OCR for Bills of Lading: How OCR Simplifies Data Extraction from Bills of Lading

OCR technology simplifies the handling of bills of lading. Automating the error-prone manual process streamlines data extraction from bill of lading, reduces cost, and boosts carrier process efficiency. The software relies on advanced machine learning algorithms to extract data from both structured and unstructured documents.

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In logistics and trade, a bill of lading (BOL) is a crucial document that details the specifics of goods being transported. The carrier issues it to the vendor, and it is also a legal contract that accompanies the goods throughout the journey. Once at the destination, the BL becomes part of the shipment receipt. Handling the bill of lading manually is an administrative task that can be time-consuming and error-prone.

The bill of lading OCR has been a breakthrough in the BL handling process. The software can extract texts and numerical data from the BL and deliver the necessary information quickly. Optical Character Recognition (OCR) is at the heart of this technology, enabling the software to read everything from printed words to images and hand-written notes. With the help of AI technologies such as Machine Learning (ML), Natural Language Processing (NLP), and Large Language Model (LLM), the software can understand the context and extract relevant information accurately.

This blog delves into what optical character recognition is and the nuances of OCR bills of lading and explores its functions, applications, benefits, and challenges. 

What is a bill of lading (BOL)?

A bill of lading (BOL) is a legal document issued by a carrier to the shipper. It is a mandatory document acknowledging receipt of goods for shipment. The BL serves several purposes, including evidence that the carrier received the consignment. It also outlines the terms of transportation and serves as a document of title. 

Types of bill of lading 

The different types of bills of lading are as follows: 

  • Inland BOL: Used for shipments within a country's borders. It acknowledges the transfer of goods between locations within the same country.
  • Ocean BOL: Issued for shipments transported via sea. It details the terms of carriage for goods transported across international waters.
  • Negotiable BOL: Allows a third-party provider to contract the carriage. It enables the holder to claim the goods at the destination.
  • Claused BOL: Contains clauses indicating discrepancies or damage to the goods noted at the time of receipt.
  • Clean BOL: Indicates that the carrier received the goods in good condition, without any discrepancies or damage.
  • Uniform BOL: Follows a standardized format and terms. It is often used in international trade to simplify documentation and procedures.
  • Through BOL: Covers the entire journey of a shipment from the point of origin to the final destination. It also acts as a receipt for multiple modes of transportation.

What is OCR in bills of lading? 

In the context of bills of lading, Optical Character Recognition (OCR) helps automatically extract data from essential international trade documents that contain important information like shipper, consignee, product descriptions, and quantities.

Bills of lading are important in the shipping and logistics industry. They contain essential information about the goods transported, the shipper, the recipient, and other details. OCR software uses machine learning (ML) algorithms to recognize and extract various types of information found in bills of lading. 

Bills of lading OCR scans the physical or digital document and identifies key information. The software then extracts all the information the user has set. The bills of lading OCR API then integrates with other systems to use extracted information for various purposes such as record-keeping, data analysis, and more. 

OCR has several advantages for document processing. In the fast-paced logistics industry, data extraction via OCR solutions eliminates the need for manual data entry. It also reduces errors and saves time that goes into entering information by hand. Instead, businesses can rely on OCR to swiftly and accurately digitize their documents and improve efficiency.

The role of OCR in bills of lading

Processing of the BL has been a manual task in the logistics industry for decades. OCR now plays a major role in improving the process by: 

Digitizing and organizing bills of lading

OCR allows carriers to go paperless by making the BL digital. OCR converts physical or scanned bills into digital text by scanning and reading the documents. This information can be integrated into CRMs, ERPs, or other logistics applications. Having digitized copies and the data entered into the system makes it possible to access information instantly. 

Extract relevant information

The OCR bills of lading API can extract all the necessary information. Personnel on the ground can digitally access shipment details, dates, addresses, and other crucial data. The OCR software identifies and captures this information accurately so every detail is correctly recorded. 

Automate repetitive tasks 

An OCR system does an outstanding job of automating repetitive tasks such as data entry and document sorting. Instead of manually entering data from each BL, the software can automatically process hundreds of documents in a fraction of the time. With automation, businesses can save significant time and costs and allow employees to focus on other crucial tasks. 

Ensuring regulatory compliance

Accurate processing and storing of bills of lading is important for meeting industry regulations and standards. OCR software can minimize the risk of human error and take the bulk of the load. It can then ensure that all necessary information is captured and stored correctly. 

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Benefits of OCR in bills of lading 

OCR in bills of lading has numerous benefits, such as: 

Benefits of OCR in bills of lading 

1. Enhanced efficiency

OCR can significantly boost efficiency across different logistics processes. By automating reading and organizing documents, employees can focus their efforts on more value-added tasks. More importantly, the software can process documents much faster than people can. Businesses using OCR in bills of lading will also see fewer entry errors. Overall, this translates into an efficient process. 

2. Cost savings

Manual data entry and document handling incur significant costs as more people are needed. Automating the bill of lading reduces the workforce necessary for the task and saves labor costs. The efficiency of automated systems also means there is less need for rework and time savings. Digital storage of BL also adds to cost savings regarding materials and space. 

3. Improved compliance

Meeting compliance and regulatory requirements is crucial for businesses to avoid penalties and maintain standards. OCR ensures that bills of lading are processed and stored accurately and enables businesses to meet regulatory requirements. The easily accessible records also help companies to stick to industry standards and legal obligations. 

4. Accelerated decision-making

Immediate access to information is crucial in making critical business decisions. With OCR, important information from bills of lading is quickly digitized and made accessible to all stakeholders. This enables teams to make faster decisions regarding shipments, routes, and negotiations with vendors and regulators. Businesses can also swiftly address problems and avoid delays and losses. 

5. Streamlined claims processing

Accuracy of information and data is at the heart of claims processing. OCR software simplifies the process by ensuring that all relevant data from BL is accurately captured and readily available. Without any confusion regarding the accuracy of the information, claim resolution becomes streamlined and faster. The net effect is higher customer satisfaction and a good business reputation. 

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Challenges of using OCR in bills of lading

Bill of Lading (BoL) OCR, while offering significant benefits, faces several challenges that can impact its accuracy and effectiveness. Here's a breakdown of the key hurdles:

Challenges of using OCR in bills of lading

1. Document quality issues

Poor document quality is a major challenge to bills of lading OCR automation. Bills of lading may be scanned from crumpled, faded, or damaged paper documents. This can result in poor-quality and unclear images that OCR systems struggle to read accurately. Smudges, stains, and handwritten notes can further complicate the extraction process. The challenge can be mitigated with advanced pre-processing and algorithms. 

2. Diverse document formats

Bills of lading come in various formats and layouts depending on the type of industry and even carriers. The variation can pose a challenge for OCR systems trained only on structured documents. Each document may have different structures, fonts, and data placement, which requires the OCR software to adapt to multiple templates. Advanced machine capabilities, which enable OCR software to read unstructured documents, are necessary to solve this challenge. 

3. Security concerns

Handling bills of lading containing sensitive information raises security concerns. Data extracted often contains confidential details about shipments, clients, and financial transactions. Therefore, this information must be protected from unauthorized access and data breaches. OCR software that offers robust safety features and strict access control can mitigate this challenge. Additionally, strong security protocols and compliance certifications are necessary to boost the confidence of vendors and carriers. 

4. Integration challenges

Businesses often use multiple software applications, such as CRMs, ERPs, and inventory management systems. Since there are diverse service providers, it can be challenging to interact seamlessly with the OCR solution. Custom bills of lading OCR API can enable integration with different solutions and ensure smooth data flow without adding complexity. 

5. OCR accuracy

Although OCR software does an outstanding job of extracting data accurately, it can still have difficulty with certain fonts, languages, and document structures. Errors in data extraction can cost businesses a lot of money. Mitigating the challenge requires better training of models, deployment of custom models for challenging applications, and human oversight. A user's involvement in overseeing problem areas can ensure high accuracy. 

Use cases for OCR in bills of lading

Here are four main use cases for OCR in bills of lading: 

1. Freight forwarding and logistics companies

Leading freight forwarding and logistics companies use OCR solutions to automate the processing of lading bills. The software extracts key information such as shipment details, consignee information, and cargo descriptions. By digitizing these numbers, freight forwarders avoid manual data entry and increase speed and accuracy. The gains allow them to manage large volumes of shipments, reduce operational costs, and ensure timely deliveries. 

2. Shipping carriers and port authorities

Operations in shipping carriers and ports involve mountains of paperwork. OCR automation solutions can effectively streamline documentation handling and cargo movement. The software quickly extracts data used for different business functions, such as managing shipping schedules, cargo inventory, billing, and other accounting tasks. The fast OCR bills of lading processing reduces bottlenecks at ports, which leads to faster turnaround times for ships and improved port operations.

3. Customs and regulatory agencies

Customs and regulatory agencies must ensure compliance before cargo is cleared to enter or leave the port. OCR solutions rapidly extract critical compliance information and reduce time spent on manual verification by port agents. The increased speed expedites clearance procedures and smoothens port operations. Businesses also have a lower risk of cargo being seized from manual errors by automating the process. 

4. Trade finance and insurance providers

Trade finance and insurance teams need to work with precise numbers when moving cargo. OCR bills of lading solutions give error-free values related to shipment details and other numbers. The data is used for tasks such as transaction verification and risk assessment and to process insurance claims quickly. Reduction in manual labor leads to faster approvals of trade finance and quicker settlement of insurance claims. 

Data fields that can be extracted from bills of lading using OCR

Bills of lading OCR can extract a range of data and information from the document. These include: 

  • Shipper and consignee details: Names, addresses, and contact information of both the shipper and the consignee. 
  • Description and quantity of goods: Information about the specific shipped items and their quantities. 
  • Freight charges and payment terms: Costs associated with shipping and the agreed-upon payment terms. 
  • Carrier and vessel information: Details about the shipping carrier, their vendors, and the vessel used for transport.
  • Date and place of shipment: The location, date, and time the shipment left the port for destination. 
  • Mode of transportation: Sea, rail, air, and road, and the combination of different modes for specific waypoints. 
  • Description of goods being shipped: Detailed cargo descriptions are essential for customs clearance and inventory management. 
  • The unit price of shipped goods: The price of each item necessary for calculating prices and financial accounting. 
  • Total value of shipment: The total value of cargo, insurance, and trade finance purposes.

How to extract data from bills of lading using OCR?

Here’s an overview of how the data extraction process works with OCR bills of lading: 

extract data from bills of lading using OCR

1. Document capture

The first step is capturing the documents, which involves scanning the physical bills of lading to create digital images. BL that are already in an electronic format such as images or document format such as PDF is also uploaded through bills of lading OCR API. The high-resolution images are then fed into the OCR system. 

2. Image preprocessing

The captured images are cleaned up by removing noise, correcting distortions and scanning errors, and fixing the brightness and contrast. Preprocessing is necessary to improve the quality of the image. Once it is easy to read for the OCR software, it is sent to the next step. 

3. OCR processing

OCR processing is the main step in which the software analyzes the preprocessed images and converts the text into machine-readable format. The algorithms identify characters, words, and numbers in the document. Software that uses more advanced engines can also recognize complicated fonts and handwriting. 

4. Data extraction

In this step, specific information is identified and extracted from the processed text. Bills of lading include details like shipper and consignee information, shipment dates, item descriptions, and other information. This step often uses predefined templates to extract information from standard bill of lading formats. Advanced models can be trained and deployed for the tasks if the documents have unexpected formats. 

5. Data validation and verification 

This step involves checking the extracted information against predefined rules or databases to correct any errors. Automated checks usually spot inconsistencies; however, manual checks can also be used to validate important data. Validation is crucial to eliminate errors that can lead to losses and regulation compliance lapses.

6. Output

The final step is to output the validated data in a usable format. This extracted data can be exported into different systems, such as enterprise resource planning (ERP), freight forwarding software, and other specific applications. The integration enables businesses to smoothly transfer data for business processes, management, reporting, and analysis. 

To get a first-hand experience of how you can automate your bill of lading processing, try a 14-day trial of Docsumo

Docsumo: The best OCR software for bills of lading data extraction 

Docsumo is a leading OCR software solution for bills of lading automation.  It offers advanced data extraction capabilities that accurately capture information from various documents. 

Docsumo’s intuitive user interface makes importing documents as PDFs or images from the API, email, or cloud storage easy. The software intelligently captures the necessary information and allows you to review it for accuracy. Finally, Docsumo’s seamless integration with industry-specific software like CRMs, ERPs, and other applications ensures the smooth transfer of the extracted data. 

Docsumo can extract data from both structured and unstructured documents. Its pre-trained models allow the software to be deployed without too much hassle, making it one of the best Bill of Lading OCR software.

Learn how BiagiBros automated shipment notification for 3PL warehouses in our case study.

As a 3PL warehousing company, BiagiBros provides organizations and businesses with supply chain solutions all over the United States. Handling more than 1500 deliveries a month, the 3PL company manually processed over 3000 documents on average. With Docsumo BiagiBros now captures data from unstructured documents with employees only having to review exceptions. The automation saved 500 hours per month for the warehousing company, with more than 95% straight through processing. 

Conclusion 

OCR technology plays a key role in automating the processing of bills of lading. Digital data extraction enhances efficiency by eliminating manual data entry and minimizing errors. As a result, businesses can automate and streamline their document handling and have employees focus on more strategic tasks. 

Beyond increasing operational efficiency, OCR in bills of lading ensures strict adherence to regulatory and compliance requirements. Businesses can subsequently benefit from cost savings and faster decision-making that also improves customer satisfaction. 

The age of manual document processing has come to an end. To stay competitive in the market, carriers and service providers need to leverage automation solutions to handle their documents. Moreover, companies that adopt robust OCR software solutions are better positioned to meet their clients' demands. 

Experience the data extraction and processing power of Docsumo for yourself. Book a demo today and discover how our advanced OCR software can supercharge your bills of lading data extraction. 

Schedule your demo and see why Docsumo is the industry leader in OCR technology.
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Written by
Karishma Bhatnagar

Karishma is a passionate blogger who comes with a deep understanding of Content Marketing & SEO tactics. When she isn’t working, you’ll find her in the mountains, experiencing the fresh breeze & chirping sounds of birds.

What does OCR mean in shipping?

OCR stands for Optical Character Recognition. OCR allows shipping applications to extract text and numerical information from documents.

What are the challenges in extracting data from bills of lading?

Manual data extraction from bills of lading takes time and is prone to errors. Other frequently encountered challenges include insurance claims, delays in payment, and fines and penalties.

How to extract data from a bill of lading?

An OCR bill of lading solution can extract a range of information from the document. Logistics companies can easily automate the data extraction process with OCR software.

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