Training course · Google Gemini · Banking

Google Gemini for Banks

Make productive use of Google Gemini and Gemini in Workspace: Docs, Sheets, Gmail, Meet, custom Gems and NotebookLM for your sources.

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

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

For organisations running on Google Workspace, Gemini is the natural AI assistant: it is available as a standalone app and is also built directly into Gmail, Docs, Sheets, Slides, Drive and Meet. In this practical day you learn to combine both access points deliberately. You summarise email threads and draft replies, create document drafts based on existing files in Drive, structure and analyse spreadsheets in Sheets and have Meet take meeting notes automatically – always with a focus on your own day-to-day workflows.

You also build your own Gems: specialised assistants with fixed instructions and knowledge files that standardise recurring tasks across the team. With Deep Research you produce well-founded research reports, and you use NotebookLM as a source-grounded workspace that answers only from your own documents and cites the relevant passages. A dedicated module covers data protection and administration in Workspace environments. You leave with tested prompts, a working Gem and a clear picture of which Google tool suits which task.

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 use Gemini in Gmail, Docs, Sheets, Slides and Meet for your recurring tasks.
  • You write prompts that bring existing Drive files and emails into the context.
  • You build a custom Gem and share it with your team.
  • You work source-grounded in NotebookLM and obtain referenced answers from your own documents.
  • 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 Gemini fundamentals and effective prompts
  • The Gemini app and Gemini in Workspace: access points and use cases
  • Prompts with task, context, format and references to Drive files
  • Web search, Deep Research and checking sources
  • Limitations, hallucinations and critical evaluation of output
Module 2 Gmail, Docs and Slides
  • Summarising email threads and drafting context-aware replies
  • Drafting, rewriting and tailoring documents in Docs
  • Pulling in and combining content from Drive files
  • Creating presentation content and images in Slides
Module 3 Sheets and Meet
  • Structuring tables, generating formulas and cleaning data
  • Analyses, summaries and charts in Sheets
  • Letting Meet take meeting notes automatically
  • Deriving action items and decisions from meeting notes
Module 4 Gems and NotebookLM
  • Creating custom Gems with instructions and knowledge files
  • Testing, improving and sharing Gems with the team
  • NotebookLM as a source-grounded workspace for your own documents
  • Generating summaries, study aids and audio overviews from sources
Module 5 Data protection, administration and rollout
  • Privacy commitments for Workspace customers versus personal accounts
  • Drive sharing settings and how they affect Gemini results
  • Handling personal and confidential data in line with GDPR
  • Usage policies and quality assurance within the team
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

Confident everyday use of Google Workspace (Gmail, Drive, Docs, Sheets); no prior AI 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 and a Google Workspace account with Gemini features enabled; alternatively a Google account for the Gemini app and NotebookLM.

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 Online Request
  • Tue, 1 December 2026 Munich Request
  • Thu, 10 December 2026 Online Request
  • Wed, 20 January 2027 Hanover Request
  • Wed, 27 January 2027 Online Request
  • Fri, 12 February 2027 Berlin Request

Frequently asked questions

What is the difference between the Gemini app and Gemini in Workspace?

The Gemini app is a standalone chat assistant for research, writing and analysis. Gemini in Workspace works directly inside Gmail, Docs, Sheets, Slides and Meet and can draw on your emails and Drive files. In practice they complement each other: the app for open questions, the integrated version for work on specific documents.

Why would I use NotebookLM in addition to Gemini?

NotebookLM restricts its answers to the sources you upload – policies, studies or project files, for example – and points to the relevant passages. This reduces hallucinations and works well for getting up to speed on a topic, building internal knowledge collections or preparing training material. Gemini is broader in scope and can also draw on the web.

Is my Workspace data used to train Gemini?

For Google Workspace customers, Google commits that content from Gmail, Drive and other services is not used to train models outside your domain without permission. Different rules apply to personal accounts. Either way, GDPR and your internal policies remain decisive – in the course we review the relevant settings together.

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 “Google Gemini 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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