Training course · Vibe Coding · Banking

Vibe Coding for Banks

Build software in natural language: from prompt to app, rapid iteration, quality and security checks, and turning prototypes into production.

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

This course connects Vibe Coding with the everyday processes of Banking. Participants work on realistic scenarios and leave with prompts, workflows and checklists they can use straight away.

Vibe coding lets business users without any programming knowledge build digital tools of their own. You describe in everyday language what a mini app, dashboard or form should do, and tools such as Lovable, Claude, ChatGPT Canvas or Replit generate a working solution. Helpers for your daily work can take shape quickly, without waiting for IT to free up capacity. This course shows you step by step how to make it work, which habits lead to good results, and what really matters along the way.

During the course you build applications drawn from your own work: a KPI overview, a data entry form, a small calculator or an automation for recurring chores. At the same time you learn to assess the risks realistically. Which data may go into such tools, who will run and maintain the solution, and when must IT be involved? With this knowledge you can create useful solutions that are accepted within the organisation and remain secure and sustainable in the long term.

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 build your own mini apps, dashboards and forms through vibe coding without programming skills.
  • You describe requirements clearly enough for AI tools to produce usable solutions.
  • You improve your applications step by step and check the results for accuracy.
  • You automate simple recurring tasks in your working environment.
  • 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 Understanding vibe coding as a business user
  • What vibe coding is and what you can achieve without programming skills
  • Tools at a glance: Lovable, Claude, ChatGPT Canvas, Replit and similar platforms
  • Spotting good candidates for your own tools at work
  • Realistic expectations: strengths, limits and common pitfalls
Module 2 Describing and building your own mini app
  • Capturing goal, users, inputs and desired outcome in plain words
  • Generating a first version and clicking through it together
  • Improving look, wording and flow with targeted feedback
  • Saving milestones and returning to an earlier version when things go wrong
Module 3 Dashboards, forms and calculators
  • Turning Excel or CSV data into an interactive dashboard
  • Building entry forms with required fields and plausibility checks
  • Creating calculators and decision aids for your team
  • Checking results for accuracy with test data and spot checks
Module 4 Automating routine work
  • Identifying recurring tasks that lend themselves to automation
  • Building simple automations for reports, notifications or file storage
  • Discussing connections to existing tools via approved interfaces
  • Documenting automations clearly and handing them over to colleagues

Day 2

Module 5 Risks and coordination with IT
  • Which data may and may not go into AI tools: data protection and confidentiality
  • Managing access rights, sharing settings and public links deliberately
  • Avoiding shadow IT: clarifying operation, maintenance and ownership
  • Preparing a handover to IT when a solution grows or becomes critical
Module 6 Hands-on project: your own solution for Banking
  • Credit ratio calculator – An app that imports balance sheet and income statement figures, calculates ratios such as equity ratio, debt service coverage and leverage and visualises multi-year trends.
  • Regulatory tracker – An internal tool that logs publications, manages owners and implementation deadlines and shows implementation status per department at a glance.
  • Meeting minutes assistant – A form-based tool that turns notes from advisory meetings into structured minutes with mandatory fields and flags missing documentation points.
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.

Possible hands-on projects

Credit ratio calculator

An app that imports balance sheet and income statement figures, calculates ratios such as equity ratio, debt service coverage and leverage and visualises multi-year trends.

Regulatory tracker

An internal tool that logs publications, manages owners and implementation deadlines and shows implementation status per department at a glance.

Meeting minutes assistant

A form-based tool that turns notes from advisory meetings into structured minutes with mandatory fields and flags missing documentation points.

Prerequisites

No programming knowledge is required; confident use of a browser, office applications and spreadsheets is enough. You work at a bank or financial services provider and know the core processes of your area.

Technical requirements

Your own laptop with an up-to-date browser, Git and an AI coding tool of your choice, such as an AI editor or coding agent with an active account.

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.

  • Tue, 24 November 2026 – Wed, 25 November 2026 Online Request
  • Mon, 30 November 2026 – Tue, 1 December 2026 Munich Request
  • Thu, 10 December 2026 – Fri, 11 December 2026 Online Request
  • Tue, 19 January 2027 – Wed, 20 January 2027 Hanover Request
  • Tue, 2 February 2027 – Wed, 3 February 2027 Online Request
  • Tue, 9 February 2027 – Wed, 10 February 2027 Berlin Request

Frequently asked questions

Is vibe coding only suitable for quick prototypes?

Vibe coding shines with prototypes, internal tools and experiments. With the right practices, namely clear specifications, tests, reviews and sound version control, results can also be turned into production-ready applications. The course teaches you to manage that transition deliberately and to recognise early on when rebuilding is the wiser option.

Which tools are used in the course?

The course is vendor-neutral. We work with the main tool categories: AI editors such as Cursor or Windsurf, coding agents such as Claude Code or Codex, and browser-based app builders. You are welcome to use your preferred tool, as the principles of specification, iteration, quality and security apply to all of them.

How should I deal with security risks in generated code?

Generated code often contains typical weaknesses such as hard-coded credentials, missing input validation or overly open interfaces. You learn to check specifically for these patterns, build security requirements into the specification from the start, use automated scanning and require a deliberate human sign-off before every deployment.

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 “Vibe Coding 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.

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