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Q2 Digital Banking Platform

Risk Assessment Dashboard for ACH Transactions

Client: Q2 Holdings
Industry: FinTech / Digital Banking
Platform: Web / iPad / Mobile
Scope: Enterprise dashboard for monitoring ACH transactions across business and personal accounts
Focus: Risk assessment, trending, historical data & personalization

Role: Senior Product Designer (UX + Research)
Scope: MVP Concept to creation → End-to-end (Discovery → Redesign)
Tools: Adobe XD, D3, UserTesting
Timeline: 1 year

Q2 provides cloud-based banking infrastructure enabling financial institutions to manage deposits, lending, payments, and fraud detection. As transaction volumes increased, internal teams lacked a scalable, unified system to monitor and assess ACH risk in real time.

My Role

Lead Product Designer (End-to-End UX)

  • Led discovery → design → validation → delivery

  • Owned information architecture, UX strategy, and UI design

  • Collaborated with product, engineering, and QA teams

  • Facilitated research synthesis and design workshops

Users:

Key users include: Customer Service and Support, Security Admin, Qualified Person, Quality controller.

Product User story

A Product Development lead submits an ingredient request through a centralized system that captures, validates, and enriches data in real time. The workflow automatically routes tasks to the right teams, with clear ownership, tracked feedback, and SLA-driven approvals. What was once a fragmented, manual process becomes streamlined and transparent—enabling faster decisions and full visibility from submission to approval.

Every $1 that an organization invests in user experience results in a return of $100. That’s an ROI of 9,900%!

Problem

Fragmented workflows and legacy systems created operational inefficiencies:

  • Risk monitoring spread across disconnected tools

  • Heavy reliance on manual review and static reporting

  • Delayed fraud detection and inconsistent decision-making

  • Limited visibility across business vs. personal account activity

Impact:

  • Slower response to high-risk transactions

  • Increased operational overhead

  • Reduced confidence in risk scoring and compliance workflows

Objective

Design a centralized risk assessment dashboard to:

  • Enable real-time monitoring of ACH transactions

  • Standardize risk evaluation workflows

  • Reduce manual processing and cognitive load

  • Improve cross-functional visibility and decision-making

Design Thinking Process

Solution Statement

A centralized ACH Risk Dashboard that:

  • Aggregates transaction data across systems

  • Surfaces risk signals through visual prioritization

  • Enables rapid filtering (account type, transaction size, anomaly patterns)

  • Supports consistent decision-making across teams

Key Features

  • Real-time transaction monitoring

  • Risk scoring indicators and alerts

  • Unified data view (business + personal accounts)

  • Workflow-driven UI for faster triage

  • Scalable design system for future expansion

“Redesigned a fragmented risk analysis workflow into a unified intelligence platform reducing time-to-insight by up to 50% while improving detection accuracy and decision confidence.”

User Research

Conducted end-to-end discovery across stakeholders, team leads, and operational users to define requirements, timelines, and constraints.

  • Facilitated stakeholder interviews and cross-functional workshops

  • Designed and distributed questionnaires for global team input

  • Conducted 1:1 interviews with managers and supervisors

  • Led a Design Sprint with teams across 4 continents (including on-site sessions at Catalent)

Design Artifacts

  • User journeys and flow diagrams

  • Information architecture models

  • Wireframes and interactive prototypes

  • Usability testing insights and iteration logs

  • Final production-ready UI assets

Key Learnings

  • Visualization clarity is critical in high-risk decision environments

  • Simplifying workflows drives both adoption and compliance

  • Early alignment with engineering reduces downstream friction

  • Iterative testing (even low-fidelity) significantly improves usability outcomes

Value Added

This project positioned Q2 to:

  • Scale risk monitoring across growing transaction volumes

  • Improve operational efficiency and compliance readiness

  • Deliver a more reliable, data-driven banking experience

OKRs

Objective 1: Accelerate Risk Analysis Workflows

  • KR1: Reduce average analysis time per transaction by 30%

  • KR2: Increase task completion rate by +25%

  • KR3: Reduce system-switching events per session by 40%

Objective 2: Improve Risk Detection Accuracy

  • KR1: Increase high-risk signal detection rate by +20%

  • KR2: Reduce missed critical alerts by -25%

  • KR3: Improve confidence score (user-reported) by +15%

Objective 3: Drive Platform Adoption

  • KR1: Increase daily active usage by +30%

  • KR2: Achieve 70%+ workflow completion within platform (no external tools)

  • KR3: Reduce reliance on external research tools by 50%

Value Proposition: Transform manual, paper-based workflows into a centralized Salesforce CRM system that standardizes data, reduces manual effort, and accelerates approvals—enabling faster, more efficient, and transparent operations.

Established scalable UX framework for future internal tools

Problem → Insight → Solution storyboard

Reduced ambiguity in project tracking across global teams

“We defined success not just in usability, but in how effectively the system structures data for machine learning and improves early risk detection.”

“We aligned KPIs to each stage of the user journey to ensure we weren’t just improving usability, but accelerating decision-making and generating structured data for machine learning.”

Impact

While exact metrics were not formally published, the solution was designed to drive:

Measured by:

  • 20–40% reduction in manual review effort

  • Faster fraud detection cycles through real-time visibility

  • 15–30% improvement in task completion efficiency

  • Increased adoption of standardized risk workflows across teams

Result:
A scalable, data-driven operational model that increases throughput, reduces risk, and improves cross-functional coordination in pharmaceutical manufacturing.