A survey by Airbase suggests that finance professionals are wasting 25% of their time on manual tasks.
Examples of such tasks include everything from ‘document chasing to error fixing, to handling credit card statements [and] bank reconciliations’.
Does this sound familiar?
One task that analysts often overlook when reviewing manual time-wasting tasks is manual data extraction. Also known as manual data entry, extracting data via copying and pasting is tedious and an excessive waste of company resources (namely, time, money and productivity).
Financial statements – a staple of most financial planning and analysis (FP&A) tasks – often require manual copying and pasting from PDF into Excel (a type of manual data entry or extraction). Luckily, various technologies exist to automate the financial data copying-and-pasting process.
Here are a few advantages to having standardised data in an Excel format:
.png)
Pictured: The result when we tried to copy and paste from the World Bank Group’s 2024 Annual Report. Left: highlighted text. Right: the copy-and-pasted data.
Businesses should consider the following three reasons why manual financial data handling is so mid-2020s:
Some companies use £50/hour analysts to enter data from reports manually. Likewise, we’ve witnessed lawyers complete copying and pasting tasks in litigation circles. Using experienced employees to complete data entry tasks designed for entry-level staff only wastes company resources.
Our client, DF Capital, found that it took 20 minutes to extract data from one invoice. Financial statements are generally more information-dense and longer, and some of our clients have suggested that it’s taken up to three hours to extract from one financial statement.
Firms handling large volumes of financial statements can’t scale unless they have a way of accessing actionable information quickly.
An automated financial statement solution can replace copying and pasting these documents manually. Of course, such a specialist tool is essential, as traditional methods are cumbersome and often inaccurate.
Financial Statements AI is our specialised tool for reading financial statement PDFs and converting them into Excel spreadsheets. It essentially transplants – or copies and pastes – your financial data into an Excel file, ready for download instantly. Note that Financial Statements AI adheres to best security practices to ensure that your data is fully protected.
Click the arrow icon to upload the financial statement, or drag and drop the file.
Financial Statements AI will automatically detect the balance sheet and income statement from the financial statement (soon, it will also be able to detect the cash flow statement). The AI algorithms will then ‘copy and paste’ the data from the PDF into a grid on the right.
By clicking through the tabs (at the top) marked ‘income statement’, ‘balance sheet’, ‘extracted data’ and ‘standardised data’, you can access both the raw financial data and the standardised metrics.
When you click the ‘Download’ button, you will receive an Excel file straight to your device. The file will contain the extracted and standardised data in separate tabs.
End to end, Financial Statements AI is a quick way to copy and paste data from financial statements in bulk.
Ready to get started with Financial Statements AI? Book a demo for live access so you can upload and download for free!
A Large Language Model (LLM) is the technical term for an AI virtual assistant that can read and generate natural language.
Since LLMs like ChatGPT and more offer customisable download options, converting financial statement PDFs into Excel spreadsheets is easy. Let’s break it down step-by-step.
ChatGPT is the most in-demand LLM, but Gemini and Claude are also popular options for these types of generalist data analysis tasks.
You should be able to quickly sign in to these LLMs using a preexisting account with Google, Microsoft, Apple or email credentials.
Click the ‘Document Upload’ box or drag and drop to upload your PDFs. The AI should accept multiple PDFs if you press the shift key and select multiple files from your computer or Google Drive.
For the free plan, here are the maximum limits of each LLM per 24 hours:
Type an appropriate prompt into the box – this is the important part.
The prompt should be clear and specific. Rather than inputting a prompt like ‘copy this financial data’, for example, you might try:
‘Transcribe all the financial data from this financial statement into an organised Excel spreadsheet’.
You could then refine the prompt depending on your preferences. For example:
Is something not working (e.g. are you receiving an error message, etc.)? Check out our guide to debugging ChatGPT when there’s a document upload error.
The LLM will produce the response in a few seconds (potentially longer for more challenging prompts). You should see a downloadable Excel spreadsheet. Click to download it and then check the outputted data carefully using the original PDF as a reference.
If something’s wrong (i.e. missing data, incorrect formatting, etc.), ask the model to regenerate the file, specifically referencing the mistake in the original file. If you want to experiment with these models thoroughly, we recommend using the Pro version of each one, priced at approximately $20.
The main disadvantage of using ChatGPT (and others) is that it can’t guarantee the security of your data. OpenAI notes that the files uploaded with any personal plan may be used to improve model performance. The implications of this are somewhat difficult to untangle, but could include:
For many financial service providers, the risk of uploading a financial statement to a publicly accessible AI model like ChatGPT is disproportionate to the net benefits (i.e. the time saved). This is particularly the case when these models still generate roughly a 1% hallucination (i.e. false information) rate.
Outside of AI, various technologies and tools can assist in copying and pasting data from financial statement PDFs into Excel. Let’s examine two.
Excel has an inbuilt PDF converter. Simply navigate to the Data tab, then choose Get Data > From File > From PDF to import your document. Note: Excel might struggle with PDFs containing complex tabular structures (such as those enclosed within a typical financial statement) or blurry images. For long financial documents – such as annual reports – you might find ‘Get[ting] Data’ a slow and unwieldy process.
There are several OCR-powered data extraction tools on the market. However, few offer functionalities for extracting from financial statement documents specifically. Training OCR engines to detect the visual nuances of most financial statements is extremely challenging.
OCR plus AI, however? As in the technology stacks found in LLMs and Financial Statements AI? Now, that’s a winning combination.
In a nutshell – yes.
Specialised data extraction tools can copy and paste data from bank statements into an Excel format. You can also use an LLM to extract data through the same prompting method. However, similar to financial statements, the sensitive personal information in bank statements makes it risky to upload them.
Most likely, converting financial statement PDFs into Excel is an admin task that will persist in office environments for years to come. PDFs are not going anywhere, nor is Excel. However, copying and pasting data manually is outdated. Instead, businesses must find a secure and speedy solution for copying their financial data into an editable Excel format.
Financial Statements AI is a pioneer in financial statement processing. Try it for free today – book a demo with our financial data project team or email hello@evolution.ai.
