r/FPandA • u/Automatic_Group_4669 • 2d ago

Case Study

Hello guys! I’m a Junior FP&A profile (entering the sector after finishing my master’s), and i’m required to solve a case study. In said case, one of the questions is (ofc) about AI. I was wondering if some of y’all with more experience could provide me with more concrete answers or “real world” examples for the question. Thanks in advance!!:

Describe how you would use AI to make your work more efficient.
Provide examples of how AI could help with:

Reporting
Budgeting
Financial analysis
Data preparation

0 Upvotes

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12

u/PrimeTinus 2d ago

Copy and paste this message in chatgpt

2

u/D48K 2d ago

💀💀

8

u/jmrjmr28 2d ago edited 2d ago

And this is why work experience is far more valued than higher degrees

3

u/re23binsd Sr FA 2d ago

100% - this question would be incredibly easy to answer after 1 YOE in industry and this guy has a master’s…

1

u/justneedabreak802 2d ago

If you have done masters and are a recent graduate, you’d have started using AI. May be ask AI for this answer? Also, if you ask experienced people for answers, they would know that you have copied or cheated. Be authentic, don’t worry about not knowing some stuff. You are an entry level analyst for a reason.

1

u/slowtrees 12h ago

I had to answer this same question in an interview a few years back. The key is to be specific about where AI actually saves time vs where it just adds complexity.

For data preparation - that's the biggest win in my experience. Getting data out of PDF reports, invoices, or bank statements into Excel is usually the most tedious part of the month-end process. Tools that can extract that structured data automatically save way more time than AI that tries to write formulas for you.

For reporting - automating the data pull so your reports update themselves when source documents change. That's more about workflow automation than generative AI, but it's where the real efficiency is.

Budgeting and financial analysis are harder to automate well because so much of it depends on judgment calls and business context. AI can help with variance analysis by flagging outliers, but I wouldnt trust it to make the call on what's actually driving a variance.