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5 Benefits intelligent document processing brings to content management
Enterprise content management (ECM) systems have long given employees easy access to whatever content they need to do their jobs. As explained in a previous post, with the advent of AI-based tools and intelligent document processing (IDP) systems, ECM tools can now go further by automating many processes that were once completely manual.
Potential use cases spread across vertical industries that are steeped in document-intensive processes, including healthcare, financial services, banking, and insurance. They also extend to back-office functions that all companies engage in, such as accounts receivable and payable, human resources, and more.
What all these processes have in common is they involve unstructured content, which until fairly recently has been a challenge for automation tools. That all changes with IDP.
In this piece, we’ll look at five examples of benefits modern ECM systems can bring to companies across several vertical industries.
1. Add context to unstructured content
With the help of IDP, modern ECM tools can extract contextual information from unstructured data and use it to generate new metadata and metadata fields. That relieves users from having to fill out such fields themselves to classify documents, which they often don’t do well, if at all. Adding metadata including classification helps enrich content and make it more searchable to fill gaps in business intelligence, and helps automatically set proper security and compliance control, reducing the organization’s risk.
2. Separate large packets of document
While optical character recognition (OCR) has long been used to help “read” documents such as PDFs, the advent of AI capabilities makes it far more effective and accurate. For example, an ECM armed with appropriate AI large language model (LLM) capabilities could scan a large packet of documents containing medical records, referral requests, and consent forms collected from other providers and during patient admission. It could then separate the package into discreet documents for individual processing, relieving employees from that arduous, time-consuming chore.
3. Classify incoming documents
IDP-capable ECM systems that employ machine learning (ML) models can be trained to read incoming documents and classify them by type, according to the text or images they contain. Consider an insurance company corporate inbox that accepts claims, underwriting, and policy servicing submissions. An ML IDP model can be trained to identify each type of document and route it to the appropriate department.
4. Extract and input data
On top of separating and classifying documents, an IDP system can also locate relevant information and extract it from a document. An insurance claim, for example, will have data including an ACORD form that lists the policyholder’s name and address, policy number, type of policy, and the like. The claim may also include notes and photos from an insurance adjuster. With proper training, an IDP model can be trained to extract relevant data from each type of document and input it into a downstream insurance processing system, such as Guidewire. Such automation can save insurance associates untold numbers of hours rekeying such data, while likely doing it with increased accuracy – because computers don’t get tired.
5. Prep content for advanced analytics
In addition to being able to “read” unstructured content, IDP systems can also transform it into a structured format. For many companies, that unlocks a treasure trove of content they can now feed to AI-based analytics engines. Such a capability can bring new insights that drive business decisions. An insurer could analyze years’ worth of claims to find patterns that dictate future underwriting decisions. Healthcare companies may discover clues as to which treatments are most effective for various conditions in patients with similar qualities. The possibilities are nearly infinite.
Hyland is an example of a vendor with an ECM platform that offers each of these IDP capabilities. To learn more, visit here.