AI in Finance
Train financial teams for more precise control, faster analysis and total confidentiality
Financial institutions face a dilemma: their teams are overwhelmed with repetitive tasks (Excel macros, monthly reporting, invoice analysis, regulatory monitoring) while their competitors are already testing AI to automate these processes.
But here's the block: confidentiality constraints in finance are non-negotiable. An accountant cannot copy-paste sensitive data into free ChatGPT. A financial auditor cannot risk a client data leak. A portfolio analyst must anonymize before using AI.
Result? The majority of financial institutions hesitate. They know AI could transform their efficiency, but don't know how to integrate it while respecting their regulatory obligations.
What it really costs
Without a secure framework to deploy AI, your financial teams waste considerable time on tasks that AI could accelerate:
Excel macros
Your employees spend hours creating macros that generative AI could code in 3 minutes.
Data analysis
Extracting insights from a 100-row table takes 2h. AI does it in 5 minutes with ready-to-present charts.
Monthly reporting
Your accountants are overwhelmed, lack time to follow their clients, and cannot produce regular summary reports. Client relationships suffer.
Sector monitoring
Analyzing CEO salaries of the 25 largest Swiss companies? Before AI, you had to download 25 PDFs and search manually. Today, AI does it in 15 minutes.
Fraud detection
Manual verification processes miss weak signals that AI could detect.
Meanwhile, other financial institutions have already trained their teams and are saving 4 to 10 hours per week per employee.
The Maijin solution
We are not AI consultants. We are trainers specialized in supporting financial institutions. We understand your regulatory constraints. We know that confidentiality is not optional.
We have supported prestigious financial institutions in Switzerland and France: Lombard Odier, Rentes Genevoises, BCV, Ethos Fund, the Financial Inspection of Canton Valais, the State Pension Fund of Geneva, the Paris Order of Chartered Accountants, and many more.
Our approach:
1. Finance sector expertise
We know your professions: audit, accounting, portfolio management, financial analysis, management control. Our training covers use cases with real impact.
2. Security and confidentiality first
We systematically integrate confidentiality best practices: data anonymization, use of secure enterprise versions, compliance with regulatory obligations.
3. Signature support in 3 stages
3 half-days spaced over 6 weeks. Between each session, your teams practice on their real cases. We anchor practices, correct prompts, adjust.
Result: your teams save time, stay compliant, and develop real autonomy with AI.
Our results in finance
vs 69% average in consulting
overall satisfaction
want to increase their AI usage
of Valais inspectors kept the paid version
What your teams will master
1. Automate repetitive Excel tasks
Your teams waste considerable time on Excel macros. Generative AI codes in minutes what took hours.
Concrete case : An inspector from the Financial Inspection of Canton Valais started using ChatGPT to create macros after our first half-day. By the second session, she was using the tool every day and saving "tremendous time" in her words.
Skills developed
- Creating automated VBA macros from natural language descriptions
- Debugging and optimizing existing code
- Automating repetitive tasks (formatting, complex calculations, consolidation)
- Creating dynamic dashboards
Tools mastered : ChatGPT, Claude, Copilot for Excel
2. Analyze financial data and create visualizations
AI transforms your raw data into actionable insights with ready-to-present charts.
Concrete case : In a bank we supported, a trained employee set up a system that automatically analyzes client portfolios (anonymized data). AI analyzes dashboard screenshots and justifies investments based on geopolitical context.
Skills developed
- Excel data analysis with Code Interpreter
- Creating relevant charts and visualizations
- Extracting insights and actionable recommendations
- Sensitivity analysis and multiple scenarios
- Computer vision to analyze complex dashboards
Tools mastered : ChatGPT (Code Interpreter), Claude, Copilot, Python
3. Produce audit and control reports
Write structured, professional audit reports by dividing drafting time by 3.
Concrete case : In training, we showed how to use AI to write an audit report. Learners use voice dictation to capture observations, then AI structures and formats the complete report.
Skills developed
- Writing audit reports from voice or written notes
- Automatic structuring: findings, recommendations, procedures
- Using reasoning models for complex procedures
- Clear and actionable executive summaries
Tools mastered : ChatGPT (with voice transcription), Claude, reasoning models
4. Accelerated sector and regulatory monitoring
Deep Research feature scans the web autonomously and produces 15-page sourced reports in under 15 minutes.
Concrete case : Valais Canton Financial Inspectors must audit organizations that received state aid. Before each audit, they use Deep Research to scan all public information about the organization and its sector.
Skills developed
- Automated regulatory monitoring on a sector or company
- Searching for specific accounting and tax information
- Multi-source comparative analysis
- Sourced and structured sector reports
Tools mastered : ChatGPT (Deep Research), Perplexity, Gemini Deep Research
5. Create personalized monthly client reports
Accountants are overwhelmed and don't have time for quality monthly follow-up with each client.
Concrete case : At the Paris Order of Chartered Accountants, we created an assistant that takes the month's income statement, analyzes important data, creates charts and generates a 5-6 page PDF with an email ready to send.
Skills developed
- Creating custom GPT assistants for client reporting
- Automated income statement analysis
- Generating relevant charts and visualizations
- Writing personalized summary emails
Tools mastered : ChatGPT, custom assistants, Gamma.app
6. Improve computer vision for invoices
New AIs have significantly improved image analysis capabilities for transcribing paper and digital invoices.
Concrete case : While supporting the Paris Order of Chartered Accountants, we explored how a system combining computer vision + LLM could handle paper invoices and digital invoices from emails and other sources.
Skills developed
- Automated data extraction from invoices (paper or digital)
- Automatic expense classification
- Validation workflows with alerts above certain amounts
- Integration with accounting software
Tools mastered : ChatGPT (vision), Claude, integration APIs
7. Financial advice and business plan creation
Reasoning models are now reliable enough to help with financial decisions and forecasting.
Concrete case : A participant at BioVal used ChatGPT to create his first order on his PEA. The trainer personally uses reasoning models to choose his ETFs.
Skills developed
- Investment portfolio analysis with reasoning models
- Creating business plans and financial forecasts
- Advice on financial products (ETFs, REITs, etc.)
- Creating GPT assistants to track products subscribed by each client
Tools mastered : ChatGPT (reasoning models), Claude, custom assistants
8. Fraud detection and automated alerts
Generative AIs trained on large datasets can detect anomalies and weak signals in financial flows.
Skills developed
- Setting up automatic alerts on unusual transactions
- Detecting potential fraud patterns
- Consistency analysis on large data volumes
- Reinforced verification workflows
Tools mastered : ChatGPT, Claude, reasoning models
Detailed case studies
Case 1: Rentes Genevoises - Copilot for 365 Training
Context : Geneva pension institution (40+ employees), had just obtained Copilot for 365.
Challenge : Train all departments (IT, Insurance, Accounting, Finance, Marketing) in a concrete and motivating way.
Format : 7 2-hour workshops per department (3 to 10 people per group)
Results :
- 92.31% overall satisfaction
- NPS of 73.08% (vs 69% average in consulting)
- 24 of 26 respondents want to increase their AI usage
Impact : Employees integrated Copilot into their daily tools with curiosity and confidence.
Case 2: Lombard Odier - AI Support for Front Teams
Context : Geneva private bank, Front teams (Global Asset and Corporate Advisory)
Challenge : Initiate teams to generative AI securely in a strict banking context.
Format : 2 half-days spaced 3 weeks apart (2 groups of 4-5 people)
Program :
- Block 1: Acculturation (AI overview, prompt engineering, banking security, identifying 5 priority use cases)
- Block 2: Advanced application (custom GPTs, multimodal features, impact case mapping)
Results :
- 96.88% satisfaction
- 100% of participants want to increase their usage
- "Very interesting and useful training for my daily work"
Impact : One employee created an automatic client portfolio analysis system that justifies investments based on geopolitical context.
Case 3: Financial Inspection of Canton Valais
Context : Valais state budget control body (22 inspectors)
Challenge : Train financial auditors to use AI for their audit missions
Format : 3 spaced half-days
Results :
- One inspector used ChatGPT every day to create macros after the first session
- 80% of inspectors asked to keep the ChatGPT Enterprise version
- Deep Research became their reference tool for audit preparation
Case 4: State Pension Fund of Geneva
Context : Complete financial management
Format : 3 spaced half-days with demonstration of autonomous AI agents
Impact : After seeing the capabilities of AI agents with computer access, the financial director revised her vision of the organization. She moved from the hypothesis "employees assisted by AI" to "employees + AI working autonomously on certain tasks".