In this post, we explore how optical character recognition (OCR) and RPA work hand-in-hand to help organizations extract insights from unstructured data.
The shift to the cloud, globalization and an acceleration of business transformation efforts is driving data growth at unprecedented scale. According to IDC, new data creation is expected to reach 175 zettabytes by 2025 – a 61% increase from 2019.
Analysis indicates that 80-90% of this data is unstructured, meaning that it cannot be easily read or analyzed by machines and, therefore, is of limited use to organizations. With the amount of unstructured data expected to grow in the coming years, organizations are faced with the need to adopt new technologies and processes to tap the full potential of their data and use it to improve decision-making, drive profitability, increase efficiency and enhance the customer experience.
In this post, we explore how two core technologies – optical character recognition (OCR) and robotic processing automation (RPA) – work hand-in-hand to help organizations extract insights from unstructured data, quickly, accurately and with limited human intervention.
Before we explore the relationship between OCR and RPA, let’s first look at these two technologies individually, as well as some related terms:
Unstructured data needs to be analyzed, sorted, saved, and re-entered into various systems to be of value to a business. Traditionally these processes were completed by people, which made them incredibly time-consuming, costly, and prone to human error.
OCR and RPA are two complementary technologies that enable organizations to automate data processes, including data capture, data entry, analysis, sorting, uploading, insights generation and editing.
You can think of OCR as an enabling technology of RPA. It analyzes the patterns that makes up letters and numbers, allowing the technology to recognize text and convert it to a structured, editable format. Meanwhile, RPA technology automates the tasks that precede and follow the text recognition, such as scanning documents, saving them, and uploading them to different systems and tools.
Once converted, the data gathered by the OCR and RPA solutions can be used to generate insights that can improve decision-making, enhance efficiency and productivity, identify pain points and more.
The standard OCR + RPA process follows these three main steps:
Step 1: Document preparation
Step 2: Text recognition
Step 3: Data extraction
OCR and RPA are two core technologies needed for companies to harness the power of their data and apply it to business processes to make them more efficient and effective. Taken together, OCR and RPA unlock an array of benefits for organizations:
Automation greatly reduces the time it takes to recognize, extract, analyze and organize data. OCR and RPA eliminate much of the manual work that slow companies down and keep valuable learnings and insights trapped in their data.
Traditional data processing and analysis can be prone to human error and misinterpretation, particularly when working with larger quantities of complex, unstructured data. OCR and RPA substantially reduce errors and misinterpretation of data and also present information back to human users in an intuitive and easy-to-consume digital format.
OCR and RPA software complete recurring and often mundane tasks, such as data entry, formatting and editing, with limited or no human intervention. This frees up staff to focus on higher-value activity and helps reduce overall costs and operating expenses for the business.
As with any AI- or ML-enabled tool, OCR and RPA becomes more accurate and efficient over time as the ML models and algorithms become more intelligent. This helps drive value for the business and enables organizations to use the technology to complete increasingly complex tasks and unlock more advanced use cases.
Faster, more accurate data processing supports a stronger customer experience and enables higher levels of personalization and customization. For example, some RPA and OCR software solutions can be used to convert text into foreign languages, which can help drive a strong customer experience across different markets and geographies.
OCR software can convert text into text-to-speech, improving accessibility for people who are blind or visually-impaired. In addition to creating a more inclusive user experience, text-to-speech conversion can also be used as a productivity enhancer in that it allows any user to consume information in a passive way.
Combining RPA with OCR capabilities, as well as other intelligent automation tools, can enable a variety of use cases across many industries. These include:
While OCR can be used to capture and analyze data, this tool typically cannot apply insights from the data into an RPA workflow or consider context during the data extraction process. This poses a significant limitation, especially in the modern business landscape, where data must be applied to business processes in order to drive value.
Intelligent document processing (IDP) is a form of intelligent automation that leverages advanced technology, including OCR, to extract semi-structured or unstructured data from any type of document and convert it into structured, usable data. IDP differs from OCR in that it can:
Intelligent data processing makes use of many technologies including:
Terms like RPA and OCR are sometimes used interchangeably with intelligent document processing. However, each of these tools has distinct capabilities and use cases. While IDP, RPA and OCR solutions are related and often used together, they are neither interchangeable nor wholly replaceable. To learn more about Intelligent Document Processing, read our related post here.
Inscribe’s intelligent document automation uses OCR and RPA to make it easy to process customer applications and extract key fields from documents including bank statements, transactions, and payslips. We work with clients to help reduce manual processes and integrate our easy-to-use API to automate document management, streamline account opening or underwriting processes, and enhance compliance.
Key features include:
To learn how Inscribe can help your organization improve your customer experience with a 10X reduction in application review times, contact our sales team to set up a demo today.
Check out our other guides on robotic process automation:
See how you can automate manual document reviews, improve fraud detection, and start approving more customers with confidence.
