How Can the Scope of Receipt Data Extraction Software Be Improved with AI?

How Can the Scope of Receipt Data Extraction Software Be Improved with AI?

No document is as important as the one that reflects the evidence of a financial transaction. Receipts, as we know them, are the most commonly stored documents in households and companies. While there is no doubt that the information printed on every receipt is invaluable, the lack of awareness about automated methods to recognize and interpret this information is frustrating.

With thousands of receipts being generated every day, manual entry and interpretation of receipt data will always be associated with errors and expenses. It was presumed that regular receipt data extraction software will help solve this problem, but even they are not offering a full-proof solution as of now.

However, the use of smart AI integration strategies with existing receipt data extraction software has emerged as a ray of hope for many. In this article, let us see how AI can transform the receipt data extraction experience completely.

In simple terms, an automated extraction of information from receipts to manage data effectively is called Receipt Data Extraction. Performing receipt data extraction becomes possible with the help of the OCR application. The Optical Character Recognition technology helps in scanning data from images, hand-written receipts, printed receipts, etc., and converts them into digital text using the software. This digitally compatible form of receipt data is easier to deal with and can be processed faster.

Automated receipt data extraction is crucial for intelligent document processing, and reduces the time and expenditure associated with traditional data extraction. The only problem with regular Receipt OCR software is that while the scanning, conversion, and extraction of receipt data happens quickly, there is no provision for smart interpretation.

Areas That Can Benefit from Receipt Data Extraction

The following domains of business operation can benefit from this hyper-intelligent Receipt Data Extraction Process:

1. Automating Payment Generation and Collection

Manually recording, processing, and uploading data related to the money that either the company owes to its vendors, or the customers owe to the company is highly cumbersome. Moreover, innumerable receipts are generated for all such transactions, and handling this huge pile of data manually will incur a lot of errors. With receipt data extraction software, these tasks can be completed in minutes, thereby allowing faster clearances as well.

2. Efficient Production and Distribution Chains

Without adequate supply chain planning, a business organization cannot focus on enhancing the quality of its work. The flow of information related to worker deployment, inventory management, service deliveries, demand, and supply scenarios, etc. has to be streamlined to make the supply chain work smoothly.

The only way this can be achieved is through digitization of receipt data extraction. Receipts and invoices store crucial supply chain information. With automated extraction and intelligent processing of this data, unnecessary delays can be avoided. This way, all deliveries will be on time, and the overall efficiency will improve significantly.

3. Managing Employee Reimbursement Receipts

There are numerous occasions when organizations have to reimburse the expenses of their employees. These expenses include the money spent on business travel, training, medical bills, dearness allowances, etc.

However, money cannot be reimbursed unless employees submit authentic proof of the expenditure. Consequently, the company receives hundreds of receipts and bills every month from its workers.

Careful processing of the receipt data is crucial to avoid any discrepancies. Thus, to manage these receipts, and to expedite the payments, it is important to make use of receipt data extraction software.

Challenges in Receipt Data Extraction

While receipt data extraction is pivotal for every organization, it cannot be denied that the process has its own difficulties. Common challenges associated with it are:

Plenty of Errors

The biggest problem in receipt data extraction is that there are usually a lot of errors in the extracted data. Conventional Receipt OCR software is unable to interpret the data which it scans. It is only capable of scanning and merely converting information into a digital format.

Readability Challenges

Several Receipt OCR software cannot scan noisy, faded, and wrinkled receipt images, and thus, the digital copy that they produce contains data that is not readable at all.

Template Dependence

Traditional Receipt Digitization done with the help of simple OCR is highly dependent on templates. It means that if the receipt data is not pre-arranged in a set format, the scanning will not be proper and thus, the digital text will be faulty and hard to read.

AI-Enabled OCR: The Only Way Out

Artificial Intelligence and machine learning tools have allowed us to enrich the regular OCR technology with plenty of impactful features. KlearStack provides an AI-Enabled Receipt data extraction software solution that has self-learning abilities.

Therefore, our software not only scans and converts the receipt data into digitally usable forms but also interprets it to eventually give relevant information to the companies. This way, the output is easy to process and does not have any errors too.

KlearStack’s adaptive machine learning algorithms rule out the need for templates to convert receipt data into a structured digital format. The scanning too, is far better than regular OCR because it is capable of converting all kinds of receipts into clear and readable digital forms. This way, Artificial Intelligence helps in optimizing receipt data extraction.

Ashutosh Saitwal
Ashutosh Saitwal
www.klearstack.com/

Ashutosh is the founder and director of the award winning KlearStack AI platform. You can catch him speaking at NASSCOM events around the world where he speaks and is an evangelist for RPA, AI, Machine Learning and Intelligent Document Processing.