Exploring the Role of RPA Document Processing

In today's data-driven world, organisations grapple with a constant influx of documents. From invoices and contracts to customer applications and loan requests, processing these documents efficiently and accurately is crucial. 

However, manual document processing is often slow, error-prone, and labour-intensive. This is where RPA Document Processing steps in, offering a powerful solution to automate these tasks and transform how businesses handle paperwork.

What is RPA Document Processing?
 

RPA Document Processing leverages software robots, also known as bots, to automate repetitive and rule-based tasks involved in document processing. These bots can mimic human actions, such as:

• Opening and classifying documents

• Extracting data from various formats (PDFs, emails, scanned images)

• Validating and formatting data

• Populating data into enterprise systems

• By automating these tasks, RPA Document Processing significantly reduces the need for manual intervention, leading to numerous benefits for organisations.

Benefits of RPA Document Processing

 

Increased Efficiency

RPA can increase transaction speed by 4 to 5 times across various business applications and platforms. This allows employees to automate the majority of the tasks and look into more tasks that need human judgement.

Improved Accuracy

Manual data entry is prone to errors. RPA bots, on the other hand, follow pre-defined rules and can achieve near-perfect accuracy, minimising errors and rework.

Enhanced Compliance

92% of manufacturers report that RPA helped them improve compliance, and 90% say that RPA has enhanced quality and accuracy (Source:Impact). Consistent and accurate data processing through RPA Document processing ensures better adherence to regulatory requirements.

Reduced Costs

Automation reduces manual labour costs associated with document processing, leading to significant cost savings. Based on the research by Wifitalents, RPA can reduce processing costs by up to 80%.

Faster Decision Making

Faster document processing translates into faster access to data, enabling quicker decision-making based on real-time insights.

Fact: RPA can help organisations to make faster decisions by automating tasks delayed because of excessive process time. (Source: IndianTTS)

Improved Customer Experience

Reduced processing times for documents like applications and claims translates to a more streamlined customer experience.

How Does RPA Document Processing Work?

 

RPA Document Processing typically involves the following steps:

A. Document Ingestion

Documents enter the system from various sources like email attachments, file servers, or scanners.

B. Document Classification

RPA bots use predefined rules to categorise documents. For example:

Example: Invoice Processing - An RPA bot identifies invoices based on keywords like "invoice number" or "due date" in the document.

C. Data Extraction

Once classified, data is extracted using two main methods:

Template-based Extraction: Pre-defined templates specify where specific data points reside (e.g., name, address, invoice total). The bot locates these areas and extracts the data.

Example: Loan Application Processing - An RPA bot uses a template to extract applicant information like name, address, and social security number from a standardised application form.

Machine Learning (ML)-based Extraction: ML algorithms analyse document structures and extract data even from documents with varying layouts.

Example: Contract Review - An RPA bot with ML capabilities can analyse legal contracts and extract key information like dates, parties involved, and termination clauses, even if the layout differs from standard contracts.

D. Data Validation & Formatting

Extracted data is checked for errors and inconsistencies. The RPA system might use pre-defined rules or data validation tools to identify potential errors. Additionally, the data is formatted consistently for seamless integration with other systems.

E. Data Transfer

The processed data is transferred to various destinations:

• Populating data fields within enterprise systems like ERP (e.g., invoice data into accounting software) or CRM (e.g., customer information into a customer relationship management system)

• Storing the extracted data in a designated database for further analysis.

• Triggering downstream workflows based on the extracted information (e.g., automatically sending an approval request for a loan application)

F. Exception Handling

The system identifies and manages unexpected situations, such as documents with unusual formats or missing data. The document might be routed for manual review or the system might attempt to resolve the issue through predefined workflows.

How RPA Document Processing Helps Different Industries

 

Industry	Use Case	Benefit
Finance & Accounting	Invoice processing, Expense report management , & Account reconciliation	Faster processing of invoices, Reduced manual data entry errors, & Improved compliance with financial regulations.
Human Resources	Onboarding processes, Leave request handling, & Payroll processing	Streamlined onboarding experience for new hires, Quicker processing of leave requests, & Improved accuracy of payroll data.
Insurance	Claims processing, Policy renewals, & Underwriting tasks	Faster claims resolution times, Reduced errors in policy renewals, & Increased efficiency in underwriting processes
Customer Service	Customer application processing, Inquiry handling, & Complaint processing	Reduced processing time for customer applications, Improved response times to customer inquiries, & Faster resolution of customer complaints
Healthcare	Patient intake, Insurance verification, & Medical record processing	Faster patient registration and intake, Reduced errors in insurance verification, & Improved efficiency in medical record management
Manufacturing	Purchase order processing, Quality control documentation, & Inventory management	Automated processing of purchase orders, Improved accuracy of quality control data, & Streamlined inventory management processes
Legal	Contract review, Due diligence document processing, & Legal document management	Faster review of legal contracts, Reduced manual effort in due diligence processes, & Improved organisation and access to legal documents
Retail	Order processing, Returns handling, & Inventory management	Faster processing of customer orders, Efficient handling of returns, & Improved accuracy of inventory data

 

What Are The Future Technologies That Will Be Implemented In RPA Document Processing?
 

Natural Language Processing (NLP) for Advanced Information Extraction 

Current RPA can extract data from predefined locations within documents. NLP will take this a step further.  

Imagine an RPA bot that can read and understand the context of a contract, identifying key clauses, obligations, and risks. This would revolutionise legal document processing and due diligence tasks.

Self-supervised Learning for Unstructured Data Handling

Supervised machine learning requires a lot of labelled data for training. Self-supervised learning techniques will allow RPA bots to learn from unlabeled documents, steadily improving their ability to handle scanned documents, emails, and handwritten notes. 

This will be a game-changer for businesses dealing with a high volume of these types of documents.

Document Summarization and Sentiment Analysis

Imagine an RPA bot that can summarise key points from a lengthy report or identify positive or negative sentiment in customer feedback emails. These functionalities, powered by NLP, will enable faster processing of documents and improve business decision-making.

Biometric Authentication Integration

Combining RPA with biometric authentication like facial recognition can enhance security and detect fraud using data processing workflows. This could streamline processes that require document verification, like onboarding new employees or processing loan applications.

Blockchain Integration for Secure Document Sharing

Blockchain technology can provide a secure and tamper-proof way to share documents within an RPA workflow. This would be particularly valuable for sensitive documents like financial records or intellectual property.

CBSL’s RPA Document Processing Solutions

RPA Document processing is revolutionising how businesses handle document processing. By automating repetitive tasks, improving accuracy, and reducing costs, RPA empowers organisations to focus on strategic initiatives while ensuring smooth document handling.

Our expert document processing solutions leverage RPA & other cutting edge innovations to deliver effective intelligent document processing solutions for our clients.

We also offer a suite of other services, including Information data management, business data automation, software solutions, solar solutions, and security printing solutions.

Frequently Asked Questions
 

1. What Is Documentation In RPA?

In the context of Robotic Process Automation (RPA), documentation refers to the process of creating and maintaining comprehensive records of RPA workflows, processes, configurations, and implementations. 

This documentation typically includes detailed descriptions of the tasks automated by RPA bots, as well as instructions for deploying, configuring, and managing these bots. Documentation in RPA is essential for ensuring transparency, compliance, and knowledge sharing within organisations.

2. What Is Automated Document Processing?

Automated document processing involves using technology, such as RPA, OCR (Optical Character Recognition), and AI, to streamline the handling of various types of documents within business processes. This includes tasks such as document classification, data extraction, validation, and routing. Automated document processing systems aim to reduce manual effort, improve accuracy, and accelerate document-centric workflows.

3. What Is The Difference Between RPA & Intelligent Document Processing?

RPA: RPA focuses on automating repetitive, rule-based tasks across multiple applications or systems by mimicking human actions. It typically involves automating tasks like data entry, form filling, and simple decision-making processes.

Intelligent Document Processing (IDP): IDP, on the other hand, specifically targets the automation of document-centric processes by leveraging advanced AI technologies such as machine learning, natural language processing, and computer vision. IDP systems can intelligently interpret, extract, and process information from unstructured documents like invoices, contracts, and forms.

4. What Are The Different Types Of RPA?

Attended RPA: In attended RPA, bots work alongside human employees, assisting them with tasks in real-time. These bots typically operate on the user's desktop and are triggered by specific events or user commands.

Unattended RPA: Unattended RPA bots operate independently without human intervention. They are usually scheduled to run at specific times or triggered by predefined conditions. Unattended bots are commonly used for batch processing and handling high-volume, repetitive tasks.

Hybrid RPA: Hybrid RPA combines elements of both attended and unattended RPA. It allows bots to work autonomously when possible but also provides interaction with human users when necessary. Hybrid RPA offers flexibility and scalability by leveraging the strengths of both attended and unattended automation approaches.