Back / AI and Machine Learning Cash Flow Forecasting: 12/13 March 3-5pm UK time
AI and Machine Learning Cash Flow Forecasting: 12/13 March 3-5pm UK time
Overview
For Treasurers looking to see a steep change in their forecasting, Your Treasury's AI and Machine Learning in Cash Flow Forecasting workshop provides the road map and practical skills to achieve your goals.
During this course, you will learn:
- When to use Automation, simple AI and Machine Learning
- To build a basic machine-learning model
- Time-saving practical use cases for AI
During this course, you will gain access to the Your Treasury platform, including the community, course materials, coding platform, and integrated Claude large language model.
Agenda
Day 1 (2 hours)
13 February - 2 hours
Setting the Scene
- Understanding cash flow statements and forecasting challenges: data quality, inefficiencies, and strategy gaps.
Unlocking AI’s Potential
- Moving from automation to AI and machine learning.
- How AI improves data quality, detects anomalies, and boosts efficiency.
Practical Examples
- Automating data collection and tagging.
- Using AI to identify missing data and create visual comparisons of forecasts vs actuals.
Implementation Steps
- Connecting, validating, and transforming data for AI use.
Reducing manual effort with AI tools.
Q&A
- Addressing your challenges and exploring AI’s potential in treasury.
Day 2 (2 hours)
14 February - 2 hours
Recap of Day 1
- Key insights from automation, AI, and machine learning applications in cash forecasting.
Introduction to Machine Learning
- How machines learn through supervised, unsupervised, and reinforcement learning.
- Exploring features and their impact on predictions.
Practical Applications of Forecasting
- Tagging transactions using machine learning.
- Building models for operating cash flows and leveraging time series tools like ARIMA, SARIMA, and Prophet.
Advanced Forecasting Techniques
- Combining time series models with machine learning for enhanced accuracy.
- Engineering features for high-quality predictions.
Key Takeaways
- Tagging as the foundation for machine learning models.
- Creating robust forecasts by integrating AI tools.
Instructor
Jessica Campbell
Jessica is an experienced teacher and data scientist who specialises in Python analysis, visualisation and automation. As a former quantitative research scientist, she has been recognised with several Awards for her presentation work, her ability to communicate technical concepts to non-technical audiences, and her contributions to diversity, equity, and inclusion. She holds a PhD in Astronomy & Astrophysics from the University of Toronto with numerous publications in esteemed research journals.
James Kelly
James is an accomplished FTSE 100 treasurer with a proven track record at leading UK companies like Pearson, Sky, and Kingfisher. Recognised for his innovative use of technology, he is the current holder of Adam Smith, Alexander Hamilton and TMI awards. A sought-after speaker for the ACT and EuroFinance, James is dedicated to sharing his expertise and empowering others in the industry.
Workshop Details
Venue
Online
Instructor
Jessica Campbell
,
James Kelly
