Cash Forecasting Agent
Create liquidity forecast - recognise historical patterns, model scenarios, highlight action needs.
Aggregates historical cash flow data, recognises seasonality patterns, calculates payment delay probabilities, models scenarios and gives the CFO a well-founded basis for credit line and investment decisions.
Score Dashboard
What This Agent Does
Liquidity is the lifeblood of a company. Too little means insolvency. Too much means opportunity cost. The cash flow forecast is therefore one of the most important treasury tasks - and one of the most difficult. It combines hard data (open receivables, due payables) with soft factors (customer payment behaviour, seasonal patterns, market developments).
The Decision Layer clearly separates what algorithms can deliver from what requires human judgement. Aggregating historical data, recognising seasonality patterns, calculating payment delay probabilities - these are ML tasks. Defining scenarios, assessing the liquidity reserve, deciding on credit lines and investments - that stays with the CFO.
The result: the CFO receives a well-founded forecast instead of an Excel estimate. Best, base and worst case are fully calculated. And the sensitivity analysis shows which variable has the greatest impact.
Micro-Decision Table
Aggregate historical data Which cash flow data forms the forecast basis? Rules Engine
Database query by period and account type
Decision Record
Challengeable: Yes - rule application verifiable. Objection possible for incorrect data or wrong rule version.
Analyse maturity structure Which receivables and payables are due when? Rules Engine
Maturity structure from open items
Decision Record
Challengeable: Yes - rule application verifiable. Objection possible for incorrect data or wrong rule version.
Recognise seasonality patterns Are there recurring seasonal cash flow fluctuations? AI Agent
ML-based pattern recognition
Decision Record
Challengeable: Yes - fully documented, reviewable by humans, objection via formal process.
Calculate payment delay probabilities How likely is a payment delay per debtor? AI Agent
ML-based scoring on historical payment behaviour
Decision Record
Challengeable: Yes - fully documented, reviewable by humans, objection via formal process.
Define scenarios Which assumptions apply for best, base and worst case? Human
Strategic assumptions require human judgement
Decision Record
Challengeable: Yes - via manager, works council, or formal objection process.
Assess liquidity reserve Is the current liquidity reserve sufficient? Human
Strategic assessment considering risk tolerance
Decision Record
Challengeable: Yes - via manager, works council, or formal objection process.
Recommendation credit line / investment Should liquidity be borrowed or invested? Human
Strategic treasury decision
Decision Record
Challengeable: Yes - via manager, works council, or formal objection process.
Create report How is the forecast prepared and communicated? Rules Engine
Data visualisation = R, narrative and commentary = A
Decision Record
Challengeable: Yes - rule application verifiable. Objection possible for incorrect data or wrong rule version.
Decision Record and Right to Challenge
Every decision this agent makes or prepares is documented in a complete decision record. Affected parties (employees, suppliers, auditors) can review, understand, and challenge every individual decision.
Prerequisites
- Access to historical cash flow data (min. 12 months)
- ERP system with open items (receivables and payables)
- Bank data for current account balances
- Defined scenario parameters (growth, costs, FX assumptions)
Governance Notes
Not GoBD-relevant: the Cash Forecasting Agent does not process tax-relevant data - it creates pure forecasts. However, it is subject to general compliance requirements for automated decision systems.
The strategic decisions (credit line, investment, liquidity reserve) have significant financial impact and remain with the CFO. The agent delivers the data basis and calculates scenarios - the decision is made by the human.
§203 StGB-relevant data is encrypted end-to-end and never passed to AI models in plain text.
Process Documentation Contribution
Infrastructure Contribution
The Cash Forecasting Agent uses the bank data infrastructure of the Bank Reconciliation Agent and the maturity structures of the AP/AR agents. The scenario modelling framework is reused by the Forecast Agent and Budget Variance Analysis Agent. The payment delay analysis delivers data to the Receivables Management Agent.
Builds Decision Logging and Audit Trail used by the Decision Layer for traceability and challengeability of every decision.
Related Agents
Bank Reconciliation Agent
Read bank statements, assign payments, post bank fees, clarify differences.
Payment Traffic Agent
Format payments, transmit to bank, process acknowledgements, ensure four-eyes review.
Frequently Asked Questions
How accurate is the cash flow forecast?
Accuracy depends on data quality and forecast horizon. For 30 days, the agent typically achieves 85-90% accuracy. For 90 days it drops to 70-80%. Scenario modelling compensates for uncertainty through ranges instead of point forecasts.
Can the agent also forecast foreign currency cash flows?
Yes. The agent considers foreign currency receivables and payables. Exchange rate assumptions for scenarios are defined by the CFO - the agent calculates the impact on EUR liquidity.
How is the forecast adjusted for sudden market changes?
Scenarios can be recalculated at any time with updated assumptions. The agent shows the deviation between forecast and actual cash flow in real time. For significant deviations, an alert is automatically triggered.
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