Document Understanding

One of the main promise of RPA is freeing up data trapped in documents.

Every company in the world has to deal with documents, especially in industries like banking, finance, insurance, manufacturing, and the public sector.

Every selling process involves repetitive document processing (accounts payable & receiving, invoices and receipts, sales orders, shipment tracking)

Automatically capturing data from the scanned / digital documents, validating and interpreting it, eliminates costly process steps, leading to improvements in productivity, customer satisfaction, accuracy of information, and better governance and compliance.

Automated Document Processing:

RPA Bridge Business Process Automations Icon Documents Capture
Document/image capture
RPA Bridge Business Process Automations Icon Data Extraction
RPA Bridge Business Process Automations Icon Classification
Data Extraction
RPA Bridge Business Process Automations Icon Data Validation
Data Validation
RPA Bridge Business Process Automations Icon Data Utilization
Data Utilization

The Automated Process

Once documents are accessible to the bot, they can be automatically digitized and classified, using a combination of technologies to maximize accuracy. Data extraction uses optical character recognition (OCR) technology to recognize and extract data which is then validated using a customizable validation station to ensure accuracy. The validated data is then utilized in the business environment giving the customer unlimited flexibility on ways to utilize their data.


Machine learning bots automatically classify and digitize incoming documents


Bot extracts important information from each document (e.g., name, employer name, pay), which can be easily referenced by agents interested in finding or validating data.


Information retrieved is validated across documents or using a “validation station” to ensure consistency and flag anything that does not match.


People are alerted to any exceptions or missing information.

Final alert

A person is informed when a process is complete and ready to move to the next stage.

Typical Use Case

The software monitors incoming email, automatically identifying each document by type and capturing key data elements to sort and route documents and their attachments to the appropriate person or bot for further handling.

For example, in AP departments each vendor will have its own document layout, but this can easily be processed with full data extraction. The Bot automatically locates and captures data, such as invoice number, total due, line-item details, terms, due date, etc. then validates it against the user’s business rules and data already in the system to ensure data accuracy. Custom solutions allow hundreds of rules to be applied.

Benefits of Document Understanding

Organizations must continually look for ways to reduce costs by leveraging technology designed to integrate and augment their existing systems rather than perpetuating costly business practices or investing in new system infrastructures. By replacing manual processes with an automated document handling, companies experience a number of quantifiable and qualitative benefits, including:

Reduced manual labor costs

Automated document processing can eliminate up to 75% of the often hidden labor costs associated with performing manual data entry and other manual processes. Along with avoiding the planned costs of paying employees to perform the tedious task of keying in data from incoming documents and forms, companies utilizing an automated processing solution no longer face backlogs of incoming documents. And, because a potential front-end bottleneck is removed, the need for expensive, unplanned overtime or hiring additional staff is eliminated.

Increased data accuracy

Manual processing invites the potential for human error. Inaccurate data entry means process staff need to manually correct errors before it wreaks havoc downstream. Dealing with these errors takes employees away from performing more value-added tasks such as servicing customers. By applying custom business rules, an automated data capture solution validates captured data without any human intervention. When these rules are applied, accuracy rates can reach upwards of 99%.

Lower per-document processing cost

Reduced labor expenses, improved data accuracy and faster turnaround times allow organizations to process more documents in a shorter period of time and at a lower cost without requiring additional staff. This means companies that invest in an automated data capture solution quickly achieve a positive ROI and realize a lower per-document processing cost.

Speeds access to critical data

Automated data capture speeds the flow of data and images into a user’s ECM, ERP or other backend system. Automated verification of data also allows discrepancies to be caught immediately. This means accurate data enters the workflow faster – in hours instead of days – making it readily available for downstream business processes.

Saves time and supports compliance with automatic indexing

With an automated solution, data fields can be selected to automatically serve as index fields in the ECM system, eliminating the need for staff to manually key in this information. These metadata fields can then trigger records management and retention rules, ensuring compliance with industry regulations, while also improving search and discovery.

Faster response to customers

When asked, those responding to AIIM research1 confirm a significant improvement in response times can be achieved using scanning and capture technology. As we see in Figure 5, with an average improvement of 4-times, a typical customer response of four days will be reduced to.

Accelerated Productivity

Automate highly-manual document processing tasks to accelerate productivity rates


Save time and costs spent on paperwork with east to deploy and maintain automations

Better Customer Experience

Mitigate the risk of errors and decrease the response time to deliver better customer experience


Help employees escape from the mundane chores and focus on higher value tasks

Achieve Unprecedented Levels Of Productivity

Taking data from the source and using it to automate or eliminate process steps is the next phase organizations should move toward as improves productivity and speeds access to information company wide.


Cost reduction compared to manual document processing


Decrease in errors that mitigates the risk of rework and related losses


reduction in time employees spend on document processing


Increase in employee productivity or customer satisfaction