Tax documents make a large part of the whole underwriting document set, whether it’s a personal loan, small business loans, or mortgage loans. While processing these tax documents, lenders care about the quality and accuracy of extracted data more than anything else. Another fact worth looking at while choosing an automated tax document processing solution is its adaptability to different layouts and changes to form templates.
In this article, we discuss the challenges of processing different tax forms, different types of data extraction solutions, and how you should go about choosing an automated tax form processing solution.
We’ll start with giving insights into common tax forms.
Let’s jump right into it:-
Enterprises, employees, and freelancers use different forms for different purposes. Let’s take a look at some of the most commonly used tax forms:-
The wage and tax statement form, W2 form is provided by all the employers to the employees. This form includes the details about salary paid to the employee in a year, state and federal taxes withheld, retirement plan contributions, and some other perks and benefits at the workplace.
W2 forms are only given to the employee - if you are an independent contractor or self-employed then the work you are doing could be the same but you will receive an earning statement on a form 1099 rather than W2.
IRS W9 form (officially Request for Taxpayer Identification Number and Certification) is most commonly used as business-contractor arrangement. W-9 form is used to verify information such as name, phone number, address, taxpayer's identification number.
This is a tax return form for businesses registered as S corporations. This form is essential for S-corporations because it not only gives the details about reporting income but also shows the percentage of the company's share owned by any shareholder. Passing business tax liability on to business owners is the main reason for getting elected as an S corporation.
The IRS form 1040 is the official form that the taxpayers of the United States of America use to file their tax returns. The form is divided into multiple sections for taxpayers to mention their income and deduction to determine the amount of tax and the refund they can expect.
Despite having relatively fixed structures, tax forms come with certain challenges for OCR software. Let’s take a look at them one by one:-
Tax forms look like highly structured documents to humans but not so much to machines. It is obvious as these forms are designed for the convenience of users. The little structure that forms offer makes it easier for automated data extraction solutions to process these documents, but there still exist variabilities OCR tax solutions have to deal with:-
For example in an application, names are strings, phone numbers are integers but address contains strings, numbers, and sometimes special characters too. Adding to it, address may contain zip code that needs to be identified, extracted, and arranged separately.
Forms do not vary a lot in terms of structure but authorities may decide to change these forms a little once in a while. In that case, the same form from two different years can have the same information at two different places. Template based OCR solutions find it difficult to adapt to these changes and may require retraining to adjust to new changes in the form.
Some forms provide references(as indicated in the image below) to the user to fill the correct information in the correct place. These can be helpful for the users but to the OCR solution, it can be confusing. OCR software may take these references as values, which could result in inaccurate data extraction.
When it comes to handwritten character recognition and extraction, OCR software still are not very accurate. Handwritten texts are sometimes not clear, difficult to recognize, and come with infinite variability, it becomes difficult for OCR software to extract the information efficiently.
Here are some of the most widely used methods to process tax forms:-
Using feature detection, an OCR solution tries to recognize characters in an image by slicing the image into smaller pieces and passing through neural networks to check if it contains a character. However, character recognition is not enough for OCR form solutions, they need to classify and categorize these characters. A rule-based model is trained to extract data using rules based on data reference points in a document. This is highly useful for structured documents that can easily be templatized such as tax forms.
In this approach, the model is trained to find defined ‘anchor text’ to identify the key to map its value against in a tax form. It could be the disclaimer at the top or the footer at the bottom or declaration somewhere in the middle.
In this approach, forms are divided into boxes using horizontal and vertical reference lines. The model is trained to find defined information with the help of these reference lines and boxes. This approach is really useful for forms, as most forms contain just a single key-value pair in a horizontal line.
Docsumo comes loaded with pre-trained APIs for common tax forms that means you can simply upload the forms to our interface to process them. You don’t need to train the model for common tax forms.
Follow these steps to use Docsumo’s pre-trained tax form APIs:-
Docsumo offers 99%+ field level accuracy and over 95% straight through processing for tax forms, that means you don’t even have to look at 95% of the total number of forms uploaded and the processed data is pushed to the database.
Schedule a demo with Docsumo today to streamline your tax form processing end-to-end.
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