In the world of trade finance, efficiency, accuracy, and risk management are paramount. Financial institutions often rely on complex documentation, such as Bills of Lading (BoLs), to manage collateral, assess credit risk, and verify shipments tied to loans and letters of credit. However, many banks still use manual processes and outdated systems to handle these critical documents, leading to delays, errors, and missed opportunities for optimization.

By digitizing BoLs and making them machine-readable through AI-powered data extraction, banks can automate key processes such as loan collateral monitoring, fraud prevention, and compliance reporting. This shift not only reduces operational costs but also strengthens financial oversight, making trade finance more secure, efficient, and scalable.

Advantages of digitizing the Bill of Lading

The Bill of Lading (BoL) is an essential document to any shipping and freight contract, and it can be used for so much more than transit and record-keeping. Here is how you can use the information on any Bill of Lading to automate and modernize your financial services with AI:

• Loan Collateral Monitoring: Automatically track and verify shipment details from BoLs, ensuring that the goods being financed or used as collateral are accurately recorded and in transit as expected.
• Credit Risk Assessment: Use real-time shipment data from BoLs to assess the movement of goods associated with loans or letters of credit, offering insights into potential supply chain risks that could impact creditworthiness.‍
• Automated Reconciliation: Streamline the reconciliation of trade finance documents by extracting key details from BoLs and comparing them with payment records, ensuring financial transactions align with physical shipments.‍
• Fraud Prevention: Extract cost and transaction details from BoLs to detect inconsistencies or anomalies in financing requests or trade documents, helping to identify fraudulent activities in trade finance.‍
• Compliance and Auditing: Extract and store data from BoLs for auditing and regulatory reporting, ensuring that financial institutions meet trade finance compliance requirements and reduce the risk of errors or omissions in paperwork.

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Extract data from any Bill of Lading with Cradl AI

Cradl AI offers a modern data entry experience where you rely mostly on AI models to extract data from documents instead of a data entry clerk. Tell the AI model what to look for in your BoLs, and lean back while it fetches the data for you.

If the AI model unsuccessfully fetched the correct data field, it will notify your admin and await manual corrections. You can also enable well-known LLMs like Google Gemini in conjunction with Cradl AI to boost your automation degree even further.

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Connect with your existing systems

Cradl AI does not attempt to replace existing automation platforms, but to pair nicely with them by supporting a multitude of integrations. Some examples are Zapier, Power Automate, Blue Prism, any email address, webhooks, as well as developer-friendly APIs.

By making a very simple two-step Zapier flow, you can automate expense tracking by writing data to a spreadsheet every time a document is processed by Cradl AI.

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Conclusion

By using AI-driven data extraction, financial institutions can streamline trade finance operations, reduce risks, and enhance compliance. This shift not only boosts efficiency but also provides real-time insights that improve decision-making and performance. Embracing these tools is key to modernizing banking processes and staying ahead in global trade.

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