Finance Process Automation Training Course

Day 1 Automation Foundations for Finance

Introduction

We begin by outlining the scope of the six-day programme and how each day builds upon the previous one. You will be introduced to the sample finance data used throughout the course, and we will discuss the processes that consume the most of your monthly time. This provides real-world examples to reference throughout the week.

Deciding What to Automate

Not every task is worth automating, so we start by learning how to distinguish them. We examine indicators of a good candidate: work that repeats, follows clear rules, involves high volume, and is prone to errors. We also discuss tasks that should remain manual, such as those requiring judgement or occurring only annually. Finally, you will learn a simple method to estimate the time savings an automation could provide, helping you determine where to begin.

Hands-on: Score a list of common finance tasks against these criteria and select the strongest candidates.

Mapping a Process

Automating a process without first mapping it often means automating its inefficiencies. In this module, you will learn to break a process down into its inputs, steps, decisions, handoffs, and outputs. We will identify where work tends to stall and where errors commonly occur, as these points often indicate where automation will yield the greatest benefit.

Hands-on: Map one real process from your own work, from the initial input to the final output.

The Automation Tool Landscape

Here we provide a clear overview of the tools covered in the course and how they integrate. Power Query prepares data, Power BI reports on it, Power Automate moves information and triggers actions, and Copilot assists with drafting and analysis. We also explain the role of n8n and how connectors enable these tools to communicate with your existing systems.

Hands-on: Match each step of your mapped process to the most suitable tool.

Data Hygiene

Automation relies on clean, consistent data, so this module covers the habits that facilitate this. We examine the importance of Excel tables, maintaining consistent column structures, and setting correct data types. We also discuss file naming conventions and maintaining a single source of truth to prevent conflicting versions of the same data.

Hands-on: Convert a messy workbook into properly structured Excel tables.

Licences and Access

Many automation projects stall because participants discover mid-process that they lack the correct licence. We explain in plain terms what a standard Microsoft 365 licence includes and what requires a premium licence. You will also learn how to verify your own access rights.

Hands-on: Check your own licences and access against the tools used in the course.

Day 2 Power Query

Getting Started with Power Query

Power Query is integrated into Excel and Power BI, and many finance users already possess it without realising. We open the Power Query editor and walk through its functionality. You will see how each change is recorded as an applied step, ensuring your work is repeatable. We also cover options for loading results back into Excel or Power BI.

Hands-on: Open the editor and load a bank statement CSV file.

Connecting to Data

Finance data arrives in various formats, so we practise connecting to the most common sources: CSV files, Excel workbooks, tables, and entire folders. We address common issues such as missing headers, unusual delimiters, and character encoding. By the end, you will be able to import data from your standard exports with confidence.

Hands-on: Connect to a ledger export and a bank statement.

Core Cleaning

This is where significant time savings are achieved. We work through essential cleaning steps: removing unwanted rows and columns, splitting columns, setting data types, and replacing values. We pay particular attention to dates and number formats, which are frequent sources of error in finance data.

Hands-on: Clean a messy bank export into a usable table.

Reshaping Data

Budgets and reports are often structured with one column per month, which may look fine on screen but is difficult to analyse. We demonstrate how to unpivot this data into a long format suitable for pivot tables and Power BI. We also cover grouping and summarising data within Power Query.

Hands-on: Unpivot a budget sheet into a long table.

Combining Data

Finance work often involves integrating multiple sources. We cover appending queries to stack data from different periods and merging queries to look up information from another table. We explain the various join types in plain terms. We then highlight one of Power Query’s most useful features: automatically combining every file in a folder, so adding a new month is as simple as dropping in a file.

Hands-on: Combine twelve monthly exports from a single folder.

Reconciliation Preparation

Here we apply your new skills to a common finance task. You will learn to match bank and ledger records using shared keys such as references and amounts. We also show how to flag mismatches, allowing you to focus on exceptions rather than checking every line.

Hands-on: Build a query that matches bank and ledger records and lists unmatched items.

Refresh and Maintenance

The true benefit of Power Query is building the process once and refreshing it monthly. We show you how to refresh queries and add new data without repeating work. We also cover documenting your steps for colleagues and avoiding common changes that break a query.

Hands-on: Add a new month’s file and refresh the query.

Day 3 Power BI

Power BI Fundamentals

We introduce Power BI Desktop, where reports are built, and the Power BI service, where they are shared. You will become familiar with the report, model, and data views and their respective purposes. We then import the data you cleaned on Day 2, allowing you to build on your previous work.

Hands-on: Load the Day 2 cleaned data into Power BI.

Data Modelling

A well-constructed model simplifies reporting, while a poor one causes frustration. We explain the star schema in plain terms: fact tables holding transactions, dimension tables describing them, and a date table enabling period reporting. We also cover table relationships and the importance of filter direction.

Hands-on: Build a model containing actuals, budget, accounts, and dates.

Essential DAX

DAX is the formula language for Power BI. We keep it practical, focusing on the few functions finance users need most. You will learn the difference between calculated columns and measures, and how to use SUM, CALCULATE, and DIVIDE to produce reliable figures.

Hands-on: Write measures for actual, budget, and variance.

Time Intelligence

Finance reporting relies on comparing periods. In this module, you will learn to calculate month-to-date and year-to-date figures and compare them with the prior year. These measures form the core of most monthly management reports.

Hands-on: Add year-to-date and prior-year variance measures to your model.

Report Design

An effective report conveys key information quickly. We cover selecting the right visuals for finance data and when a simple table is superior to a chart. You will also learn to add slicers and drill-downs, and use conditional formatting to highlight significant variances.

Hands-on: Build the budget versus actual report page.

Sharing and Refresh

A report is only useful if the right people can see current figures. We show you how to publish to a workspace and share reports with colleagues. We also cover setting up scheduled refreshes and best practices for shared workspaces.

Hands-on: Publish your report and set a refresh schedule.

Day 4 Power Automate

Automation Basics

We introduce Power Automate and its capabilities for finance teams. You will learn the differences between automated flows (triggered by events), instant flows (manually triggered), and scheduled flows (running at set times). We also explain standard versus premium connectors, which impacts what you can build with your licence.

Hands-on: Build a simple instant flow.

Triggers and Actions

Every flow starts with a trigger and executes actions. We examine triggers useful in finance, such as new email arrivals, new file additions, or specific times. We then cover common actions in Outlook, SharePoint, Excel, and Teams.

Hands-on: Trigger a flow from an email with an attachment.

Conditions and Expressions

Real processes involve decision-making, so this module shows you how to build this into a flow. We cover conditions, switch statements, and loops. We also introduce simple expressions for handling dates, text, and numbers, focusing on what finance users will actually need.

Hands-on: Route invoices differently based on supplier or amount.

Approvals

Approvals are among the most valuable uses of Power Automate in finance. We examine different approval types, how to send requests to one or multiple people in sequence, and how to record outcomes. This provides a clear audit trail of who approved what and when.

Hands-on: Add an approval step to your flow and log the result.

Error Handling

Flows can fail, and knowing how to identify and fix issues is as important as building the flow. We show you how to read run history and diagnose problems. We also cover run-after settings, retries, and failure notifications to ensure you are alerted before deadlines are missed.

Hands-on: Intentionally break your flow, then locate and fix the fault.

Invoice Intake Build

Now we integrate the day’s learning into a complete working process. Your flow will save invoice attachments from email to SharePoint, log invoice details to a list or Excel table, and send each invoice for approval. This pattern is adaptable to many other finance processes.

Hands-on: Complete the invoice intake and approval flow from start to finish.

AI Builder Demonstration

To conclude the day, the trainer demonstrates how AI Builder can read invoices and extract details like supplier, date, and amount automatically. We explain the licensing requirements and help you assess whether the time saved justifies the cost for your invoice volume.

Hands-on: Instructor demonstration only.

Day 5 n8n

n8n Fundamentals

n8n is a versatile automation tool capable of connecting to almost any system with an API. We start with the basics: the editor, workflows, nodes, and executions. You will see how data moves from one node to the next, which is key to understanding n8n.

Hands-on: Build and run your first workflow.

Triggers and Credentials

We examine different ways to initiate a workflow: on a schedule, via webhook, or manually. We also cover how n8n stores credentials for connecting to other systems and best practices for keeping them secure.

Hands-on: Set up a scheduled trigger and connect an email account.

Working with APIs

Many finance systems and data services offer APIs, and n8n’s HTTP Request node allows you to use them. We show you how to read API documentation without being a developer, send requests, and interpret the JSON data returned.

Hands-on: Fetch daily exchange rates from a public API.

Transforming Data

Data from an API rarely arrives in the required format. We cover filtering records, mapping fields to correct names, and applying simple logic using IF and Switch nodes. By the end of this module, you will be able to transform raw data into a clean summary.

Hands-on: Shape the exchange rate data into a summary table.

Scheduled Finance Workflow

Here you combine the day’s learning into a complete workflow. It runs on a schedule, collects data, writes results to a spreadsheet, and sends a summary via email or Teams. We also add error handling to notify you if a run fails.

Hands-on: Complete the scheduled data collection and notification workflow.

Choosing Between n8n and Power Automate

With both tools now familiar, we compare them side by side. We examine the connectors each offers, hosting options, costs, required skills, and support structures. This helps you select the right tool for each process rather than defaulting to one.

Hands-on: Compare both tools for the process you mapped on Day 1.

Hosting and Data Protection

The location where automation runs impacts data protection. We compare cloud-hosted and self-hosted n8n and their implications for your organisation. We also cover your obligations under POPIA when financial or personal information passes through a workflow.

Hands-on: Review a workflow for data protection risks.

Day 6 Copilot and Governance

Copilot Overview

We begin with a realistic view of what Microsoft 365 Copilot can and cannot do in finance work. We explain how Copilot uses your data and why it only accesses what you are permitted to view. This sets clear expectations before you start using it.

Hands-on: Explore Copilot across Excel, Word, Outlook, and Teams.

Copilot in Excel

We demonstrate how to ask Copilot in Excel for analysis, formulas, summaries, and charts. The emphasis is on verifying every result against source data, as Copilot may produce plausible but incorrect answers. You will develop the habit of verifying before relying on its output.

Hands-on: Analyse a trial balance with Copilot and verify every figure.

Variance Commentary

Writing variance commentary monthly is time-consuming, and Copilot can produce a useful first draft. Using the Day 3 data, you will ask Copilot to draft budget versus actual commentary. We then show you how to identify statements unsupported by the data and correct them before distribution.

Hands-on: Write and verify variance commentary for the Day 3 report.

Communication and Collaboration

We examine how Copilot can assist with the writing surrounding finance work. You will practise drafting executive summaries in Word and emails in Outlook. We also cover meeting recaps and follow-up actions in Teams.

Hands-on: Turn your variance commentary into an executive summary.

Copilot with Power BI

Copilot can answer questions about a Power BI report and summarise its contents. We test this on the report you built on Day 3 and examine where it adds value. We also discuss the limitations of AI-generated insights and why human interpretation remains essential.

Hands-on: Ask Copilot questions about your Day 3 report.

Prompting Well

The quality of Copilot’s output depends heavily on how you ask. We cover practical techniques: providing context, specifying desired formats, and refining requests step by step. You will also learn to save effective prompts for reuse in monthly reporting.

Hands-on: Build a short prompt library for your monthly reporting.

Governance

Automations require maintenance, or they become risks when staff leave or systems change. We cover data privacy and POPIA, access permissions, and documenting each automation. We also discuss naming an owner and backup for every automation, and reviewing and retiring those no longer needed.

Hands-on: Create an automation register entry for each build from the course.

Summary and Next Steps

We conclude by reviewing what you have built over the six days. We discuss how to select your first automation to implement back at work and where to find help if you encounter difficulties.