Business fields · Finance & Treasury
AI training for Finance Teams
Finance and treasury teams handle large volumes of data, tight closing deadlines and strict demands for traceability. Generative AI is reshaping this work: AI assistants summarise bank statements, loan agreements and covenant clauses, draft commentary on cash flow variances and support scenario analysis on interest and exchange rates. AI agents and automation take over recurring steps such as matching payment advices, preparing the liquidity forecast or assembling management reports. What matters is that finance professionals review the output, connect data sources properly and define clear approval workflows. That frees finance teams to focus on analysis, steering and advising management instead of copying figures between spreadsheets, the ERP system and banking portals.
Who is this course for?
- CFOs and heads of finance
- Treasury and cash managers
- Financial analysts and FP&A teams
- Corporate finance and M&A specialists
- Payments and banking operations staff
Typical challenges we address
- Consolidating the liquidity forecast from many sources such as ERP, bank accounts and business units
- Explaining and commenting on budget-to-actual variances quickly
- Reviewing loan agreements, covenants and bank correspondence under time pressure
- Producing reports for executives, the supervisory board and lenders at short notice
Practical scenarios from your field
Cash flow commentary
An AI assistant analyses variances between forecast and actual cash positions and drafts commentary on the main drivers, such as customer receipts, supplier payments or tax dates, which the team then reviews and refines.
Financing agreement analysis
Loan agreements, promissory notes or lease contracts are summarised: maturities, interest mechanics, covenants, termination rights and reporting obligations are extracted into a structured overview for treasury and controlling.
Scenarios and sensitivities
AI helps draft scenario narratives and spreadsheet formulas for interest rate, currency and commodity sensitivities, for example showing how rising reference rates would affect financing costs and covenant ratios.
Management and board reporting
From KPIs, tables and bullet points, an AI assistant produces concise executive summaries, slide drafts and explanatory notes for management, the board or lenders, tailored to audience and level of detail.
Automated remittance matching
An automation workflow reads remittance advices from emails and PDFs, matches them to open items and flags discrepancies for manual review before the data is posted to the ERP or cash management system.
Policy and process documentation
Treasury policies, payment approval processes and control descriptions are structured and harmonised with AI support from notes, existing documents and interviews, making them clear and audit-ready.
Possible hands-on projects
Liquidity cockpit
A small web app that imports bank balances and expected cash flows from CSV exports, shows a rolling 13-week forecast and highlights potential shortfalls in colour.
Covenant tracker
An internal tool that calculates ratios such as leverage or interest cover per facility, compares them with thresholds and warns early of potential covenant breaches.
FX exposure calculator
A calculator that aggregates open foreign currency positions from orders and receivables, shows net exposure per currency and compares hedge ratios against the treasury policy.
All 15 courses for Finance Teams
AI for business (12)
- ChatGPT for Finance Teams
- Claude for Finance Teams
- Microsoft 365 Copilot for Finance Teams
- Google Gemini for Finance Teams
- AI Agents for Finance Teams
- Prompt Engineering for Finance Teams
- Generative AI for Finance Teams
- n8n for Finance Teams
- Make for Finance Teams
- Perplexity for Finance Teams
- Mistral Le Chat for Finance Teams
- EU AI Act & AI Compliance for Finance Teams
Vibe & agentic coding (3)
Data protection & compliance
Financial and banking data is confidential and may constitute inside information under MAR; only use approved AI environments with a data processing agreement and GDPR-compliant data handling. Payment approvals must remain under the four-eyes principle and must never be triggered autonomously by AI agents.
Prerequisites
You have hands-on experience in financial planning, treasury or reporting and are confident using spreadsheets.
Frequently asked questions
Can an AI assistant approve payments on its own?
No. AI can prepare payment proposals, match remittances and flag anomalies, but payment approval stays within your authorisation and four-eyes framework. In the course we show how to design automations so that people remain at the critical control points and every action is logged and traceable for auditors.
How should we handle confidential financial data in AI tools?
Start with an approved enterprise environment that has a contractual data processing agreement and does not use your inputs for model training. Add rules for pseudonymisation, such as masking account numbers or counterparties. We discuss practical guidelines that you can agree directly with IT, data protection and compliance.
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