Free webinar: Ideas on the use of Machine Learning (ML) to address key challenges of Financial modeling in the Automotive Sector

What you will learn
  • How to do accurate  forecasting using ML techniques
  • How to do sales forecasting based on historical data and not on guess work
  • How to handle seasonality of product sales volume over a period
  • How to leverage AI technology to do accurate sales planning and forecasting
  • How to understand long term trends generated by external factors: e.g. Pandemic/War crisis
About Speaker

Tom Byrne, MSc FCMA  is a Qualified Accountant
Experienced  IT  professional and has over 40+ years of Industry experience and has performed  in different roles such as Finance Manager, Information Systems Manager, Solutions Architect and consultant.  He has qualifications in mathematics, operational research, management accountancy and quantitative finance. This webinar is based on his real life experience and we hope you will definitely enjoy the talk.

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    Sector:
    Automotive

    Business volume:
    Seasonal based on time of the year.

    Product: highly seasonal.

    Case Study

    In the early 1990s  this manufacturing company was  facing a financial challenge. The UK economy was in recession and the marketplace was changing.  There were challenges to forecasting and the  management of working capital.

    The purpose of this webinar is to give an overview of  how these challenges were handled in those times based on the  available tools in the 1990s.

    Now in the year 2022 technology  has improved significantly, especially with the advent of the Cloud. Computing power has significantly  improved and is now highly scalable with distributed architecture.  

    Also with the advent of  Artificial Intelligence (AI) & Machine Learning Techniques and powerful languages like Python and open source technologies it is now possible to forecast more accurately.

    This webinar contrasts solutions developed during the 1990s with the much simpler,more accurate,scalable and reliable solutions using Machine Learning techniques that are available today.