VAM — Redesigning a legacy bank-agent application
Reorganized a fragmented desktop application around frontline jobs to be done, persistent system feedback, guided task flows, and reusable interaction patterns.
A B2B SaaS tool for bank agents to manage accounts, policies, transactions, and service requests.
Outdated UI patterns, inconsistent interactions, and module-first navigation no longer matched how agents actually worked.
End-to-end redesign across discovery, journey mapping, IA, prototyping, design system, usability testing, and handoff.
Remove redundant steps and navigation dead ends.
Bring account, policy, and transaction work into one coherent architecture.
Create reusable components and patterns engineering can extend safely.
Contextual interviews, workflow observation, and competitive review.
Personas, journey mapping, pain-point synthesis, and KPI definition.
Information architecture, flows, wireframes, component library, and iterative prototypes.
High-fidelity design, usability validation, engineering collaboration, and QA.
Explored task frequency, workarounds, friction, and unmet needs with frontline agents.
Compared intended flows with real behavior to expose dead ends, redundant navigation, and missing system feedback.
Competitive review of enterprise banking tools pointed toward task-oriented navigation instead of feature-grouped menus.
Common tasks required roughly seven screens when two or three should have been sufficient.
Actions lacked confirmation, loading, and useful error states, causing repeated actions and uncertainty.
Inconsistent tables, date inputs, and unlabeled controls increased learning effort even for experienced agents.
The highest friction appeared after account lookup.
Targeted a reduction from seven average steps to three using time-on-task and session analysis.
Targeted improvement from 2.1/5 to above 4/5 using post-session feedback.
Targeted a 60% decrease in help-related supervisor escalations.
Primary navigation reflects recurring jobs to be done.
Success, error, progress, and validation feedback appear at every consequential interaction.
Labels, contextual help, and stepped flows reduce memorization and first-use burden.
Cross-functional structure workshops used card sorting and affinity mapping to test the proposed IA before high-fidelity design. Core flows were explored in low-fidelity first, then validated across three usability rounds with five bank agents per round.
Tables, filters, forms, status badges, action menus, confirmation dialogs, and notifications.
Typography, spacing, color, and elevation variables mapped to implementation-friendly rules.
Documented multi-step policy updates, bulk transactions, customer drill-downs, and exception handling.
Pending work, recent interactions, daily metrics, and quick entry points for frequent tasks.
Account, policy, transaction, and open-case context in one consolidated view.
Reduced a seven-screen process to a three-step guided flow with validation and review-before-submit.
Advanced filtering, sortable columns, status states, bulk actions, and safeguards around irreversible operations.
- 40+ documented components delivered.
- New-agent onboarding reduced from about three weeks to under one week.
- No critical usability issues remained in the final QA round.