Sure. I use ledger so everything is plain text. The idea is I classify each transaction in my bank statement to work out what the "other side" of the transaction is. It could be an expense account like "Expenses:Groceries" or another asset like "Assets:Vanguard" or something.

I train an SVM on my previous year's ledger, then it interactively goes through the CSV bank statement showing the prediction for each transaction, and allows me to quickly change it if I don't agree, using fuzzy completion. I used scikit-learn for the machine learning. It's not "production grade" or anything, but it really doesn't matter.

All the code is here in case it's useful: https://github.com/georgek/accounts But it's very much made for me. It was all about making something with low enough friction that I'd actually use it. It won't necessarily work for anyone else. I'd imagine an LLM could pop out something very similar these days, but you wouldn't learn anything in the process, of course.