Computer simulations allow us to play out various scenarios repeatedly and assess the outcomes. It is also true for computer simulations that are used in finance. Through scenario analysis, we can gain some comfort and assurance that the decision taken is the right one given the circumstances. However, there are a few considerations with the use of artificial intelligence (AI). 

FP&A Digitalisation was discussed at several FP&A Boards in the past but the recent mindset shift has changed the perspective. It went from anxiety before the implementation to peace of mind in fully controlling the processes and confidence in the quality of provided FP&A insights.

True Business Partnering starts when the FP&A community fully owns the numbers, completely agrees with them, and publicly endorses them.

Without a doubt, the effects of AI on the global economy are jaw-dropping. But how does that affect the FP&A sector? Do we need to worry about the rise of artificial intelligence?  

Is your most fancied FP&A RPA initiative not delivering the anticipated benefits? You are not alone. So, what are the most common pitfalls? And more importantly, how can you sidestep them and increase your odds of a successful RPA implementation?

Machine Learning provides tremendous insight regarding market trends & business drivers. These factors include market propensity, consumer demand, economic factors, weather, & transportation costs. Many companies take these variables into consideration but provide limited or time-consuming analysis.  This process limits corporate agility.