Training course · Lovable · Banking

Lovable for Banks

Build web apps from prompts: take Lovable from idea to a working React app with Supabase backend, GitHub sync and deployment.

Duration
1 day (7 hrs)
Format
Online or on-site
Language
German or English
Participants
open dates or exclusive for your team
Certificate
Certificate of attendance

Overview

“Lovable 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 Lovable productively, safely and transparently in Banking – from the fundamentals to advanced workflows.

Lovable lets you build web applications simply by describing what you need, with no programming knowledge required. In this course, business users from marketing, sales, HR, operations or product management learn how to turn an idea into a clickable, working application within hours: a landing page for a campaign, an internal tool for logging requests, a simple customer portal or a prototype that helps you pitch an idea convincingly inside your organisation.

The course is hands-on throughout. You work on a small project of your own and learn to state requirements clearly, store data securely, set up logins and publish the result. Just as important is a realistic perspective: which projects you can deliver without IT support, when to involve IT or your data protection officer, and how to hand a successful prototype over to a development team. That way you use Lovable productively without creating shadow IT or security risks.

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 describe requirements in a way that lets Lovable generate a usable web application.
  • You create a landing page with a form and publish it on your own.
  • You build an internal tool with login, data storage and roles without any coding.
  • You develop clickable prototypes and use them to align with stakeholders.
  • 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 From idea to first draft
  • What Lovable can do and what happens behind the scenes, explained plainly
  • Breaking an idea down into goal, user groups, pages and content
  • Writing your first prompt and judging the result
  • Making small, precise change requests instead of starting from scratch
Module 2 Landing pages and web presence
  • Campaign and event pages with a clear message and call to action
  • Adding images, copy and your corporate design
  • Contact and registration forms that store submissions
  • Checking how pages look on mobile and desktop
Module 3 Internal tools and forms
  • Building input forms, overview lists and simple dashboards
  • Storing data in a database without writing SQL
  • Setting up logins and roles: who may see and change what
  • Spotting typical errors and fixing them with the undo history
Module 4 Customer portals and prototypes
  • Simple portals for customers or partners with a protected area
  • Clickable prototypes for product ideas and stakeholder presentations
  • Collecting feedback and implementing iterations in a focused way
  • Handing a well-documented prototype over to development or IT
Module 5 Publishing, security and ground rules
  • Publishing your app and making it available on your own domain
  • Personal data, GDPR and coordination with IT and data protection
  • Costs, usage limits and realistic effort
  • Recognising when a project belongs in professional developers’ hands
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

Confident use of a web browser and standard office software is all you need. No programming knowledge is required. You work at a bank or financial services provider and know the core processes of your area.

Technical requirements

A laptop with an up-to-date browser, a Lovable account (a paid plan is recommended for intensive use) and free GitHub and Supabase accounts.

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 Online Request
  • Mon, 30 November 2026 Hanover Request
  • Tue, 15 December 2026 Online Request
  • Wed, 13 January 2027 Online Request
  • Wed, 27 January 2027 Munich Request
  • Thu, 4 February 2027 Online Request

Frequently asked questions

Do I own the code Lovable generates?

Yes. The output is standard React and TypeScript code that you can push to your own repository via the GitHub sync. From there it can be developed, tested and deployed entirely independently of Lovable. In the course we show you how to set this up properly from day one so you avoid any lock-in.

Is Lovable suitable for production applications?

For prototypes, MVPs, internal tools and modest customer-facing apps, yes, provided you review security and the data model carefully. Supabase Row Level Security, secrets handling and the maintainability of a growing codebase all need attention. The course covers exactly which checks make sense before you go live.

How does Lovable differ from Cursor or Claude Code?

Lovable is a browser-based app builder with a fixed stack, built-in hosting and Supabase integration, which makes it ideal for getting started quickly. Cursor and Claude Code work inside any existing codebase and technology. Many teams combine them: start in Lovable, then continue in the editor via GitHub.

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 “Lovable for Banks” cost?

The course costs a flat €949 plus VAT per participant – whether online or on-site. This includes 1 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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