Training course · n8n · Banking

n8n for Banks

Workflow automation with n8n and AI: master nodes, the AI Agent node, integrations and GDPR-friendly self-hosting in practice.

Duration
2 days (14 hrs)
Format
Online or on-site
Language
German or English
Participants
open dates or exclusive for your team
Certificate
Certificate of attendance

Overview

“n8n for Banks” is designed for roles such as Corporate and retail relationship managers, Credit analysts and credit operations staff and Compliance, AML and risk management teams and shows step by step how to use n8n productively, safely and transparently in Banking – from the fundamentals to advanced workflows.

n8n is a flexible workflow automation platform that combines visual flows with language models and hundreds of integrations. Unlike many cloud services, n8n can also be self-hosted, so your data can stay in your own data centre or with a European hosting provider. Over two days you will learn how triggers, nodes and data flows fit together, how to transform data between applications and how to automate recurring tasks from your day-to-day work reliably.

The core of the course is the combination of automation and AI. Using the AI Agent node, chat models, memory and tools, you build workflows that classify emails, summarise documents, enrich records or answer enquiries. You learn to catch errors, test workflows and document them properly. Finally, you look at hosting options, credential management and data protection, so that your automations run stably, securely and in line with GDPR once they go into everyday operation.

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 build n8n workflows independently using triggers, logic nodes and data transformations.
  • You can connect n8n to the applications you use every day and fall back on the HTTP Request node where needed.
  • You can use the AI Agent node and other AI building blocks for classification, extraction and summarisation.
  • You can safeguard workflows with error handling, validation and human approval steps.
  • 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

Day 1

Module 1 Fundamentals: workflows, triggers and nodes
  • Getting to know the n8n interface, canvas and execution view
  • Trigger types: schedules, webhooks, incoming email and app events
  • Understanding items and JSON data and working with expressions
  • Using core nodes such as Edit Fields, IF, Switch, Merge and Loop Over Items
Module 2 Integrations and data processing
  • Connecting common applications: email, spreadsheets, CRM, collaboration and cloud storage
  • Using the HTTP Request node for APIs without a ready-made integration
  • Creating, managing and sharing credentials securely within the team
  • Filtering, merging and reshaping data and writing it to target systems
Module 3 AI in n8n: the AI Agent node and LLM building blocks
  • Connecting chat models from different providers as well as locally hosted models
  • Configuring the AI Agent node with a system prompt, memory and tools
  • Automating classification, structured data extraction and summarisation
  • Using your own documents via vector stores for retrieval-augmented generation
Module 4 Error handling, testing and maintainability
  • Setting up error workflows, retries and failure notifications
  • Validating AI output and defining fallbacks for unusable responses
  • Working with pinned test data and tracing past executions
  • Modularising, naming and documenting workflows for colleagues

Day 2

Module 5 Self-hosting, data protection and operations
  • Cloud versus self-hosted: effort, control and licensing model compared
  • Assessing data flows to AI providers against GDPR requirements
  • Managing access rights, logging and retention of execution data
  • Adding human-in-the-loop approval steps to automated processes
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

You should be confident with common office applications and have basic experience with AI assistants. No programming is required, although a basic grasp of structured data is helpful. You work at a bank or financial services provider and know the core processes of your area.

Technical requirements

You will need a laptop with an up-to-date browser. We provide an n8n environment for the exercises, or you can use your own instance; API keys for a language model are set up together during the course.

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.

Suggested dates

All dates are suggestions – your preferred date is always possible.

  • Wed, 25 November 2026 – Thu, 26 November 2026 Online Request
  • Mon, 7 December 2026 – Tue, 8 December 2026 Salzburg Request
  • Mon, 14 December 2026 – Tue, 15 December 2026 Online Request
  • Mon, 11 January 2027 – Tue, 12 January 2027 Online Request
  • Thu, 28 January 2027 – Fri, 29 January 2027 Bremen Request
  • Thu, 4 February 2027 – Fri, 5 February 2027 Online Request

Frequently asked questions

Do I need to code to work with n8n?

No. Most workflows are built visually by connecting nodes. During the course you also learn simple expressions to reference and reshape data precisely. A Code node is available for special cases but is not essential. A logical understanding of processes and data fields is entirely sufficient to get started.

Why is n8n attractive from a European data protection perspective?

n8n can be self-hosted, for instance on your own servers or with a European hosting provider. This keeps you in control of where workflow and execution data is stored. What still matters is which data you send to external AI services. On the course you learn to assess these data flows and, where appropriate, connect locally hosted models.

How does n8n differ from Make or Power Automate?

All three automate processes across applications. n8n stands out for its self-hosting option, its fair-code licensing and particularly flexible AI building blocks such as the AI Agent node. Make offers a very approachable cloud interface, while Power Automate excels at deep Microsoft integration. The course puts these differences into context for typical scenarios.

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 “n8n for Banks” cost?

The course costs a flat €949 plus VAT per participant – whether online or on-site. This includes 2 training day(s) with a live trainer, course materials, a lab environment and a certificate of attendance.

Can I suggest my own date?

Yes. Our suggested dates are just a guide. In the request form you can always describe your preferred date or period in free text – we check availability and confirm 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 or Kaiserslautern. We can also run the course exclusively for your team.

More courses for Banks

More n8n courses

All 45 n8n courses

n8n · Munichn8n · Salzburgn8n · Berlinn8n · Augsburgn8n · Hanovern8n · Bremenn8n · Stuttgartn8n · Kaiserslauternn8n · Online