AI for Finance, Risk & Audit
Move from spreadsheets to AI-augmented analysis, controls, and assurance.
A domain track for finance, risk and internal-audit professionals. Apply AI to real workflows — financial analysis, forecasting, anomaly and fraud detection, controls testing and audit automation — with explicit attention to governance, model risk and regulatory expectations.
- 42 hours
- 16 modules
- Cohort-based · flexible batches
Pricing is set per cohort and organisation — Talk to us.
Outcomes
What you'll be able to do
Concrete, demonstrable skills — the kind you can show in an interview or put to work on day one.
Apply AI to real finance and audit workflows: analysis, forecasting, anomaly detection, controls
Build three-statement models and multi-scenario forecasts with Copilot and ChatGPT
Detect fraud and anomalies across full populations rather than small samples
Automate audit and month-end-close tasks with governed workflows
Reason about EU AI Act, data residency and model risk for finance AI use cases
Curriculum
The modules
Sequenced to build on each other. Each module is a first-class unit — the same ones our AI recommender draws on to map a personalised track.
16
modules
54.5
hours total
AI Foundations for Finance Professionals
What LLMs can and cannot do for finance work, the responsible-use baseline for regulated environments, and a starter prompt library for analysis, variance commentary and drafting.
Financial Analysis & Modeling with Copilot & ChatGPT
Accelerate analysis — generate Excel formulas and pivots from natural language, build three-statement models and produce variance commentary using Copilot in Excel/Power BI and ChatGPT for ad-hoc analysis.
Introduction and Personalization
Introduces Claude Cowork's core capabilities and guides learners through setting up and customizing their workspace for personal and professional use cases.
Financial Workflow Automation
Leveraging Cowork to automate complex financial workflows, streamline data-heavy reporting and improve bookkeeping accuracy.
Fundamentals of n8n
Introduces n8n's core concepts — workflows, nodes, triggers, actions and data flow. Learners install n8n, explore the interface and build their first automation from templates.
Spreadsheet Automation
How n8n integrates with spreadsheet platforms to automate data processing and management. Learners build an Expense Tracker connected via Telegram and Google Sheets.
Document Processing Automation
Automated document handling — upload triggers, classification logic and route-based processing. Learners build an AI Document Summarizer, an Invoice Processing System and Document Storage Automation.
Business Process Automation
Process mapping, inefficiency identification and multi-step workflow design for organizational use. Learners build a Job Application Processing Workflow and a Query Assisting Agent.
Introduction to Gemini in Workspace
What Gemini is, how it integrates with Workspace apps, the benefits of AI-first workflows, and an overview of core tools beyond the standard apps.
Expert Workflows and Real-World Implementation
Designing end-to-end Workspace workflows, building reusable prompt-template systems, AI for decision support, and a capstone workflow across collaborative AI environments.
Forecasting & Scenario Analysis with AI
Build driver-based forecasts and run scenario/sensitivity analyses with AI-assisted modeling, plus an intro to ML time-series approaches in Python for those who want them.
Anomaly Detection & Fraud Analytics
Detect anomalies across transactions and the general ledger — how AI learns 'normal', flags deviations and cuts false positives — with hands-on journal-entry testing and Benford-style analyses.
Audit Automation & Controls Testing
Automate the audit playbook — document extraction, reconciliations, sample selection and controls testing — using AI to read contracts, invoices and ledgers and produce working papers faster.
Governance, Regulatory & Model-Risk Considerations
The controls layer — EU AI Act high-risk categories, data residency, model risk management (SR 11-7 style), explainability and audit trails — and why self-hosted/open tools matter in regulated finance.
Claude, MCP & Skills for Finance
Connect Claude to your ERP and ledger via MCP (QuickBooks, Salesforce, Postgres) on a self-hosted tenant, author Skills for reconciliation and appeal-letter workflows, and build financial dashboards with Artifacts.
Dashboards, Reporting & AI-Assisted Insight
Turn financial data into board-ready insight — natural-language dashboards, AI-generated narratives and the 'ask your data' pattern for finance leaders.
Questions
Good to know
Still wondering about something? Ask us directly in the enquiry form below.
Only for accountants/auditors?
No — for finance analysts, FP&A, risk and internal-audit professionals. Examples are tailored to each role.
Do I need Python?
No. Python appears as an optional advanced path; the core track is Excel/Power BI + Copilot/ChatGPT/n8n.
Enquire
Talk to us — we'll help you choose.
Tell us where you're starting from and what you want to build. We'll walk you through the cohort, the lab, and whether this is the right first step — or point you somewhere better.
- A real reply from our team — never a bot wall.
- Honest guidance on fit, prerequisites and timing.
- Cohort dates and how the hands-on lab time works.
Keep exploring
Programs you might pair this with
Ready to startbuilding?
Enquire about this course, book a demo, or let our AI map your perfect track. The lab is open.