Training course – AI Agents – Finance & Treasury

AI Agents for Finance Teams

Agentic AI for business teams: understand AI agents, automate workflows safely and keep control with human-in-the-loop and governance.

Duration
6 hours, one session
Format
Online or on-site
Language
German or English
Participants
open dates or exclusive for your team
Certificate
Certificate of attendance

Overview

“AI Agents for Finance Teams” is designed for roles such as CFOs and heads of finance, Treasury and cash managers and Financial analysts and FP&A teams and shows step by step how to use AI Agents productively, safely and transparently in Finance & Treasury – from the fundamentals to advanced workflows.

AI agents go a step beyond conventional chat assistants: they plan sub-tasks, use tools such as search, files or business applications and complete multi-step work largely on their own. In this compact course you will learn how agents are built, how they differ from chatbots and traditional automation, and which tasks genuinely justify their use. Widely used platforms serve as practical examples, including Microsoft Copilot Studio, custom GPTs and Claude with projects and tool connections.

In the hands-on sessions you design agent workflows for tasks from your own area of work, from triaging requests through research and drafting to handing results over to business systems. You decide where a person reviews and approves, which permissions an agent receives and how errors are detected. A dedicated block covers governance, data protection and accountability, so that your agents not only work but remain controllable, traceable and defensible within your organisation.

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.

The course is delivered live – either online in a virtual classroom or on-site in our training rooms in Munich, Salzburg, Berlin, Augsburg, Hanover, Bremen, Stuttgart and Kaiserslautern. We can also run it exclusively for your team.

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

What you will be able to do

  • You can explain how AI agents are structured and clearly distinguish them from chatbots and classic automation.
  • You can select a suitable agent platform for your requirements using transparent criteria.
  • You can design an agent workflow for a real process in your area and build a working prototype.
  • You can define human-in-the-loop checkpoints, test cases and escalation rules.
  • Use AI assistants effectively for liquidity planning, variance analysis and financing documents.
  • Automate recurring treasury tasks with clear review and approval steps.
  • Critically assess AI output and keep financial data confidential and audit-proof.

Course outline

Module 1 What makes an AI agent
  • Agent building blocks: language model, instructions, knowledge, tools and memory
  • How agents differ from chatbots, macros and classic workflow automation
  • Levels of autonomy: from suggestion-making assistants to agents that act independently
  • Realistically judging which tasks suit agents and which do not
Module 2 Platform overview: Copilot Studio, GPTs and Claude
  • Microsoft Copilot Studio: agents grounded in company data and connected to Microsoft 365
  • Custom GPTs: configuring instructions, knowledge files and actions
  • Claude with projects, knowledge bases and tool access via the Model Context Protocol
  • Selection criteria: data access, integrations, administration and licensing
Module 3 Designing and building agent workflows
  • Breaking tasks into steps and defining hand-offs between agent and human
  • Writing system instructions, examples and knowledge sources for consistent output
  • Connecting tools: search, documents, email, spreadsheets and business applications
  • Building a prototype agent for a real process from your own area
Module 4 Human-in-the-loop, quality and error handling
  • Setting approval steps, escalation rules and thresholds for human review
  • Test cases, evaluation criteria and spot checks for quality assurance
  • Common failure modes: wrong tool choice, endless loops and fabricated facts
  • Using structured user feedback to improve the agent over time
Module 5 Governance, security and roll-out
  • Roles and responsibilities across business units, IT, data protection and works council
  • Least-privilege permissions, logging and protection against prompt injection
  • Positioning under the EU AI Act and GDPR: transparency, documentation and data flows
  • From pilot agent to production: operation, maintenance and measuring success
Module 6 Practice lab: Finance & Treasury
  • Cash flow commentary
  • Financing agreement analysis
  • Scenarios and sensitivities
  • Management and board reporting
  • Automated remittance matching
  • Policy and process documentation
Module 7 Data protection, quality & transfer to daily work
  • 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.
  • Ground rules for safe AI use in your team
  • Checking results: facts, sources, tests and the four-eyes principle
  • Personal action plan for the next 30 days
  • Open questions, outlook and resources for further learning

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.

Prerequisites

You should already use an AI assistant such as ChatGPT, Copilot or Claude on a regular basis. No programming skills are required. You have hands-on experience in financial planning, treasury or reporting and are confident using spreadsheets.

Technical requirements

You will need a laptop with an up-to-date browser. Ideally you have access to at least one agent platform such as Copilot Studio, ChatGPT with GPTs or Claude; practice accounts can be provided if needed.

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.

Dates & locations

For every location we suggest a date roughly four weeks ahead. Your preferred date is always possible.

  • Munich Fri, 11 December 2026 6 hrs Request
  • Salzburg Fri, 11 December 2026 6 hrs Request
  • Berlin Mon, 14 December 2026 6 hrs Request
  • Augsburg Tue, 15 December 2026 6 hrs Request
  • Hanover Wed, 16 December 2026 6 hrs Request
  • Bremen Mon, 14 December 2026 6 hrs Request
  • Stuttgart Thu, 10 December 2026 6 hrs Request
  • Kaiserslautern Thu, 10 December 2026 6 hrs Request
  • Online Thu, 10 December 2026 6 hrs Request

Frequently asked questions

Do I need programming skills to build AI agents?

No. The platforms used on the course rely on visual interfaces, plain-language instructions and ready-made connectors. You learn to specify agents precisely from a business perspective, connect tools and test workflows. Where deeper technical integration would be needed, you will know which requirements to put to your IT team.

Which platform will we use during the course?

The course is vendor-neutral and uses Microsoft Copilot Studio, custom GPTs and Claude as examples. You build your prototype on the platform that is available or planned in your organisation. The principles of workflow design, control and governance you learn carry over to other agent solutions as well.

How do I stop an agent from acting without control?

Through deliberate design: agents receive only the minimum permissions they need, critical actions such as sending, booking or deleting require human approval, and every step is logged. In addition, you define test cases and escalation rules. These are exactly the control mechanisms you develop for your own use case during the course.

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.

How much does “AI Agents for Finance Teams” cost?

The course costs a flat €949 plus VAT per participant – whether online or on-site. This includes 6 hours of live training with a trainer, course materials, a lab environment and a certificate of attendance.

Can I suggest my own date?

Yes. For every location we suggest a date roughly four weeks ahead. In the request form you can always describe your preferred date or period in free text – we check availability and get back to you within one working day.

Is the course online or on-site?

Both are possible: live online in a virtual classroom or on-site in Munich, Salzburg, Berlin, Augsburg, Hanover, Bremen, Stuttgart and Kaiserslautern. We can also run the course exclusively for your team.

Can the course be tailored to our team?

Yes. Tailor-made courses cost approx. €4,500 more, depending on the topic and by arrangement. We agree content, examples and exercises with you in advance.

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