Training course – EU AI Act & AI Compliance – Banking

EU AI Act & AI Compliance for Banks

Putting the EU AI Act into practice: risk categories, deployer obligations, AI literacy under Art. 4, AI policy and GDPR interfaces.

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

“EU AI Act & AI Compliance for Banks” is a hands-on course for roles such as Corporate and retail relationship managers, Credit analysts and credit operations staff and Compliance, AML and risk management teams. Rather than learning EU AI Act & AI Compliance in the abstract, you work on tasks from your daily routine – with examples, exercises and templates from Banking.

The EU AI Act is the first comprehensive legal framework for artificial intelligence, and it applies not only to providers but also to organisations that use AI systems in their daily work. In this compact course you will learn how the regulation is structured: prohibited practices, high-risk systems, transparency obligations and general-purpose AI models. You will find out which role your organisation plays as a deployer, which obligations follow and how to record and classify the AI applications you use in a structured way.

The practical part turns the requirements into manageable steps. You clarify what the AI literacy obligation under Article 4 means in concrete terms, how to organise training in a verifiable way and what an internal AI policy should cover. You also examine the interfaces with the GDPR, such as legal bases, data protection impact assessments and automated decision-making. You leave with an AI inventory template, a draft policy and a clear compliance roadmap for your area of work.

Banks operate between rising cost pressure, digital competitors and dense regulation. Generative AI offers tangible efficiency gains: AI assistants analyse credit files and financial statements, summarise regulatory publications, help relationship managers prepare client meetings and answer internal questions about policies and procedures. AI agents and automation speed up processes in credit operations, KYC and complaints handling. At the same time, specific requirements apply: outsourcing and ICT risk management, traceable decisions and protection of customer data. Banks using AI must assess use cases carefully, integrate models and providers into risk management and assign clear responsibilities. Then AI becomes a tool for better advice and leaner processes.

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?

  • Corporate and retail relationship managers
  • Credit analysts and credit operations staff
  • Compliance, AML and risk management teams
  • Organisation and process owners
  • Internal audit

Typical challenges we address

  • Analysing extensive credit files and financial reports efficiently
  • Tracking and implementing regulatory changes from the EBA, ECB and national supervisors
  • Meeting documentation duties in advisory and lending processes
  • Reducing manual checks in KYC and AML without compromising quality

What you will be able to do

  • You can explain how the EU AI Act is structured and assign your organisation to the correct roles.
  • You can classify the AI applications in use by risk category and maintain an AI inventory.
  • You can name the specific obligations of deployers and derive appropriate measures.
  • You can develop an AI literacy concept under Article 4 and a draft internal AI policy.
  • Identify and assess AI use cases across front office, credit operations and compliance.
  • Use AI for credit analysis, regulatory research and client communication with clear review steps.
  • Take supervisory requirements on risk management, DORA and outsourcing into account when using AI tools.

Course outline

Module 1 Structure and logic of the EU AI Act
  • Objectives, scope and phased application of the regulation
  • Roles at a glance: provider, deployer, importer and distributor
  • The risk-based approach: prohibited practices, high risk, limited risk and minimal risk
  • Specific rules for general-purpose AI models
Module 2 Classifying risk in practice
  • Prohibited practices such as social scoring or emotion recognition in the workplace
  • High-risk areas under Annex III, including recruitment, creditworthiness and education
  • Transparency obligations for chatbots, synthetic content and deepfakes
  • Recording and classifying your own AI applications in an AI inventory
Module 3 Obligations for deployers of AI systems
  • Use in line with instructions and human oversight by competent staff
  • Input data quality, monitoring of operation and retention of logs
  • Informing employees and affected persons and reporting serious incidents
  • Fundamental rights impact assessment: when it is required and how it works
Module 4 AI literacy under Art. 4 and internal AI policy
  • What sufficient AI literacy means for different roles
  • Designing training concepts and documenting measures verifiably
  • Components of an AI policy: approved tools, data classes, approvals and labelling
  • Responsibilities, AI officers and involving the works council and IT
Module 5 GDPR interfaces and governance
  • Legal bases, purpose limitation and data minimisation when using AI
  • Data protection impact assessment and its relationship to the fundamental rights assessment
  • Automated individual decisions, data subject rights and data processing agreements
  • Compliance roadmap: priorities, ownership and regular review
Module 6 Practice lab: Banking
  • Credit file analysis
  • Regulatory monitoring
  • Client meeting preparation
  • KYC research support
  • Complaint classification
  • Internal knowledge assistant
Module 7 Data protection, quality & transfer to daily work
  • AI use in banks is subject to supervisory requirements such as the German MaRisk, DORA for ICT risk and third-party providers, banking secrecy and the GDPR. Creditworthiness assessments of natural persons are classified as high-risk under the EU AI Act, with additional obligations.
  • 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

Credit file analysis

An AI assistant summarises annual accounts, management accounts and business plans, calculates ratios via transparent formulas and drafts the credit memo, which analysts review before making their recommendation.

Regulatory monitoring

New circulars, guidelines and consultations are collected and summarised automatically; AI maps them to affected departments and produces an initial gap list against existing policies.

Client meeting preparation

Relationship managers receive a concise briefing from approved data sources covering product holdings, open topics and suggested questions, without AI making investment or credit recommendations on its own.

KYC research support

AI structures company register extracts, ownership structures and adverse media, proposes likely beneficial owners and documents sources so that staff can complete reviews faster.

Complaint classification

Incoming complaints are categorised by topic, urgency and product, deadlines are flagged and draft responses prepared for the complaints team to review and approve.

Internal knowledge assistant

An AI assistant answers questions about procedures, product terms and processes based on the bank's written rules and always cites the source for verification.

Prerequisites

No legal background is required. A basic knowledge of the GDPR and an overview of the AI applications used or planned in your area are helpful. You work at a bank or financial services provider and know the core processes of your area.

Technical requirements

All you need is a laptop with an up-to-date browser and an office suite for working with templates. No special AI licences are necessary.

Data protection & compliance

AI use in banks is subject to supervisory requirements such as the German MaRisk, DORA for ICT risk and third-party providers, banking secrecy and the GDPR. Creditworthiness assessments of natural persons are classified as high-risk under the EU AI Act, with additional obligations.

Dates & locations

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

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

Frequently asked questions

Does the EU AI Act apply to companies that only use AI tools?

Yes. Anyone using AI systems under their own authority in a professional context is a deployer. All deployers must, in particular, ensure that their staff have sufficient AI literacy. Where high-risk systems are used, for example in recruitment, further obligations apply, such as human oversight, logging and informing the people affected.

Does this course satisfy the training obligation under Article 4?

The course covers core AI literacy content and you receive a certificate of attendance that you can add to your documentation. However, Article 4 requires measures tailored to role, prior knowledge and context of use. That is why you also learn how to set up and maintain your own AI literacy concept for your organisation.

Does the course replace legal advice?

No. The training provides practical knowledge for specialists and managers so they can interpret requirements, ask precise questions and implement first measures. For binding assessments of individual systems, especially in high-risk areas, you should involve your legal department, your data protection officer or external specialist lawyers.

Does using an external AI service count as outsourcing?

It depends on the use case. Many AI services must at least be assessed as ICT third-party services under DORA, and some as outsourcing under national supervisory rules. We show which questions to clarify with information security, outsourcing management and compliance before a tool goes into production.

May AI decide on loans?

Credit decisions remain the responsibility of authorised staff. AI can prepare documents and analyses. If AI systems are used to assess the creditworthiness of natural persons, the high-risk obligations of the EU AI Act apply, together with transparency and explanation duties towards customers.

How much does “EU AI Act & AI Compliance for Banks” 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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