Essential AI Concepts for Finance Professionals

Essential AI Concepts for Finance Professionals: Foundations, Applications, and Emerging Trends is a focused, single-session micro course that demystifies AI for busy finance teams. In one sitting, you’ll build a clear mental model of how modern AI works, where it adds value across finance, and how to evaluate opportunities and risks without needing to code. Through plain-English explanations, bite-size caselets (forecasting, anomaly detection, fraud, sentiment/compliance), and quick interactive prompts, you’ll leave with a practical checklist for spotting high-ROI use cases and speaking confidently with data and tech partners.

You’ll learn to:

• Grasp the essentials of machine learning, deep learning, and NLP—what they are and when to use them.
• Distinguish supervised vs. unsupervised learning in real financial tasks (e.g., risk scoring vs. clustering customers).
• Apply AI to both structured data (ledgers, transactions) and unstructured data (contracts, emails, filings).
• Use NLP for compliance monitoring, policy mapping, and automated reporting summaries.
• Understand foundation models and domain-specific LLMs, including strengths, limits, and governance considerations.
• Evaluate model performance, bias, explainability, and controls required in regulated environments.

Session outline:

1. Course Overview – goals, outcomes, and what “good” looks like in finance AI.
2. Key AI Concepts – data, features, models, training, inference, evaluation.
3. Foundations of ML, DL, and NLP – intuitive analogies and real finance examples.
4. Applying AI to Structured & Unstructured Data – forecasting, anomaly detection, document intelligence.
5. Supervised vs. Unsupervised – choosing the right approach and measuring success.
6. NLP in Compliance & Reporting – screening, disclosure extraction, policy adherence.
7. Foundation Models & Finance LLMs – customization options, risks, and control frameworks.
8. Conclusion – value checklist, next-step roadmap, and guardrails for responsible adoption.

Who it’s for: Finance leaders, analysts, auditors, and ops professionals.
Prerequisites: Finance literacy; curiosity about data. No coding required.