Artificial Intelligence in Finance

digital training

Artificial Intelligence (AI) and Machine Learning (ML) are transforming the financial industry by enabling new approaches to decision-making, risk management, and innovation. This course introduces participants to the fundamentals of AI methods and their applications in finance.

The program begins with the foundations of AI and ML, distinguishing them from traditional statistical approaches and highlighting their relevance for financial services. It then explores financial data sources, including market data and accounting fundamentals, and introduces essential preprocessing techniques such as cleaning, transformation, and feature engineering.

Participants engage with a wide range of modeling approaches, from linear and penalized regression models (Ridge, Lasso, Elastic Net) to classification algorithms such as k-Nearest Neighbors, Support Vector Machines, decision trees, and ensemble methods like Random Forests. Further topics include regression trees, boosting techniques, and neural networks, along with regularization methods such as dropout, early stopping, and batch normalization.

The course concludes with regulatory and ethical challenges. Issues of transparency, bias, and fairness are discussed alongside the implications of frameworks such as the EU AI Act. By the end, participants are equipped with the knowledge and tools to apply AI responsibly within financial institutions.

The training includes:

• 15 online on-demand sessions of 90 minutes each (access via Moodle)
• four online live consultation hours (via Zoom)
• Duration of access: 12 months, starting January 5, 2026, at 9:00 a.m.

Please also create an account on the Moodle continuing education platform: https://wbmoodle.uni-leipzig.de/login/index.php