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.

 

Previous Meetings

2018

2019

2020

We are planning four insightful sessions in 2020.

Committee Members

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:

  • A.P. Moller - Maersk
  • ABN AMRO Bank N.V.
  • AC Nielsen
  • ADFG
  • Altice USA
  • Bank of America
  • BECU
  • Bekaert
  • Comcast
  • Deutsche Bahn
  • Egencia, an Expedia company
  • Emirates Group
  • Government of Ontario
  • Honeywell
  • HSBC
  • Konika Minolta
  • Microsoft
  • PayU
  • PepsiCo
  • Providence Health & Services
  • Reckitt Benckiser
  • ResQ Limited
  • Siemens AG
  • Siemens Healthcare
  • Stewart
  • Swiss Railway Freight Logistics (SBB Cargo AG)

 

Previous Meetings: Overviews and Case Studies

General Information:

Case Studies (articles):

    Videos

    Agenda

    1. The Committee: its mission and rules

    2. Live Survey-on AI

    3. AI/ML: Some concepts and definitions

    • Business Case –Research Study on AI/ML in FP&A - Irina Steenbeek
    • AI/ML in Finance: Vision - Igor Panivko(5 min)
    • Stefan Spiegel - a quick overview of the AI project in SBB Cargo
    • Matthijs Schot - a quick overview of ML Driver-based planning project in the Maersk Group

    4. Conclusions

    Agenda

    1. Case studies

    • How Artificial Intelligence could replace old-school Management Accounting. Stefan Spiegel, CFO at Swiss Railway Freight Logistics (SBB Cargo AG)
    • Artificial Intelligence – Lessons from other Industries and potential applications to Financial Planning. Saurabh Jain, VP Business Performance Controlling at Siemens Healthcare

    2. Open discussion on AI / ML questions

    3. Conclusions and next steps

    Agenda

    1. Presentations

    • The Future of FP&A: Incorporating AI into the Financial Forecasting process. Xena Ugrinsky, Principal and Founder at GenreX (New York, USA)
    • Modern Finance. Leveraging AI/Machine Learning in Decision Making. Takeshi Murakami, Group Controller at Microsoft (Tokyo, Japan)

    2. Open discussion on AI / ML questions

    3. Conclusions and next steps

    Agenda

    1. Presentations

    • Baby steps towards implementing ML for forecasting. Asif Khan, Global FP&A Lead at PayU (Amsterdam, Netherlands)
    • FP&A teams driving performance change with AI. Xavier Fernandes, Analytics Director at Metapraxis (London, United Kingdom)

    2. Open discussion on AI / ML questions

    3. Conclusions and next steps

    Agenda

    1. Presentations

    • "Dynamic and Interactive Sales Planning Based on the Algorithmic Model" by Igor Panivko, CFO Konika Minolta (Ukraine)
    • "Machine Learning for better results in FP&A" by Kevin McConnell, Intelligent Technologies Solution Strategy at SAP (USA)

    2. Open discussion on AI / ML questions

    3. Conclusions and next steps

    Agenda

    1. Presentations

    • "Challenges with implementing AI prototypes" by Tanja Schlesinger, VP Business Intelligence OneSource at DB Regio AG (Germany)
    • Egencia case study on AI/ML by Saul Mateos, Sr. FP&A Director at Expedia (USA)

    2. Open discussion on AI / ML questions

    3. Conclusions and next steps

     

    Agenda

    1. Introduction

    2. General Discussion: suggestions about future meetings and reflection on the previous ones

    3. Conclusion

     

    Agenda

    1. Introduction

    2. Case Study: “How to use AI to create a forward looking planning framework?” by Frederic Peeters, VP Finance, Steel Wire Solutions at Bekaert (Brussels, Belgium)

    3. Q&A Session

    4. Conclusions

     

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