IDC predicts that worldwide data will exceed 175 zettabytes by 2025, from 45 zettabytes in 2019. That’s a lot of data! Business data makes up a significant portion of it. But unfortunately, 80% of all business data is trapped in unstructured formats such as documents, emails, images, and PDFs. Converting unstructured, handwritten, scanned documents into digital, searchable, computer-readable documents is one of the biggest challenges faced by many organizations.
Some industries suffer more from this challenge than others. Financial services organizations need to examine documents, such as a loan or credit applications, with the highest degree of accuracy and care, often turning to manual review to pull out sensitive or critical information, such as mortgage rates or credit scores. Healthcare and life sciences organizations are fighting an uphill battle against an ever-growing mountain of documents and forms, searching for and analyzing data that is essential to clinical trial research and patient diagnosis in order to more accurately treat their patients. Public sector entities are forced to tie up their already-strained resources to process data from documents, such as applications for a wide variety of services. However, unstructured data present both a challenge and an opportunity for a business.
Digitization is the need of the hour
Digitization (not to be confused with Digital Transformation) is often discussed as one of the possible solutions to make the most of business data trapped in documents. Digitization is the process of converting information into digital format. Over the years we have seen many digitization initiatives across different industries. But digitization is not revolutionary anymore, it’s evolutionary. Organizations have to embrace it to survive and stay relevant. Intelligent Document Processing (IDP) is one of the digitization workflows that uses advanced technologies such as natural language processing (NLP), Computer Vision, Optical Character Recognition (OCR), and machine learning (ML) to capture, extract, and process data from different types of documents.
Even though digitization and IDP has been top of the mind for many business, the pandemic has drastically increased the urgency of it. In early 2020, almost all business were forced to go ‘online’ in a matter of days. And the consequences of not doing effective digitization were far too real to overcome. In April 2020, the US federal government announced the Paycheck Protection Program (PPP) to provide small businesses with funds to cover up to 8 weeks of payroll, mortgage, rent, and utility expenses. With phenomenal demand and over $349 billion allocated in just the first 13 days of the program, small business owners were scrambling to qualify.
BlueVine, a fintech company that provides small business banking, used their technology, engineering expertise, and the power of machine learning to help process billions in loans. BlueVine used AWS machine learning to automatically extract text and data from documents, to help automate the loan application process. In just 4 months, they were able to serve more than 155,000 small businesses with over $4.5 billion in loans during the first round of the Paycheck Protection Program. They delivered services to those who needed it most, with 79% of loans going to customers with fewer than 10 employees and 94% of loans under $60,000—serving small businesses struggling to remain afloat. BlueVine worked closely with DoorDash as their strategic partner to serve many stressed small independent restaurants, and simplify and accelerate the loan process. BlueVine used ML to automate loan application processing and scale quickly to meet the unprecedented demand. The company estimates they helped save 705,000 jobs in 2020 and 2021 as a result of their efforts.
Desirable side effects of IDP – increased accuracy and improved productivity
One of the biggest advantages of digitization through IDP is the improved productivity. Document processing has traditionally been a very labor and time intensive task. For example, a typical PDF form has about 50 form fields; to recreate it as a digital form, the person has to drag and drop data to the right location on each form—a particularly time-consuming and dreadful task. HelloSign, a Dropbox company that automates the signature process, introduced HelloWorks, a product that turns PDFs into mobile friendly forms. Using AWS machine learning, HelloSign automatically processes pdf documents and saves its customers hundreds of precious hours. Intuit, who provides innovative financial management solutions, including TurboTax and QuickBooks, to approximately 50 million customers worldwide uses machine learning to understand documents and eliminate manual data entry for its customers. For millions of Americans who rely on TurboTax every year, this technology simplifies tax filing by saving them from the tedious, time-consuming task of entering data from financial documents.
We still need humans in the loop for extra oversight
One of the most crucial parts of document processing is ensuring the accuracy and security of information. Due to regulatory requirements and other unique business needs, many organizations must still rely on manual processes to analyze documents while processing sensitive documents in healthcare, handwritten documents, or insurance claims. Machine learning technologies with a built in human-in-the-loop mechanism helps organizations get the best of both worlds.
National Health Service, Business Services Authority (NHS BSA) provides a range of support services to healthcare organizations, contractors, and patients in the United Kingdom. As part of those services, NHS processes 54 million paper prescriptions per month. The organization requires an IDP solution that can do that work quickly—but can also enable fast, easy human intervention where necessary. NHS BSA uses machine learning with human in the loop technology to apply expert human judgement to various workflows.
Undoubtedly, documents are the building blocks of every business. Getting the most of the data trapped in documents is of utmost importance for modern businesses. IDP augments human workforce by giving modern workers the tools needed to uncover valuable information from business documents. As we reimagine the future of work and the future of data processing, intelligent document processing is where it all starts.
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