Wells Fargo- Credit Risk -360
Date
:
June 2025
Categories
:
UI/UX Design
Project Overview
:
Credit Risk 360 is an enterprise risk management platform designed to help financial analysts evaluate loan applications, monitor customer risk signals, and make faster, data-driven credit decisions through a centralized dashboard experience.
Project Mission
:
Enable faster, smarter, and more transparent credit risk decisions through a centralized, data-driven, and compliance-friendly platform.
Project Vision
:
Create a centralized, intelligent, and compliance-friendly risk management experience that improves analyst efficiency, visibility, and decision confidence.
Project Details
Overview
Led the end-to-end transformation of an enterprise Credit Risk 360 platform, evolving it from a collection of fragmented tools into a unified, agentic AI ecosystem. By centralizing data and automating complex decision-making workflows, the redesign significantly reduced cognitive load and operational friction for credit analysts.
Core Agentic AI Capabilities
Autonomous Data Synthesis: Engineered intelligent data pipelines that aggregate and reconcile inputs from disparate legacy systems in real-time.
Explainable Risk Scoring: Designed transparent AI interfaces that visualize the "why" behind risk signals, ensuring regulatory compliance and analyst trust.
Proactive Workflow Orchestration: Implemented dynamic "next-best-action" surfacing, allowing the system to guide analysts through high-priority risk patterns rather than just displaying static data.
My Role
Product Strategy: Orchestrated enterprise workflow redesign and product vision.
Design Execution: Led dashboard UX, data visualization, and complex interaction design.
Systems Thinking: Architected information flow and scalable enterprise design patterns.
Accessibility & Compliance: Championed accessibility-first (WCAG) standards for high-stakes financial environments.
Cross-functional Leadership: Bridged the gap between AI engineering, compliance stakeholders, and end-users.
The Problem: Fragmented Intelligence
Analysts struggled with disconnected legacy systems, resulting in:
Operational Silos: Fragmented workflows causing delayed decision-making.
Cognitive Overload: Complex, non-prioritized datasets overwhelming analyst bandwidth.
Visibility Gaps: Inconsistent evaluations due to limited real-time risk tracking.
Research Insights
Insight | Impact |
|---|---|
System Fragmentation | Increased time-to-decision and error rates. |
Reactive Alerting | Missed critical risk signals due to poor prioritization. |
Cognitive Saturation | Reduced accuracy caused by complex, manual data parsing. |
Audit Friction | Operational delays due to disjointed compliance tracking. |
Design Approach
The redesign utilized a Human-in-the-Loop (HITL) architecture:
Centralized Ecosystem: Consolidated multi-system inputs into a single, cohesive dashboard.
Progressive Disclosure: Surfaced information based on task urgency to reduce cognitive load.
Explainable AI (XAI): Integrated context-aware insights to validate AI-driven decisions.
Accessibility-First: Implemented robust keyboard navigation, high-contrast data tables, and screen-reader-optimized layouts to ensure inclusive enterprise productivity.
Business Impact
Force Multiplier: Dramatically increased analyst efficiency and application review velocity.
Operational Excellence: Significant reduction in manual data entry and cognitive overhead.
Confidence & Clarity: Elevated decision-making quality through transparent, data-driven insights.
Skills Demonstrated
Enterprise UX • Agentic AI Design • Systems Thinking • Fintech UX • Accessibility (WCAG) • Workflow Orchestration • Product Strategy • Design Systems • Stakeholder Collaboration