P&L Anomaly Detection Engine
B2B, UI/UX
2025

The P&L Anomaly Detection Engine is a sophisticated financial monitoring system designed to help finance teams identify unusual patterns, errors, and potential fraud in profit and loss statements through AI-powered anomaly detection. The system serves CFOs, FP&A analysts, and finance managers who need to ensure accurate financial reporting and prevent revenue leakage.
Problem Statement
Finance teams across organizations struggle with manual P&L analysis, leading to delayed detection of financial anomalies that can cost companies millions in revenue leakage.
Current Process
• Time-consuming: Manual review of financial statements takes 40+ hours per month
• Error-prone: Human analysis misses 60% of subtle anomalies
• Reactive: Issues discovered weeks after occurrence, limiting corrective action
• Lack of context: No clear explanation of why something is flagged as anomalous
Business Impact
Contribution
Research, UI/UX Design, Prototypes
Team
Designer, Project Manager, Tech Lead
Duration
3 Weeks
Pain Points
Black-box alerts erode trust as users lack visibility into why they’re triggered or how to act on them
The absence of a unified workflow from alert to resolution causes inefficiencies and tracking gaps
Frequent false positives create alert fatigue, leading users to ignore critical issues
Executives need quick, mobile insights, while analysts require deeper, data-rich desktop tools
Objectives
Detect, investigate, and resolve anomalies using explainable AI for greater trust and clarity
Reduce investigation time and minimize alert fatigue through intelligent prioritization and automation
Deliver mobile-friendly executive summaries for quick, informed decision-making on the go.
Ensure audit-ready traceability and compliance with a transparent, end-to-end workflow.
01
02
03
04
Discover Intuitive Designs


Anomaly explanation interface for Walmart MAC analysis featuring KPI summaries, trend visualizations, AI insights on mix shifts and cost drivers, SKU-level impact analysis, and a detailed evidence table for investigation.




