How is Microsoft using AI to reach up to 99% accuracy in some forecasts? In this episode of FP&A Today, Daniel Sousa-Lennox, a data scientist at Microsoft with deep experience of financial analysis, reveals all.

The Microsoft’s finance team – about 5000 people – saw its first foray into machine learning in forecasting. The team developed FINN (or Microsoft Finance Time Series Forecasting Framework) says Sousa-Lennox who sits within the finance organization, providing software engineering and data science expertise. Using machine learning and creating AI finance tools (such as FINN which has been open-sourced) Sousa-Lennox says the Microsoft finance team has replaced burdensome forecasting and Excel heavy lifting.  "The tool has helped, for instance, this one team in terms of accuracy to get the revenue that they were trying to forecast for an Azure product (the cloud computing platform run by Microsoft) to 99% accuracy".  But Sousa-Lennox adds that it is important to remember that AI is not "magic" and "wont lead to 99% in every single forecast" and the quality of data is paramount.

Nevertheless the results are transforming financial forecasting at the $2trillion company.

FINN alone provides access to 25+ models supporting Microsoft’s daily, weekly, monthly, quarterly, and yearly forecasts, transforming the approach of FP&A.

Sousa-Lennox says: “It takes on average for a forecast used run using our tool, it takes about an hour to an hour and a half, which is significantly less than a week [previously]. It is also an hour and a half where you don’t have to be actively doing anything.”

In this episode Daniel Sousa-Lennox shares:

• Similarities and differences between FP&A in US and Panama (and banking vs Microsoft)

Links

Follow Daniel Sousa-Lennox: https://www.linkedin.com/in/dsousalennox/

FINN (Open-sourced by Microsoft): https://microsoft.github.io/finnts/