Advanced Capture

HARVEY SPENCER ASSOCIATES_____________________________________________________________

Advanced Recognition
Expanding the Capabilities of Capture© 2017 HSA Inc.

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Introduction
Advanced Recognition consists of a series of technologies including patternrecognition such as Optical Character Recognition (OCR) supplemented by AI
techniques, computer vision and deep learning with rules based validations
to understand, classify and extract information from a broad set of incoming
multi-channel information. Inputs to the business process are now comingfrom a variety of sources in a multitude of formats. Business leaders arebeing called on to take advantage of all possible sources of information.
Data may come from documents, mobile devices, voice transcriptions, social
media, and images that is distributed and utilized throughout theorganization. Advanced Recognition allows for these multi-source data to beclassified, validated and where appropriate, extracted for automatic entry
into the business process.
Advanced Recognition Drives Business Value
A large German based multinational company started a “paperless office”
initiative with a single capture application for H-R to just create electronic
images of all personnel files, saving floor space and integrating with their
ECM and SAP systems. Through the success of this project and thedemonstrated benefits, capture and automation gained management’sattention. The company continued to realize these benefits as they added
multiple business application without adding additional personnel. By
utilizing Advanced Recognition, they achieved greater accuracy, and had asolution that was easier to deploy and implement in real-time to drive value.
In their shared services environment they found it advantageous to capture
all incoming documents for all business units.
The Advanced Recognition Services reduces cost and enables new businessprocesses and capability to be invoked through enhanced classification
integrated with the business needs and extraction of relevant validated data.

© 2017 HSA Inc.

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Why Hasn’t Every Organization Done This?
There are many companies who have implemented basic capture to convert
and index their paper to solve a departmental problem and stopped there.
Often it was in response to an immediate need:••“We have purchased an ECM solution to streamline our workflow, weneed to install a basic scanning system to get the paper into a digitalformat”“We need to reduce our paper storage costs, so we installed a batch
scanning solution to convert our back files of paper into indexedimages”

Having successfully installed and used a scanning solution for a number ofyears, organizations have achieved the first step in realizing the “paperlessoffice”, but often do not think about how to improve or expand their solution.
The initial solution is out of mind from the IT department and CIO, who haveachieved initial ROI payback goals and have other pressing issues to worryabout. Here is an outline of relative costs of a end-to-end scanning
operations with limited automation:
Capture Step

Labor Cost Comment

Document Preparation+++

ClericalScanning+++

Scanner Operator Cost

Recognition

0

Unattended

Indexing & Validation+++++

Very Labor Intensive

QC and Exception Processing +++QC and Rescan Cost

Release to Workflow

Unattended© 2017 HSA Inc.

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Document preparation, indexing/ validation, quality control and exception
processing are all labor intensive. These costs can be reduced throughapplication of Advance Recognition technology. In addition to cost savings
the speed of processing can add substantial value to Line of Businessapplications and shared services environments. Now is the time to look into
how Advanced Recognition technologies can help improve processes andreduce costs.
Value of Advanced Recognition
Capture, Manage and Control Multiple Inputs
Capture is no longer just about processing scanned images. In the state of
the art digital workplace information is begin captured, analyzed,synthesized and utilized to create and enhance business value. Today’s
requirements include the ability to process images created via faxes, mobiledevices, digital copiers (MFPs) and electronically created images. Once datafrom incoming images is recognized, extracted and routed, these data canbe called for utilization in business processes and analytics. Given today’s
digital workplace why hasn’t every organization embraced Advanced
Recognition to automate business processes?
Most organizations are already running a batch oriented capture system,
which has resulted in efficiencies in terms of lower cost, faster, more
efficient capture and better management of paper. Surprisingly many
capture solutions are still being bought and used for the limited purpose ofscanning and manually indexing paper and electronic documents. In 2016
we found that $434m was spent on these types of basic capture solutions.
As these basic solutions often run in the mailroom or back office they often
receive little “C Level” attention. The prevailing thought is often ‘oh well it
will all be electronic soon as paper is going away’ and as the saying goes ‘ifit ain’t broke, don’t fix it’. While expecting big growth in mobile capture,electronic mail and social media input, the reality is that paper is still a very
important part of the process. Organizations are being called on to generateactionable data for compliance, analytics and customer centric businessprocesses.

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Although scan and store is great and you’re saving money, you are only
scratching the surface in terms of how capture technology can help yourorganization. The Digital Transformation is increasing the amount of imageand unstructured data that affect your business. Daily basic scan-and-store
will not help you manage this new influx of data. The only way to adapt tonew market digital workplace requirements is with Advanced Recognition.
In fact in 2016, 20% of all capture spending or about $700m was invested insoftware to capture, identify, understand, and extract data.
Automated Classification Drives Business ValueIn the past semi and unstructured documents had to be sorted andseparators entered between document types. Manual processes were slow
as operators had to insert patch cards or separator sheets to classify
documents, files and folders. These labor-intensive processes add cost,require printing, and time to insert and potentially remove them afterscanning.
Consider how human understanding is applied to processing a document;
the operator picks up a document, and quickly identifies the document type.
Once a knowledge worker recognizes the document type they can then bringup an interface to manually extract data. The system validates these data
against rules associated with the field using a database lookup. If you get it
wrong, then you have to retype it. It’s all very time consuming.
Advanced Recognition works in a similar way but more efficiently. The
automated capture system looks quickly at the size of the image, overalllayout and using this information determines the document type. This levelof automation provides the high level of routing and indexing informationnecessary to decide what comes next.

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Image
Classification

OCR andtextualclassification

Inbuilt
validation
rulesIntelligent
dataextraction

Capture solutions can provide advanced classification that leverages both
image and textual elements to understand the document type and identify
data to extract. This saves printing costs of barcodes, patch codes, andseparator sheets and, reduces or even eliminates the need for manual
sorting. With today’s improved feeders in document scanners, the cost ofdocument prep, which was previously around $10 per thousand pages, isreduced to nearly nothing. Most organizations report a return on investment
within 12 months simply by implementing automated classification alone.
More business applications are now able to take advantage of data that isgenerated in field offices, customer facing encounters and even information
coming direct from customers themselves. On Demand Transaction Capture
has be growing 10-15% per year and we see this growth continuing in thenear future. Mobile capture is growing at 25% annually. Integrating proven
Advanced Recognition capabilities within a remote/distributed capture
workflow can be effective for some digital workplace applications.
Document Classification Reduces the Cost of Set-up
In basic capture solutions, managers spend large amounts of time setting up
new form types so that operators can manually scan a batch of the same
document type. In order to identify fields the operator has to label orbarcode various areas of the form. They then have to laboriously go field-byfield drawing around each zone with a mouse and then connect that withvalidation rules. Some simple rules are sometimes included, but often thelook-ups and validation rules have to be specifically programed.
Advanced Recognition uses Artificial Intelligence (AI) techniques to “learn”
new document sets and other input types, which then can be incorporated© 2017 HSA Inc.

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into the rule set. Advanced Recognition technology works on the basis of
auto analysis of textual document content, image based analysis of
document topology or a combination of textual and image analysis. The
system can be trained to identify document types and subsequently “learn”
to identify variations. This reduces the need to manually set up and identify
each specific document type and locate the fields to capture. Small changes
between similar documents automatically become incorporated, eliminating
the need for customization and coding.
A digital mailroom is a good example of how Advanced Recognition is being
applied. Mail is opened, prepped and scanned. Electronic documents canalso be input via email or watch folder.
The Advanced Recognition
classification then goes to work to identify the document type. There ofcourse can be exceptions flagged that require verification by the operator
and could provide the basis for further recognition training. OCR, ICR(Intelligent Character Recognition), barcodes are used for auto indexing.
Once uncertain fields are verified either automatically or through somehuman intervention then documents and associated data are sent torelevant databases. Documents can then be called by workflows for routing
to appropriate recipients for review and approval.
Speed - Extract and Validate Data Faster
Through Advanced Recognition the system can “classify a document” but it
can also ‘read a document.’ OCR is not new technology but it has beenenhanced and optimized for various business applications. Application
specific lexicons, business rules and the ability to interpret rich image data
have improved accuracy rates that can be employed as needed for particularbusiness applications. Application Oriented OCR is being applied to invoiceprocessing, form processing and other data automation for the automationof business processes.
Validation of extracted data is important in making the system reliable.
Using forms and invoice processing as examples, there are solutions thatutilize mathematical formulas such as quantity x unit price to validate the© 2017 HSA Inc.

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extended amount, as well as, calculate discounts. If barcodes provide
information concerning document type, then the format must be identified
and the barcode converted to relevant information. If the form is a survey,
using OMR (Optical Mark Recognition) or check boxes recognition can also beeasily automated. By leveraging from preset form types, for example
invoices that have already been setup, the system makes it possible tointegrate a new document or form types in a fraction of the time that legacy
capture and OCR applications required.
With Advance Recognition
technology it is now easy to add new document types to the process
whether they are in paper, fax, image or PDF formats.
Advanced
Recognition enhances auto-validation protocols, improves data accuracy andreduces the number of costly exceptions.
Initiate and Validate Workflows
Utilizing rules and auto-understanding of the incoming information, relevant
metadata can be created and added to the images, which in turn can affectworkflow. The classification and the extracted validated data, combined withbusiness rules, can result in the generation of relevant metadata that is noton the form while capturing it. One example is an order that exceeds thesupplier’s credit. It is possible via look-up into the supplier database to place
the customer’s credit limit within the metadata, and even, provide a look up
linkage to his account and history. By capturing all relevant business data
immediately, organizations interact with clients and prospects, engaging inreal-time.
Within the ECM, ERP or other business application, business processes canbe accessed and modified at the time of capture in real-time in order tobetter understand and route information and images. In the above situation,breaching a credit limit may require a supervisor’s approval.
So theworkflow is modified to allow routing to the supervisor with an attachedmessage, which is automatically created via the capture solution.
Consider a Customer Engagement Management (CEM) environment where
the customer is required to submit a document maybe while on a chatsession or phone call to a customer service representative. Using advanced© 2017 HSA Inc.

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capture the customer may take out a mobile device or scanner to convert apiece of paper to an image on demand. This image could then be displayed
the representative’s screen, as well as, the customer’s with relevant
extracted data with perhaps an dynamically updated application or claim
form. If the information runs up against a business rule requiring an
exception, the workflow routes the new information and may then require an
additional approval level.

Take Action
We have discussed the advantages of moving from simple capture to
Advanced Recognition systems that are impacting business. These benefits
include:1. Advantages of streamlining existing scanning operations – utilize
Advanced Recognition to automatically identify different document
types, eliminating the need for separator sheets with the ability toauto-classify documents. This will reduce scanning set up cost, andimprove efficiency.
2. Understand and Extract more relevant data. With Capture we can“machine read” documents and utilize OC and XML tagging to extract
important data. This allows for data validation, improved accuracy anda more effective process.
3. Consider applying Advanced Recognition to data obtained fromadditional image sources such as mobile devices, fax, and otherdocuments as the business application requires. Now more than justscanned documents available for input into business processes. PDF
documents can be very versatile “containers”. By applying Advanced
Capture understanding and data tagging more information can betransmitted and utilized.
4. The additional understanding that is obtained through Advanced
Recognition opens up opportunities, not only for better understanding
and data availability, but also through application of AI, the ability toinitiate business workflows when appropriate. Data derived from© 2017 HSA Inc.

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Advanced Recognition can be utilized in rules based system that calls
for managerial intervention when necessary, makes data available on
demand for customer facing applications, or automatically routes
information to multiple business processes.
Advanced Recognition unleashes information and opens up opportunities fororganizations to improve operationally, provide enhanced customer
experience and differentiate in the market place. It is said that “informationis power” and now we have Advanced Recognition to harness that power.

© 2017 HSA Inc.

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