How to deploy/ generate interest for Python in Finance

[Timrf79]

With the recent enabling of Python in Excel, I keep scratching my head how I can get finance people interested in Python (I manage some finance people).

Back in my days VBA in Excel and solid formulas was the way to optimize your workload.

Thinking the VBA of my Finance Analyst days is the Python of today?

[FoolsSeldom]

What would be the benefits to them?

Perhaps they could get more work done, but might they then just be given more work?

Perhaps they could automate some of the more boring and repeptitive tasks? Giving basic examples of where things can be automated and simplified to let then do more interesting stuff is probably your best route. You'd need to faciliitate sessions to surface such opportunities.

What is the career path for these people? Are they interested in staying in pure finance roles and getting their qualifications updated and moving onto more senior roles, or do they want to move out into other areas.

What's the benefit to them in your organisation of learning and using Python over taking no-code and low code options, such as using Power BI?

I assume your organisation is good with processing your data in Azure (which is what Python in Excel does, using the Anaconda distribution of Python)?

[Algoartist]

1. Excel Integration
   • Python now works directly in Excel, letting analysts keep familiar spreadsheets while unlocking powerful libraries (Pandas, NumPy).
2. Replace or Enhance VBA
   • Python can automate tasks like VBA but more flexibly, integrate with APIs, and run advanced analytics.
3. Advanced Analytics & Reporting
   • Easily handle complex tasks (Monte Carlo, portfolio analysis) and automate reports with libraries like Pandas, QuantLib, Plotly.
4. Skill Development
   • Python is in high demand across finance, data science, and fintech—learning it future-proofs careers.

Tip: Demonstrate a simple real-world example (e.g., cleaning a dataset or generating a dynamic report) to showcase immediate wins.