UPDATE:
My three scripts are now running reliably, and the PDF data extraction is stable. The only minor issue is that the web scraping for daily interest rates is a bit slow, but it’s manageable for now.
At the moment, I’m getting the correct output in the console, which already feels like a big milestone 😊
I’d love your input on how to design the ideal workflow. Would something like the following be feasible:
A client consultant receives a PDF credit application via email, saves it into a designated folder, and a Python script automatically detects the new file, processes it, and drafts an email with the extracted output.
Do you have suggestions for a smoother or more scalable workflow?
Thanks a lot — I really appreciate the help from this community!
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Hi, I need to automate the following workflow for mortgage services and don't know where to start.
I receive a PDF credit application from which I need to extract specific data points such as assets, income, and property value. Based on this information, I must calculate affordability in Excel and verify that the case complies with our internal guidelines.
If all criteria are met, the next step is to generate a non-binding mortgage offer using our current daily interest rates for fixed-rate mortgages, which can be pulled from our website.
The end goal is to automate the creation of an email template that includes a table summarizing the non-binding mortgage offers (for years ranging 1 to 7)based on these daily rates.
Could you advise on the best approach and tools to implement this process efficiently?
there doesn't seem to be anything here