The legacy portfolio monitoring workflow was:
Manual & Error-Prone – Agents spent excessive time downloading, renaming, and categorizing financial documents.
Lacking Visibility – No single view of borrower exposure, requiring agents to work across disconnected systems.
Data Entry Bottlenecks – Cash flow analysis and CBR tracking were conducted in third-party tools (Airtable), creating data silos.
Manual & Error-Prone – Agents spent excessive time downloading, renaming, and categorizing financial documents.
Lacking Visibility – No single view of borrower exposure, requiring agents to work across disconnected systems.
Data Entry Bottlenecks – Cash flow analysis and CBR tracking were conducted in third-party tools (Airtable), creating data silos.
As Lead UX Designer, I collaborated with product managers, engineers, and financial analysts to transform the workflow.
Stakeholder & User Research – Conducted interviews with portfolio agents to identify pain points.
Process Mapping & Wireframing – Designed low-to-high fidelity wireframes to streamline document handling & financial tracking.
Usability Testing & Iteration – Led testing sessions to refine interactions and reduce cognitive load.
Cross-Team Alignment – Worked with engineering & data science teams to integrate OCR, automation, and real-time data processing.
Stakeholder & User Research – Conducted interviews with portfolio agents to identify pain points.
Process Mapping & Wireframing – Designed low-to-high fidelity wireframes to streamline document handling & financial tracking.
Usability Testing & Iteration – Led testing sessions to refine interactions and reduce cognitive load.
Cross-Team Alignment – Worked with engineering & data science teams to integrate OCR, automation, and real-time data processing.
all work
Other Projects
Outcome & Business Impact
Document Handling Time Cut by 70% – Automated categorization reduced manual sorting errors.
Loan Risk Assessments 50% Faster – Agents could analyze borrower financials in 5-10 minutes, down from 30+.
80%+ OCR Accuracy – Extracted financial data seamlessly populated analysis tables, reducing data entry errors.
Increased Compliance & Risk Visibility – A single portfolio view reduced data silos and improved monitoring accuracy.
Loan Risk Assessments 50% Faster – Agents could analyze borrower financials in 5-10 minutes, down from 30+.
80%+ OCR Accuracy – Extracted financial data seamlessly populated analysis tables, reducing data entry errors.
Increased Compliance & Risk Visibility – A single portfolio view reduced data silos and improved monitoring accuracy.
Conclusion & Key Takeaways
UX research can uncover major operational inefficiencies, leading to scalable, high-impact solutions.
Automating data-heavy workflows reduces cognitive load, improves compliance, and enhances productivity.
Providing real-time financial insights empowers agents to make faster, more informed lending decisions.
Automating data-heavy workflows reduces cognitive load, improves compliance, and enhances productivity.
Providing real-time financial insights empowers agents to make faster, more informed lending decisions.
Problem Statement
Portfolio monitoring agents relied on manual processes across multiple systems to analyze cash flows and credit bureau reporting (CBR). This inefficiency led to data gaps, slow loan reviews, and compliance risks. The new automated portfolio monitoring system streamlined workflows, enabling faster decision-making, reducing manual effort, and improving risk assessment accuracy.
Overview
My Role & UX Process
Data Visualization
Cross-functional Collaboration
Financial & Platform UX/UXR
A UX Approach to Smarter Risk Management
Internal Tools | Fintech
To enhance efficiency and improve financial tracking, the new system incorporated:
Automated Document Categorization – AI-powered OCR detection auto-classified uploaded financial documents.
Side Drawer for Document Preview – Agents could view, re-categorize, and disposition documents without switching screens.
Financial Analysis Table – A dynamic dashboard enabled agents to compare period-over-period financial performance.
Exposure Calculation Module – Provided a real-time view of borrower exposure, incorporating direct, proposed, and indirect liabilities.
CBR Alerts & Risk Monitoring – Automated alerts flagged increases in revolving debt or decreases in credit score, triggering proactive reviews.
Automated Document Categorization – AI-powered OCR detection auto-classified uploaded financial documents.
Side Drawer for Document Preview – Agents could view, re-categorize, and disposition documents without switching screens.
Financial Analysis Table – A dynamic dashboard enabled agents to compare period-over-period financial performance.
Exposure Calculation Module – Provided a real-time view of borrower exposure, incorporating direct, proposed, and indirect liabilities.
CBR Alerts & Risk Monitoring – Automated alerts flagged increases in revolving debt or decreases in credit score, triggering proactive reviews.