As our clients continue their digital transformation journeys, challenges with traditional document capture solutions are coming to the forefront. Managing and configuring classification sample sets and extraction rules in layout-driven, legacy solutions, is time consuming and expensive. Modern digital businesses require systems that can continue to provide accurate results as forms and businesses evolve. Existing solutions cannot adapt automatically to minor changes requiring application development or engineering intervention for reconfiguration.
Machine learning and AI to the rescue, right?
IBM Automation Document Processing
Most AI solutions are either narrowly targeted to one kind of document (such as ID cards, invoices, or shipping labels) or require significant development effort to wire together the models, the repository, and the user interface. IBM is leading the way with a new fully integrated, deploy anywhere, configuration-driven solution.
The new document processing capability for the IBM Cloud Pak for Automation is a new way of thinking about document capture and data verification.
Imagine a bank receiving and storing bundles of documents related to the opening of a loan. A loan package will often contain a scan of the signed note itself, ID cards, income verification documents, several disclosure forms and supporting documentation like pay stubs, bank statements and the like. These documents might arrive as a single PDF, a disorganized pile of images, pieces of physical paper, or a mix of the above. The documents need to be captured, classified, and indexed with relevant data from each document, then rendezvous with a workflow or case already in progress. At Perficient, we have been helping our customers solve this kind of problem for decades, but it often presented a few specific challenges.
- Document classification
Historically, it has been difficult, time-consuming, and expensive to achieve the vision of accurate automated classification. Traditional approaches required fixed form layout, fixed keywords, barcodes/patch codes or general text matching. These kinds of tools are extremely sensitive to changing document sources and structures. Thinking about that loan package, tax returns and W2s are standard forms with standard layouts that change rarely.
A traditional capture solution might be trained to recognize the layout, however even a minor change year to year could break that classification model. With the machine learning models embedded in IBM Automation Document Processing your classification model will be more resilient to minor changes in form layout. Not only is it pretrained on common document types, the new product makes it easy for a business user to extend the training using custom sets of samples.
- Data extraction
While text recognition technologies have continued to evolve and improve, traditional capture technologies have not progressed in their ability to make sense of that text. The continuing dependence on structured form extraction and assumptions about each document’s layout causes similar problems to my earlier classification example. However, certain document types, like the note itself in our loan example, may have inconsistent layouts. Supporting documents like banks statements, payroll statements and disclosures will vary significantly within a single loan package. With these kinds of documents, we may not know where a piece of information may appear, or even if it is present. Nevertheless, we just want to extract the right information if we do find it. IBM’s new tools come with pretrained deep learning models designed to easily find hundreds of common key-value pairs. In the model setup wizard, a business analyst can add more fields and with a small set of samples, train the system to extract those as well.
So, I hear you saying “This still sounds like machine learning (ML) and AI to the rescue! Why is this different?”
A Cloud Pak for Automation Integrated Solution
IBM has integrated this solution into Cloud Pak for Automation platform via the Business Automation Studio low-code designer. With IBM Automation Document Processing, you have a simple, business analyst friendly wizard that walks through training the classification and extraction models. The wizard enables the user to set up data validation rules (dates, phone numbers, confidence levels) and simultaneously maps that configuration into new or existing document classes and property templates in an IBM FileNet Content Manager repository. These low-code tools enable that same business analyst to design, test and deploy an intuitive user experience for validating classification and extraction results in real-time. This integration also means that these capabilities can be used directly from a Case or Workflow Solution.
Getting back to our example…
A potential borrower goes to the bank’s website and indicates their intent to apply for a loan. They fill out some information, attach a few documents, and a case is started. IBM Automation Document Processing classifies and extracts metadata from the documents, the decision service compares the information provided in the form to the data in the attachments and either automatically rejects the loan, sends a request to the applicant to supply more information or routes the case to a loan officer for further review.
IBM Automation Document Processing capabilities provide the system the necessary data to:
- Automatically check that the applicant entered their income correctly on the application.
- Validate that the requested loan amount is under the absolute limit for that income level.
- Immediately check the credit report of the applicant.
- Automatically request more information from the applicant
…and quite a bit more, all before a human is asked to review anything.
Once the loan is approved, the system can also determine if the executed note:
- Is tagged to the correct loan number.
- Has all the right boxes checked.
Each of these tasks can be completed without human intervention.
Delivering On The Unmet Promise
As you can see, IBM’s integrated and comprehensive approach to applying AI-led automation to document processing tasks is essential to meet the requirements of dynamic, information intensive uses cases. Because it is coupled to an industry leading content services and digital process automation platform, IBM Automation Document Processing enables more rapid delivery of information to automated business processes. These capabilities deliver on the unmet promise of document capture solutions with a modern and readily deployable package.