| FazBrowse GitHub Viewer | Trending | | Home |
| Tools: [Download Repo ZIP] [Original HTTPS Page] |
| Name | Name | Last commit date | ||
|---|---|---|---|---|
Example Python code to transcribe tables from regulatory filings into a digital form. To run these examples you will need an Anaconda environment, a Mistral API key. In this example we transcribed the balance sheet table from Solvency and Financial Conditions reports that companies need to file every year.
For a subset we took the main 18 life insurance companies operating on the Italian market.
The process of extraction is performed in 5 phases.
The notebook performs the following steps (with slight modifications depending on the table format):
The notebook applies fixes to the DataFrame to make the numbers closer to the reported numbers. It joins all the tables into a single dataset and saves it into the Dirty_Combined folder.
The notebook applies a series of tests that check for the internal consistency between the numbers. Flags potential errors. After the individual fixes are applied, it saves the table into the Cleaner_Combined folder.
A version of this process is used by us to extract data for our actuarial models. One of the benefits of releasing our code is the feedback and improvement ideas. If you have any, you can contact us at gregor@osmodelling.com.
MIT license
| Back | FazBrowse Home | New Git URL |