Key information
Programme overview
Artificial intelligence (AI) is transforming finance as a function across industries, creating both opportunities and risks for finance leaders. From trading floors to compliance teams, finance professionals are under increasing pressure to evaluate and implement AI responsibly, while driving measurable business value.
The Finance programme from Imperial Executive Education is designed for senior finance professionals and transformation leaders who must understand and evaluate AI and strategically integrate it into their organisations. Delivered online over 6 weeks, the programme takes leaders like you from foundational concepts such as machine learning, data readiness and generative AI through to applications in trading, portfolio optimisation, lending, financial planning and analysis, fraud detection, compliance and enterprise-level AI strategy.
You will join a select cohort of senior finance professionals and learn through recorded videos, weekly office hours, playbook assignments and case studies. The learning journey is designed to provide you with value beyond the classroom and enable you to deliver strategy memos, compliance briefings, financial planning and analysis (FP&A) action plans and an AI adoption strategy. After completing the programme, you will sign off with actionable strategies, measurable ROI frameworks, a lifelong global network of peers, Associate Alumni status and the confidence to translate AI-driven innovation into boardroom-ready strategies.
Who should attend
The AI in Finance programme is designed for decision-makers and finance leaders who need to understand, evaluate and strategically lead AI adoption within their organisations. This programme is suitable for:
- Executive finance leaders, including chief financial officers, vice presidents of finance and group finance directors, responsible for shaping budgets, forecasts and long-term financial strategy
- Compliance and governance leaders, such as heads of compliance, anti-money laundering officers, audit executives and regulatory affairs directors responsible for ensuring AI adoptionmeets transparency and regulatory standards
- Risk and lending leaders seeking to deploy AI responsibly to improve accuracy, reduce bias and strengthen compliance
- Investment and trading professionals who want to apply AI to sentiment analysis, portfolio optimisation and algorithmic execution
- Transformation and innovation leaders responsible for driving cross-functional alignment and AIenabled growth
- Financial planning and analysis leaders, such as vice presidents or directors of FP&A, treasury heads and senior FP&A managers, aiming to modernise forecasting, budgeting and real-time business insights
Learning Objectives
By the end of the programme, you will be able to:
- Differentiate between AI, machine learning, deep learning and generative AI
- Analyse data types and model selection for financial applications Leverage AI-driven tools for trading, portfolio optimisation, FP&A, budgeting, lending, fraud monitoring and compliance
- Determine where AI generates measurable value in finance while weighing ethical, regulatory and operational implications
- Prepare and present strategy memos, compliance briefings, dashboards, and an AI adoption plan that addresses multiple stakeholder needs
- Develop cross-functional collaboration plans for AI implementation
Learning Journey
Module 1: Foundations of AI for Finance Leaders
Module 2: AI in Trading and Investment Management
Module 3: AI in Lending and Credit Risk
Module 4: AI in FP&A and Budgeting
Module 5: AI for Fraud, Risk Detection and Compliance
Module 6: Strategic implementation and ROI of AI in Finance
Programme faculty
Marco Di Maggio
Professor of Finance, Department of Finance, Imperial Business School
Before joining Imperial College Business School as Professor of Finance, Marco Di Maggio was the Ogunlesi Family Professor of Business Administration at Harvard Business School and Director of the Fintech, Crypto, and Web3 Lab, a cross-disciplinary initiative fostering collaboration between academia and industry.
His research explores financial intermediation, with a particular focus on the impact of emerging technologies, including blockchain and AI, on financial markets, organisations and individuals.
Marco’s work has appeared in leading academic journals, such as the American Economic Review, the Journal of Finance and Journal of Financial Economics. It has also been widely cited by global media outlets, including The Wall Street Journal, the New York Times, The Economist, Bloomberg, Institutional Investor, Slate and Forbes.
In addition to his academic work, Marco collaborates with a range of organisations in both traditional finance and the crypto/decentralized finance sectors.