Despite the continuous digital transition, many businesses still spend a significant amount of time manually processing data from numerous documents. Various facts and data must be processed and input by hand regarding digital files such as PDFs, photos, spreadsheets, and even multimedia such as video.
As a result, retrieving important data remains a challenge. When all is said and done/reviewed, scaling this error-prone operation that also tends to be costly is almost impossible. Artificial intelligence can help in this situation.
AI and deep learning have been tasked with addressing these difficulties to enhance efficacy and efficiency, thanks to their ability to understand text semantics and automatically gain knowledge. Intelligent document processing (IDP), which automates data extraction from unstructured and semi-structured documents and converts it into structured and usable data, has enhanced data extraction with high accuracy.
So, before we understand the role of AI and deep learning in document processing, let’s know what document processing automation is.
Defining Document Processing Automation
The design of technologies and workflows that assist in creating electronic documents is known as document process automation. These include logic-based systems that construct a new record from preexisting text and data parts. Certain businesses increasingly use this method to put together legal papers, contracts, and letters. Automation solutions enable enterprises to reduce data entry time, proof-reading time, and the dangers associated with human error.
Role Of AI And Deep Learning In Document Processing Automation
Consider how AI-powered document processing can improve a variety of corporate processes. Data from costs, insurance, accounting, employee on-boarding, and other documents can be automatically evaluated and filed while managing a variety of formats. In a word, artificial intelligence is not just rethinking but also redesigning how businesses use digital documents today.
AI can unlock the full power of an organization’s data by leveraging natural language processing (NLP) for document inspection and analysis, allowing both employees and customers to be more engaged.
How Is AI Streamlining The Documentation Process?
The steps in the document process automation workflow are as follows:-
· Ingestion Of Data
Whether the data is structured, non-structured, or in any other format, the data source is the principal conduit for extracting information (data). Data ingestion is reading data from various sources, such as PDFs, Excel spreadsheets, emails, Word documents, and scan files.
· Pre-Processing Of Data
Cropping, noise reduction, and filtering are image and data pre-processing techniques that simplify data extraction.
· Data Collection
Extracting relevant data is one of the most critical tasks in the entire operation. OCR is a cutting-edge technology that is supported by a variety of machine learning algorithms. Various computer vision models and libraries, such as CNN and OpenCV, are available to assist text detection and extraction.
· Indexing/Classification Of Data
Following the extraction of data and text from the source, classifying or indexing that data according to the template is a substantial task. For example, when extracting text from invoices, it’s critical to distinguish date, amount, name, and other fields from the text you’ve removed. Deep learning models come to the rescue here, labeling data by category and AI automating the entire process.
· Extraction Of Data
The information you obtain through the preceding procedure could be in several formats, including text or images. NLP and computer vision techniques aid in the comprehension of the underlying data.
Sectors Using Document Processing Automation
The idea of a paperless office is a long way off for many industries, and industries like banking, insurance, healthcare, logistics, and government are all replete with paper documentation. So, let’s look at industries that use document processing automation.
1. Financial Services And Banking
Even if cryptocurrencies are displacing traditional transactions, cash is still king in the economy, and checks are widely used. Officers must access the KYC document and verify the signature for legitimacy before honoring a cheque payment, which is a manual task. This is a time-consuming operation because of the large volumes and repetitive processes. This process can be made touchless with image processing techniques. This is a part of Intelligent Document Processing, and 10xDS has implemented it for a central Middle Eastern bank. IDP solutions can also alter account opening forms, maintenance forms, mortgage applications, KYC, and tax forms.
2. Insurance
Insurance firms face a threat in the form of claims forms. Claimants must sign these paper forms. Insurance officers must compare the claim to the policy paperwork for coverage and eligibility. This holds for any insurance. Verification of supporting papers such as invoices and receipts is also required. In the insurance industry, IDP is beneficial for documents such as life insurance applications, auto accident claims, disability forms, change of beneficiary forms, and annuity account forms, among others.
3. Healthcare
Patient intake forms, enrollment documents, health insurance claim forms, and many more paper documents are employed in healthcare institutions. The administrative cost of processing the data from these documents is enormous. The healthcare sector has a significant chance to focus on digitization, data extraction, and processing these forms.
4. Government
Intelligent document processing can be used for various documents, including employment applications, tax filings, and social security paperwork. Many countries of the world still use paper for government documents and forms. Even though many government institutions are pursuing digitization, they cannot eliminate paper-based signed forms, and processing and storing these papers is a significant difficulty.
5. Logistics
Multiple parties coordinate and ensure the delivery of goods and payments in trade finance. Letters of credit and other paperwork that must be processed are used to communicate between banks and businesses. The processes mentioned above can readily be automated.
Benefits Of Document Processing Automation
Now that we know how document processing can be used in enterprises let’s look at some examples. This may have prompted you to consider how you might implement these solutions in your organization. We’ll look at some of the essential document processing advantages.
- Improves Productivity And Efficiency
One of the essential advantages of Intelligent Document Processing is that it reduces the need for human intervention and labor-intensive tasks in many document-centric workflows. The only time a person is required is if a data problem that IDP solutions cannot resolve.
Extracting, converting, sorting, and indexing data using these IDP solutions takes seconds. Unstructured documents are included. This can significantly improve the efficiency of these critical business processes.
- Helps In Cost Cutting
To decrease costs and to stick to a tight budget is one of the most critical tasks for every organization. Intelligent Document Processing can also help you save money almost immediately.
Because these Intelligent Document Processing systems minimize processing times, they can reduce the number of people needed. Furthermore, these technologies can aid in the reduction of other operational expenditures.
You’ll get a greater return on investment (ROI) with more efficient systems and procedures than other software or even human employees. And more quickly!
- Make Your Procedures Go Faster
Large amounts of data might take a long time to process for anyone. However, the good news is that bots can easily handle large amounts of data.
Another essential benefit of Intelligent Document Processing is the ability to speed up your procedures. After all, manually entering data is mind-numbingly monotonous and time-consuming due to its labor-intensive nature.
- Lowers The Chance Of Human Error
Unfortunately, human mistakes occur, especially when vast data must be entered fast. This can have a lot of negative ramifications for a company, especially now that GDPR is in effect.
However, because Intelligent Document Processing solutions eliminate the need for manual effort and data entry and deal with any abnormalities or errors, they can significantly lower the danger of human mistakes. This results in faster data extraction and organization and more accurate and high-quality data.
- Compliance And Data Security Becomes More Straightforward
Similarly, the ability of Intelligent Document Processing systems to automate operations and reduce the risk of human error can assist firms in becoming more compliant.
This is critical in today’s digital environment, where individuals are more concerned about the security of their personal information and how it is utilized.
Because document processing solutions always leave a digital trail, compliance is much easier. This trail can then be utilized to audit and ensure that data protection requirements are followed. Not to mention that the security technology ensures that the data within is kept safe and secure and cannot be misused because only authorized individuals have access to it.
Conclusion
Document management is essential for information distribution and preservation, and AI is a source of value creation that can be applied across the board. Depending on how complex document processing workflows are, the cost savings from automation may not be worth it compared to manual processing.
Automating an everyday routine like a customer support request is one thing, but more complex and particular circumstances necessitate a custom solution. Organizations that have advanced document processing technologies already have a competitive advantage. However, transitioning totally from manual to automated document processing may not be as simple as it appears.
The promise of end-to-end automation of document-centric business activities is too attractive to pass up, especially given the exponential growth of unstructured data in the coming years – but only if the opportunities are adequately studied.
To know the importance of AI and automation, contact the ONPASSIVE team.
