AI in Finance · From IFRS reporting to investment decisions, with AI working beside you.

By the end of this course you can use AI to prepare and check an IFRS reporting pack, speed up the close, analyse and value a company, detect anomalies, and govern all of it so that a professional can sign it.

Every topic is taught through two lenses. The AI practitioner's asks how the tools work, what they are likely to get wrong and how to make their output reliable. The investment professional's asks what the numbers mean, who relies on them, and what you owe those people.

The examples follow three fictional organisations: Ardena Foods Plc, a Nigerian food manufacturer reporting under IFRS in Naira; Velra Capital, an Abuja asset manager; and Tamari Microfinance Bank. Each lesson has a worked example, prompt templates you can use the same day, a checklist for verifying what the AI produces and a short practice task, and each module ends with a quiz. The course closes with a capstone: an AI-assisted IFRS reporting pack for Ardena Foods, with a model answer.

Who it is for: Accountants, finance teams, auditors, analysts and finance students (ACCA, ICAN and CFA candidates and members) in Nigeria and beyond. No coding or data science background is assumed.

Course outline

12 modules · 74 lessons · 51h 50m · 4 free previews

01Foundations: how AI really works, for finance peopleWhat machine learning, deep learning and generative AI actually are, how large language models produce their answers and why they sometimes make things up, and where the finance professional sits in an AI system that reads data, calls tools and prepares entries. The module ends by setting up a safe AI workbench: choosing tools, protecting confidential data and working within the Nigeria Data Protection Act 2023.6 lessons · 3h 30m
- Welcome: what this course will change in your workFree preview25 min
- From rules to learning: machine learning, deep learning and generative AI in plain EnglishFree preview40 min
- Large language models: tokens, context windows, why they make things up and how to make them reliable45 min
- The finance AI stack: data, models, tools, agents and where the professional sits40 min
- Your AI workbench: choosing tools, confidential data, and the Nigeria Data Protection Act 202345 min
- Module 1 quiz15 min
02Working with AI like a finance professionalHow to instruct an AI assistant with the precision of a good audit instruction, and how to make its work checkable. You will learn the parts of a strong finance prompt, structured outputs such as journals and JSON that can be validated before posting, verification routines that apply the four-eyes principle to AI, a governed prompt library for a whole team, and retrieval that grounds answers in your own documents.6 lessons · 3h 55m
- The anatomy of a finance promptFree preview35 min
- Structured outputs: tables, journals and JSON you can trust50 min
- Making AI check its own work: reasoning, verification and the four-eyes principle45 min
- Building a prompt library for a finance team40 min
03Data foundations for AI in financeAI is only as reliable as the data you give it. This module follows the data of Ardena Foods, a fictional Nigerian manufacturer, from the ledger, sub-ledgers and bank files through a chart of accounts designed for automation, cleaning and matching, Excel and a first Python script, to the governance and audit trail that let a professional sign the result.6 lessons · 4h
- Finance data: the ledger, sub-ledgers, ERP, bank feeds and market data40 min
- A chart of accounts built for automation40 min
- Cleaning and reconciling data with AI45 min
- Excel and AI, and your first Python for accountants60 min
- Data governance, lineage and the audit trail
04AI across the record-to-report cycleFollow the October close of Ardena Foods, a fictional Nigerian manufacturer, from end to end: AI-assisted transaction coding and journal drafting, bank and intercompany reconciliations, accruals and cut-off, the close calendar and variance commentary. The module ends with the controls that make AI-generated entries safe to post: maker-checker review, approval thresholds, logging and segregation of duties.6 lessons · 4h 5m
- Coding transactions and suggesting journals45 min
- Bank and intercompany reconciliations45 min
- Accruals, prepayments and cut-off45 min
- The month-end close: checklists, variance commentary and the close calendar45 min
- Controls over AI-generated entries
05IFRS financial statements with AIIn this module we build a complete IFRS reporting pack for Ardena Foods Plc, a fictional Nigerian food manufacturer, from one balanced trial balance: the statement of financial position, profit or loss and OCI (by function, by nature and under the new IFRS 18 categories), the statement of cash flows, changes in equity and the key notes. At every step you see the AI prompt that does the work and the professional checks that prove it is right, and the module ends with disclosure checklists, cross-statement consistency checks and digital tagging.7 lessons · 5h 15m
- The IFRS reporting package: IAS 1 today and IFRS 18 from 202740 min
- From trial balance to statement of financial position (worked build)Free preview55 min
- The statement of profit or loss and OCI, and the new IFRS 18 categories and subtotals55 min
- The statement of cash flows (IAS 7): the indirect method with AI
06AI for the hard IFRS judgementsRevenue contracts, leases, expected credit losses, impairment, fair value and group accounts are where IFRS asks for judgement and where errors cost the most. In this module AI works as the analyst's assistant, reading contracts, extracting data and building schedules, while you make and document the judgements, recompute every number and decide what is signed.6 lessons · 4h 40m
- IFRS 15 revenue: reading contracts with AI through the five steps50 min
- IFRS 16 leases: extracting lease data and building schedules50 min
- IFRS 9 expected credit losses: staging, PD, LGD and machine learning55 min
- Impairment (IAS 36) and fair value (IFRS 13): cash flow models with AI55 min
- Group accounts (IFRS 10): consolidation and eliminations
07Financial analysis and forecasting with AIAnalyse a company the way a finance director and a lender would: ratios with the story behind them, forecasts that are tested before they are trusted, and scenarios for the Naira, inflation and interest rates that hang together. Using the fictional Ardena Foods Plc, you build a three-statement model with AI help, check that it balances and links to cash, and turn the results into a board pack that leads with decisions and never lets AI invent a number or a cause.6 lessons · 4h 15m
- Ratio analysis and the story behind the numbers45 min
- Forecasting: from trend lines to machine learning50 min
- Scenarios and sensitivities: inflation, FX and interest rates in Nigeria45 min
- Building a three-statement model with AI55 min
08Investment analysis: the investment professional's lensWork as an analyst at Velra Capital, a fictional Abuja asset manager: research a company from primary sources with AI as your reader, value it with a DCF and multiples, analyse its bonds and covenants, and measure portfolio risk with VaR and stress tests. The module closes with alternative data and text analytics, tested honestly, and with the professional duties in the CFA Institute Code of Ethics and Standards of Professional Conduct that govern every use of AI in investment work.7 lessons · 5h 10m
- The research workflow with AI: annual reports, results calls and filings45 min
- Valuation with AI: DCF, multiples and the checks that matter60 min
- Credit and fixed income analysis50 min
- Portfolio construction, factors and risk50 min
09Risk, fraud, audit and assuranceHow AI and analytics change the control side of finance: finding fraud and anomalies in whole populations, monitoring transactions for money laundering, scoring credit fairly and explainably, and gathering audit evidence with data and AI. The module ends with model risk management, the discipline that keeps every model in this course validated, monitored and documented well enough for a professional to rely on it.6 lessons · 4h 20m
- Fraud detection: anomaly detection, Benford's law and journal entry testing50 min
- AML, KYC and transaction monitoring45 min
- Credit scoring, fairness and explainability50 min
- Audit and assurance with AI50 min
- Model risk management: validation, drift and documentation
10Treasury, tax and finance operationsAI in the engine room of finance: forecasting cash and liquidity, analysing FX exposure and hedges, preparing tax data and computations without letting a model supply the law, and automating invoices, payables and receivables. The module ends with AI agents, and the guardrails, approvals and audit logs that make them safe to use on real money.6 lessons · 4h 5m
- Cash forecasting and liquidity45 min
- FX exposure and hedging analysis45 min
- Tax work with AI: data, computations and the limits45 min
- Invoices, payables and receivables: document extraction and automation50 min
- AI agents in finance operations
11Governance, ethics, regulation and sustainability reportingHow to govern AI in a finance function so that a professional can sign the result: the main frameworks (NIST AI RMF, ISO/IEC 42001 and the EU AI Act), confidentiality, data protection and the accountancy ethics codes, and bias, explainability and accountability. The module also applies AI to sustainability reporting under IFRS S1 and S2, and ends with a complete model AI policy you can adapt for your own team.6 lessons · 4h 10m
- AI governance frameworks: NIST AI RMF, ISO/IEC 42001 and the EU AI Act45 min
- Confidentiality, data protection and professional ethics45 min
- Bias, explainability and accountability45 min
- Sustainability reporting with AI: IFRS S1 and S250 min
- Writing an AI policy for a finance function
12The AI-enabled finance function, and the capstoneHow to lead the change: build an honest business case for AI in finance, plan the pilot and the scale-up, bring people with you, and develop the skills the finance professional of 2030 will need. The module ends with the capstone, an AI-assisted IFRS reporting pack for Ardena Foods built from a trial balance, followed by a full model answer and a self-assessment rubric.6 lessons · 4h 25m
- The business case: costs, benefits and ROI45 min
- The roadmap: pilot, scale and change management45 min
- The finance professional of 203040 min
- Capstone brief: an AI-assisted IFRS reporting pack for Ardena Foods60 min