Predictive Cash Flow Management

Overview

A $30M revenue company was managing cash flow with spreadsheets that were outdated the moment they were finished. The CFO had been caught off-guard by cash shortfalls three times in the past year, requiring expensive emergency credit line draws. We built an AI-powered cash flow forecasting system that integrates with their accounting, billing, and banking systems to provide a continuously-updated 90-day forecast with scenario modeling and early warning alerts.

The Challenge

Cash flow depends on dozens of variables: when customers actually pay (not when they're supposed to), seasonal revenue patterns, variable expenses, one-time costs, and upcoming commitments. The model needed to learn each customer's real payment behavior (not just terms), account for seasonal patterns, and handle the uncertainty inherent in predicting human behavior — all while presenting results in a format a CFO trusts enough to make decisions from.

Our Approach

We built a customer-level payment prediction model trained on historical AP/AR data. Each customer gets a predicted payment date based on their actual behavior, not net terms. This feeds into a cash flow simulation that runs thousands of scenarios to produce confidence intervals. The dashboard shows the most likely forecast plus best/worst cases. Automated alerts fire when the probability of a cash shortfall in the next 30/60/90 days exceeds defined thresholds. The system also recommends specific actions: which invoices to follow up on, which payments to delay, and when to draw on credit facilities if needed.

Key Features

• 90-day rolling cash flow forecast
• Customer-level payment prediction
• Scenario modeling with confidence intervals
• Automated shortfall early warning alerts
• Recommended actions to prevent crunches
• Bank account integration for real-time balances
• What-if analysis for major decisions

Results

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