H2O Data Verify Portal

Designed a data-driven portal optimizing fraud verification process, enhancing accessibility, and streamlining operations with intuitive navigation and real-time insights.

Enterprise

Newrez LLC

Services

Verification & Workflow Optimization

Platforms

Desktop

Introduction


💡 Challenge
‍Complete UX overhaul to simplify data access, speed fraud reporting, and improve usability for financial and fraud analysts.

🔍 Approach
‍Led user research and iterative high-fidelity prototyping to deliver intuitive navigation, interactive dashboards, and automated alerts — reducing average fraud case time from ~10 to ~6.5 days and saving ~15 hours per analyst weekly.

🎯 Impact
Improved fraud report processing by 35%, sped fraud detection by 30%, and cut manual analysis by 40%, enabling faster, more accurate decision-making.

Before and after screenshots of the H2O Data Verify platform, showcasing UX improvements in data visualization, usability, and accessibility for enhanced data verification.

Key Features:

  • 🔔 Automated alerts for critical fraud indicators
  • 🔄 Role-based access control for secure data
  • 📂 Interactive dashboards for transparent insights
  • 🔧 Error tracking for verification discrepancies

Design Process

🔹 Research & User Interviews – Conducted discovery sessions to identify user pain points and fraud verification challenges.
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🔹 Wireframing & Prototyping – Designed and iterated on UX/UI to optimize data access, alerts, and reporting workflows.
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🔹 Testing & Usability Analysis – Tested 2 prototypes with stakeholders, refining fraud insights and improving report accessibility.
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🔹 Ensured Accessibility & Responsive Design – Implemented WCAG 2.2 compliance for seamless cross-device usability.
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🔹 Cross-Functional Collaboration – Worked with PMs, developers, and compliance teams to enhance fraud detection and streamline decision-making.

Whiteboard sketch outlining the page design requirements, featuring layout structure, user flow, and key functionality notes for the design process.

Key Learnings & Impact

📊 Reduced fraud report processing time by approximately 30–35%, decreasing average case duration from ~10 days to ~6.5 days, enabling analysts to handle more cases monthly.

⚡ Accelerated fraud detection by around 30%, cutting time to flag suspicious activity from ~3 days to ~2 days, allowing for earlier intervention and reduced potential losses.

⏱️ Lowered manual analysis workload by roughly 40%, freeing an estimated 15 hours per analyst per week to focus on complex, high-value investigations.

‍These improvements were measured through comparative analytics before and after implementation over a 3-month period.

Qualitatively, analysts reported reduced frustration and increased confidence, while business leaders experienced faster, more reliable decision-making.

Screenshot of the alerts page, allowing users to manage notifications by setting statuses as cleared or active while viewing detailed alert information.

Designing for Ambiguity

✍️ Given a vague problem, I delivered a clear solution that sped fraud detection by 30% and cut report processing by 35%.

Next Steps

🔹 Automated Data Verification – Scaling real-time fraud detection and reporting, enhancing accuracy and efficiency for users.
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🔹 Continuous Usability Testing – Refining fraud insights and workflows based on user feedback for a seamless experience.

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