Table Data Extraction from Financial Statement using AI 

In the Financial Document, Tables are the most important label of the document. Most of the data and reports of the document are structured in Table Formats like Asset Columns, Liabilities Columns, Revenue, Date, and many more. 

Extracting this type of very Important Finacial Data from a Table is a very Challenging Task. To automate this challenging Manual Task, you should use Docextractor Table Data Extraction Tool. This Software creates a complete table view from a single input of each data of the table and their AI bot analyzes the data of the uploaded image and structures the data in tables format into Required Database.

What are financial statements?

Financial Documents or Statements is a very important and sensitive documents for every Business and Company. It shows you How powerful the company is Fundamental. If you are Stock Market Trader, you know how important to analyze the Financial Report of the company before picking any stocks, Is it Profit Making Company or Loses Company, every detail is shown here.

In Short, to say, Financial statements are reports that summarize a company’s financial activity and position at a specific point in time. These statements provide information about a company’s financial performance and help stakeholders, such as investors, and creditors, to assess the company’s financial health. These statements are typically prepared at the end of an accounting period, such as a quarter, or a year.

In Financial Documents, there are 4 main types of financial statements:

  1. Balance Sheet: The balance Sheet shows the company’s financial position at a given point in time by listing the company’s assets, liabilities, and equity. As an Owner or director of the company, Keeping Tracking of assets and Liabilities is very important.
  2. Income Statement: The income statement shows the company’s income, expenses, and profit or loss over a specific period of time, usually a year or a quarter. From this report, it was analyzed, is the company profitable or Losses Company.
  3. Cash Flows Reports: These show the company’s cash inflows and cash outflows over a period of time and provide information about how the company is generating and using cash. It means, though, the company is a profitable company, but, it has real cash in its hand or they are only paying debt from its Profit.
  4. Statement of Stockholders’ Equity: This statement shows the changes in the company’s equity over a period of time, including the issuance and repurchase of stock and the distribution of dividends to their shareholders.

What are the main challenges to Extract Data from Financial documents?

Yeah, you have lots of Financial Documents, in which you want to extract each and every Label with correct information. But, It takes a lot of time to carefully collect the exact data of the exact label from the table of the document, because, most of the data is organized in Table Format. On the other hand, you should keep an eye on the digit of the value, one mistake or incorrect digit can ruin the report.

  • While Extracting Data from financial documents, here are some challenges you will face, that you need to overcome to get the correct value for each and every field.
  • Data is often presented in a structured format, such as a table or chart, but sometimes it can also be presented in unstructured text. which makes it difficult to extract data consistently and accurately.
  • Documents can be long and complex with multiple sections and subsections. Identifying and extracting specific data points can be challenging.
  • Financial documents may contain errors, and inconsistencies or sometime may contain Nil Field, which can make it difficult to extract accurate information.
  • Financial documents can be in different formats, such as PDF, Excel, or Word, which can make extracting data using a single tool or method challenging.

To overcome these challenges, you should use the Techniques of Data Scraping, and NLP(Natural Language Processing) to extract data. Imaginorlabs Presents Docextractor has its own ML, and AI Algorithm, Data Scraping, and NLP techniques which help to overcome these challenges. 

Why do You Software Docextractor IDP Software for table data extraction from the financial statements?

IDP software such as Docextractor is particularly useful for extracting tabular data from financial statements because it is capable of accurately and consistently extracting data from structured formats such as tables from the Financial Document. With the help of artificial intelligence and machine learning algorithms, it analyzes and captures the data of the tables and charts. 

These are some advantages of using IDP software like Docextractor to extract tabular data from financial statements;

  • Accuracy & Speed: This software is able to can extract data from tables much faster than a human, saving time with a high degree of accuracy, reducing the risk of errors
  • Ease of Use: The UI of the software is very simple and easy to use, with a simple interface and straightforward workflow. Anyone can easily understand the Step by step process of Extraction.
  • Versatility: Docextractor IDP software is able to support a variety of document types and formats, including PDF, Excel, and Word to extract data from tables from the Financial Statements.
  • Scalability: If any company has a high volume of data, this software  IDP software can easily handle this making it suitable for use in large organizations with multiple departments and locations.

How to Extract Table Data from a financial statement using Docextractor?

Step #1: Registration:

Login to Docextractor by entering your NameEmail, and Password.

Step #2: Create Project:

Now, you can see the All of your Existing Projects and the option of Creating New Projects.

Step #3: Create Project Name:

Then Set your Project Name and Description.

Step #4: Upload the Image:

Next, you need to Upload or Test the Existing Storage Image document from which you want to extract data. To Upload, Just Click on the ‘Choose your Files’.

Step #5: Set Targeted Label:

After uploading the image, you need to set a Label of which data you want to extract.

For Example, Here, we are extracting of Bill, amount, and Name.

Step #6: Choose the Training Option:

Step #7: Process and Collect Data:

After completing all the necessary steps, Here is the Dashboard of the Process of Extracting Data. All Done.

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