’t match or when AI confidence is low.

✓ Manual override path: If the AI cannot read the document, members can continue to complete setup without getting stuck.

✓ Cross-platform consistency: Matching flows for web and mobile ensure a unified experience across devices.

Outcome

Since launching in 2025, the feature has been well received by internal teams and has operated without the need for revisions. The addition of document uploads has also strengthened validation, helping insurers more easily also confirm direct deposit accuracy.

Reflection

Designing flexible fallback paths and transparent messaging has been essential to ensuring that AI enhances the experience rather than becoming a barrier.