Artificial Intelligence / Machine Learning FP&A Committee
Artificial Intelligence (AI) and Machine Learning (ML) are already impacting our everyday lives but it is also becoming a valuable tool for FP&A. The technology is evolving at an incredibly rapid paste and it is challenging to keep track of all trends and innovations.
According to Forrester’s 2018 predictions for AI, 70% of enterprise expect to implement AI over the next 12 months. And by 2020, according to Gartner, AI technologies will be virtually pervasive in almost every new software product and service.
The Artificial Intelligence (AI) / Machine Learning (ML) FP&A Committee was established on 29th of March 2018.
The mission of the Committee is to guide the development, application and promotion of better practices for using AI/ML and other related data science techniques within in Finance (FP&A). This includes identifying, driving and supporting new trends by developing new content and sharing it with the global finance community. The ultimate strategic purpose being enabling quick and dynamic decision making that is reliable.
The core focus of this Committee is, therefore, on the practical application of AI/ML e.g. leadership, people, roadblocks and change management focusing ultimately on benefits realization.
- "Introductory Meeting: Defining the Mission" on 29 March 2018
- "AI / ML for FP&A: Case studies" on 19 June 2018
- "AI / ML for FP&A: Vision and Case studies" on 14 November 2018
- "AI / ML for FP&A: Case studies" on 20 March 2019
- "AI / ML for FP&A: Algorithmic Model" on 5 June 2019
- "AI / ML for FP&A: Deutsche Bahn and Egencia Case Studies" on 9 October 2019
We are planning four insightful sessions in 2020.
The Committee's members are senior finance practitioners who represent large organisations that already started experimenting with AI / ML in finance or implementing it.
The Committee is a truly international think tank. The members come from different countries, namely China, Denmark, Germany, Japan, the Netherlands, Sweden, Switzerland, Ukraine, the United Arab Emirates, the United Kingdom, the USA.
At the moment Committee members represent the following organisations:
- ABN AMRO Bank N.V.
- AC Nielsen
- Bank of America
- Deutsche Bahn
- Government of Ontario
- Konika Minolta
- Maersk Group
- Siemens Healthcare
- Swiss Railway Freight Logistics (SBB Cargo AG)
- Swiss Re
Previous Meetings: Overviews and Case Studies
- Deploying Artificial Intelligence & Machine Learning in FP&A
- Global AI/ML Think Tank for FP&A
- AI/ML FP&A Committee: Third Meeting
Case Studies (articles):
- SBB Cargo: Using AI to Build an Intelligent Business Simulation Engine
- Microsoft Case Study: Data to Action — Drive Business with Technologies
- PayU Case Study: Experiences from implementing machine learning (ML) for forecasting
- Modern Finance. Leveraging AI/Machine Learning in Decision Making
- Baby Steps Towards Implementing ML for Forecasting
- FP&A Teams Driving Performance Change with AI
- Dynamic and Interactive Sales Planning Based on the Algorithmic Model
- How AI Could Replace Old-School Management Accounting
- The Future of FP&A. Incorporating AI Into the Financial Forecasting Process
- Machine Learning for Better Results in FP&A
- Egencia Case Study: Artificial Intelligence for FP&A