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To resolve the challenges of manual data extraction and processing of documents, a time-intensive and error-prone process, companies are leveraging technologies such as optical character recognition (OCR) technology in collaboration with Artificial Intelligence (AI).
Most of the data generated in companies are either semi-structured or unstructured. Thus, it becomes a barrier to automating the business processes dealing with such documents. Consequently, it leads to resource overuse and errors in manually processed documents. This is why a Document Intelligence Platform (DIP) becomes significant for the success of businesses.
Document Intelligent Platforms are technological solutions that deploy Intelligent Document Processing (IDP) frameworks to solve mundane and repetitive daily tasks. These applied solutions harness the potential of Artificial Intelligence (AI), Machine Learning (ML), Natural Language Processing (NLP), and computer vision to automate and augment the data-handling process.
With this, the brands can quickly and accurately access pertinent data, such as invoices. Details are identified, quality control is ensured, and any errors are flagged, then remedied. According to a projection in 2019 by Gartner, 50% of global B2B invoices will be processed and cleared automatically through 2025. Additionally, 80% of these ‘will be transmitted digitally’ by 2030.
Due to the exponential growth of high-volume data, also known as ‘Big Data,’ extracting, maintaining, and following the needed data for its productive usage poses challenges. The key stumbling block is the inability to acquire data from secure, trustworthy sources faster for online research. Due to this, consistency, speed, and reliability are at stake, and thus, overlooking them leads to redundancy. Thus, managing large volumes of document data extraction will also lead to unproductive processing as it becomes more challenging to extract manually.
Here are some of the challenges during data extracting process:
Data quality: Data quality is one of the most crucial attributes in analytics. Most companies extract data from various sources to get a more precise picture of what is happening within their businesses, but this comes at a cost. Therefore, the benefits of extracting data from multiple sources might not overshadow the risks that come with poor data quality.
Absence of standardization: The information is not always in the format companies require. Organizations thus leverage software solutions to extract and process data. However, this can be expensive and time-exhausting when you’re looking for information from various sources that are not per your needs.
Lack of accessibility: Obtaining accurate data can be a formidable and expensive process. There are many reasons a company might not be able to extract data from a source effortlessly. One reason could be that the resources do not have the needed data, or it is concealed behind a high paywall.
Inadequate data: The data extraction procedure is not always flawless, as data may be misplaced due to errors or omissions during the extraction process.
The importance of document intelligence has grown exponentially over the years as it eliminates human errors by using robust verification techniques to ensure fully accurate and seamless data workflows for lasting results. These contribute to a sustainable data universe for any and every brand to utilize, as well as depend on in the future for reference. Intelligent Document Processing & Document Intelligence Platforms both synergize and synchronize efficient data processing, hence boosting profitability and ROI.
Thus, this functionality secures the future of many businesses, which can then focus on reinvesting their profits in further growth and development, thereby saving resources. As per McKinsey, at least 65% of senior management have stepped up investments in both automation and artificial intelligence since the pandemic began.
Document intelligence ensures quicker and greater data availability, with more accessible and secure information with an accountable digital trail. This promotes higher integrity, especially within sensitive data circles, handling confidential and financial information. It also enables the firms to be prepared for unexpected future events, including expansion, transition, migration, or even merging data with other entities.
Versatile and adaptable: Document intelligence platforms can be integrated with other systems, making them flexible applications for use virtually anywhere. These can be deployed in various domains, be it a banking or medical setting. This transferable versatility is not only unique but also sets up a future precedent of adaptability.
Improves accuracy and speed: Documents and data can be retrieved even quicker and more accurately. It is now easier to automate document categorization, which boosts productivity and saves time and money.
Enhances credibility and reliability: Drives accuracy by using digital signing techniques to eliminate any document or data tampering. This increases the credibility and reliability of data, forgoing the need to verify results, again saving time.
Reduces human effort: Automation using AI, ML, and NLP minimizes human clerical effort to propel data processing speeds to scale quantifiably without compromising on quality.
Boosts customer satisfaction and ensures compliance: Customer service satisfaction levels increase and can be maintained to meet the expected or desired levels using analytical data (extracted via Document Intelligence Platform). It also indexes data for better searchability and compliance.
Ensures data security: Enriched security through controlled data gateways and accuracy measures, ensuring that information is always securely stored. This way, only authorized personnel have access to the correct information.
Handles ‘Big Data’ easily: Better flexibility with personalized data workflows drives capabilities and the capacity to handle big data at scale. Various applications can benefit from this, ranging from custom queries to specific data collation. The agility is what really sets DIPs from any other associated solution out there.
The automated processes of extracting, processing, and identifying pertinent data underpin how DIPs operate. These channels are faster and less susceptible to tampering, hence driving greater accuracy. Classification and tracking ensure that whatever data has been processed are examined, monitored, and thus made suitable for its primary purpose. This ‘fit for purpose’ data serves the industrial need aptly and with precision-based accuracy. Hence, companies can gain data insights from Document Intelligence Platforms which deploy Intelligent Document Processing and harness the power of AI, ML, and NLP.
Some common features that one would encounter across such platforms include:
Finally, the evolution of smart AI, ML, deep computer vision-based learning, and NLP is why document intelligence platforms have emerged to the rescue. Without these constituents to power IDP, data extraction accuracy levels would remain at variable lows. It is now up to stakeholders to see and realize the significant role such processing software plays in driving data-based solutions further afield in our global yet interconnected arena of services. Be it healthcare, finance, retail, or even legal industries, companies can benefit from faster, more accurate, and automated data processing.
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