CASH FLOW FORECASTING

Net Cash Forecasting From Real AR and AP Data

Name: CashPulse
Brand: Transformance
Availability: InStock

The only platform delivering multi-horizon net cash forecasts from real AR and AP data. 90-95% accuracy covering 13-week cash flow and beyond; confidence ranges instead of single-number guesses, and full-year horizons for portfolios with FX exposure or long booking cycles.

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CashPulse cash flow forecast with 8-week prediction chart, confidence bands, and upcoming payment probability scores

TRUSTED BY ENTERPRISE FINANCE TEAMS

90-95%

Forecast accuracy

8-week

Rolling horizon

Weekly

Retrained automatically

PREDICTIVE FORECASTING

Prediction-fed, not snapshot-based

Traditional forecasts look backward at what happened. CashPulse aggregates live AR data, payment predictions, and external signals into scenario-based forecasts by entity, currency, and category.

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CashPulse cash flow forecast with confidence bands and payment predictions

ML PIPELINE

Forecasts that see the future

Unlike traditional models limited to historical data, our engine incorporates forward-looking factors like commodity prices, weather events, and economic indicators to deliver forecasts that adapt to what's coming, not just what's happened.

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SCENARIO PLANNING

Build your own scenarios

Start from AI-predicted baselines, then layer custom assumptions like FX changes, payment delays, and seasonal adjustments to model any business outcome. Compare base, optimistic, and stress scenarios side by side.

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Scenario planning interface with stress test conditions and impact comparison

CREDIT RISK

Score every customer, live

Real-time credit risk assessment combining payment behavior, credit utilization, external ratings, and AI-predicted trends. Flag breaches before they happen, not after.

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HOW IT WORKS

From data to forecast in three steps

Connect

Plug into your ERP, bank feeds, and external data sources. CashPulse ingests live AR data, payment history, and market signals.

Train

Hundreds of model configurations tested in parallel. The champion model is selected automatically based on accuracy and stability.

Forecast

8-week rolling forecasts with confidence bands, payment-level forecasts, and scenario overlays. Updated daily.

CAPABILITIES

Everything you need to forecast with confidence

Rolling Forecasts

30/90/365-day rolling forecasts updated daily from live AR and AP data, payment patterns, and external signals like FX and commodity prices.

Learn more about ClearMatch →

Scenario Modeling

Layer custom assumptions on top of AI baselines. Compare base, optimistic, and stress scenarios

See how Vero acts on scenarios →

Credit Risk Scoring

Real-time risk assessment per customer combining payment behavior, utilization, and predicted trends

See how CollectPulse uses credit signals →

Entity Rollup

Consolidated forecasts across entities, currencies, and ERPs with drill-down to individual forecasts

Meet Vero, your AI agent →

Ready to forecast with live AR data?

See CashPulse in action on your own data. Deploy in weeks, not months.

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“

We didn’t have any real cash flow forecasting for over 10 years. Transformance solved this in a matter of months.

VP Finance IT

Major Agriculture Firm

BEFORE vs AFTER

The difference is measurable

Before

Manual forecasting

xMonthly spreadsheet updates

xHistorical data only, no forward signals

xSingle-point estimates, no confidence bands

xEntity-by-entity, no consolidated view

xStale by the time it reaches leadership

After

With CashPulse

✓Daily rolling forecasts from live AR data

✓Future factors: commodities, weather, FX

✓Confidence bands with best/expected/risk

✓Multi-entity rollup in reporting currency

✓Always current, always actionable

Enterprise-grade security and compliance

GDPR Compliant

ISO 27001

End-to-end encryption

Full audit trail

FAQ

1 What is cash flow forecasting software?

Cash flow forecasting software predicts future cash position by modeling expected inflows and outflows across AR, AP, and treasury activity. It replaces the monthly Excel forecast that treasury teams rebuild from bank snapshots and aging reports.

2 How is AI cash flow forecasting different from traditional forecasting?

AI forecasts from live, processed AR data rather than ERP snapshots. CashPulse knows which invoices will be paid because ClearMatch matched them, which are disputed because ClaimIQ flagged them, and which have promise-to-pay dates because CollectPulse recorded them. Traditional tools forecast from aging buckets and bank balances.

3 How accurate is invoice-level payment prediction?

Accuracy depends on data volume and customer payment history. Predictions tighten as the system accumulates resolution patterns. Forecasts are shown with confidence bands so treasury teams see the uncertainty, not a single deceptive number.

4 Can it forecast by entity, currency, and region?

Yes. Filter forecasts by legal entity, region, or reporting currency. Each entity's forecast reflects its own customer payment behavior, not a global average. Critical for multi-entity enterprises operating across dozens of countries.

5 Does it integrate with our existing treasury or ERP system?

CashPulse connects to SAP, Oracle, NetSuite, and Microsoft Dynamics. It can feed forecasts back into existing treasury tools or stay self-contained. AR data flows from the other Transformance products directly.

6 How long does implementation take?

CashPulse is typically live within 4 to 6 weeks once ClearMatch or CollectPulse is in place. Standalone deployments are possible but the forecast signal is cleaner when upstream AR data is also processed by Transformance.

7 Can we model what-if scenarios?

Yes. Scenarios are action-linked: if we accelerate collections on the top 20 overdue accounts, how does that change the 30-day forecast? The scenarios connect directly to actions your team can execute, not abstract parameter sliders.

8 Is the forecast data secure?

Yes. Deployment runs inside your VPC. Forecast data never leaves your cloud boundary. The platform meets ISO 27001 standards and every forecast change is logged.

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9 How do you combine AR and AP data into one net cash forecast without double-counting?

CashPulse builds a unified net cash position curve from real AR data (matched payments, active disputes, promise-to-pay dates) and real AP data (committed POs, payroll, tax schedules, contracts). Each entity's flow is netted at the legal-entity level with intercompany flows eliminated. Treasury teams see net cash, not gross inflows.

10 What model architecture powers CashPulse, and how is it different from legacy cash forecasting tools?

Legacy cash forecasting platforms run a single auto-regressive model for every customer and every horizon. That works for short, stable cycles but loses signal mid and long term, and it treats every variable in isolation. It cannot ingest external factors like FX rates, commodity prices, weather, or harvest cycles that materially shift when customers pay. CashPulse uses a multi-architecture engine that picks the right model per portfolio and horizon. Auto-regressive runs only where it actually fits (stable short-cycle portfolios). Mid-horizon behaviour-driven forecasting uses multi-dimensional ML pattern matching with persistent memory. Long-cycle, multi-entity portfolios with FX or commodity exposure run on a deep learning architecture purpose-built for multi-horizon time series, with quantile outputs and external signal ingestion as first-class inputs. Right model per region and entity, not one-size-fits-all.

11 What accuracy do you measure, and how?

CashPulse delivers 90-95% accuracy out to 90 days, measured as MAPE on the rolling P50 forecast against actual payment outcomes as invoices close. We track per-horizon accuracy (7/30/90/365 days), forecast bias, and per-customer hit rate, and rebuild the model when accuracy drops below threshold.

12 How should we interpret the confidence ranges in cash decisions?

Every forecast ships with three lines: best-case (P90), expected (P50), and risk-adjusted (P10). Plan against P10 for liquidity floors and covenant compliance, against P50 for working capital decisions, and against P90 for upside scenarios like early-payment discounts. Stress-test by adjusting external inputs (FX, commodity prices, customer payment behaviour) and watch the band move.

13 How much historical data do we need to deploy CashPulse?

Most enterprises deploy with around 3 years of payment history. Stable portfolios with predictable behaviour can deploy on as little as 1 year. Volatile or seasonal businesses (commodities, agriculture, FX-exposed multi-entity groups) benefit from up to 5 years. For portfolios with smaller scope or less history, CashPulse runs multi-dimensional ML pattern matching instead of the deep learning architecture. Even at the lower data end, accuracy beats legacy auto-regressive forecasting because the model captures behaviour and external signals rather than projecting historical averages forward.