- EN
International commodity trading is a business of large volumes, high stakes, and strict rules. Deals worth tens of millions of dollars depend not only on logistics or price, but also on the accuracy of documentation. Banking instruments, including Letters of Credit, are designed to reduce risks between parties, but at the same time create a complex, multi-level verification process. A single inaccuracy in a product name, date, or number of documents can result in a bank rejection, delayed payments, and funds being “frozen” and unavailable for the seller’s operational activities.
These risks are particularly costly for a SMART business client: an international trader working with global suppliers, buyers, and financial institutions. In the client’s operations, Letters of Credit are a key settlement instrument. The company regularly processes multiple amendments to Letters of Credit and prepares document packages that must comply 100% with all bank requirements. Manually checking these requirements, accounting for all amendments, and cross-checking documents was time-consuming and left room for inaccuracies due to human error.
That is why the international trader approached SMART business with a request to automate the verification of Letters of Credit and documents before submission to the bank. The solution had to extract data and account for all amendments to the Letters of Credit, generate an up-to-date checklist of requirements, and identify discrepancies in advance — before the document package reached the bank. Here’s how SMART business implemented this complex solution, which business challenges it helped overcome, and what impact it had.
Simply put, the process in this business works as follows: after a deal is concluded, the buyer opens a Letter of Credit with a bank, and the trading company receives the Letter of Credit with a detailed list of requirements: which documents, in what quantities, and with which wording and details must be provided for the bank to make the payment. After the goods are shipped, the company prepares a presentation package — a package of commercial and supporting documents (invoices, certificates of origin, insurance documents, bills of lading, etc.) — and submits it to the bank. The client’s team explains as follows:
This is the stage where the risk increases significantly. For the bank, what matters is not the logic or intent of the parties, but the literal compliance of the documents with the Letter of Credit terms: product names, amounts, dates, and wording must match exactly. Any discrepancy in the documents can result in a payment delay, even if the shipment itself was completed correctly.
Before automation based on the AI solution from SMART business, the compliance check between the Letter of Credit and the document package was performed manually, which made it impossible to accelerate the process.
The client’s team systematically reviewed:
The challenge was that amendments could apply to individual clauses as well as entire sections of the terms. The same parameter, such as the product description or list of documents, could be changed several times. Therefore, the client’s team had to ensure that the final, up-to-date version of each requirement was taken into account.
The process was further complicated by typical Letter of Credit requirements:
When an error was identified, the bank would return the package for correction, having spent 2–3 days reviewing it. The trading company would then have to repeat the entire cycle of internal verification, corrections, and resubmission. During this entire period, the funds were effectively “stuck” at the bank and could not be used for the seller’s operational activities or other strategic business purposes.
During the analysis, SMART business and the client’s team identified a comprehensive list of issues that were slowing down business processes:
Taken together, these challenges created the need to automate compliance with Letter of Credit requirements: moving from manual document package preparation to a controlled process with a detailed report of all potential discrepancies. This request formed the basis for the key objectives of the automation project:
For us, the value of the SMART business solution is that it goes beyond automated document processing. It provides a complete, controlled workflow for working with letters of credit and documents — from receiving the Letter of Credit to generating the final discrepancy report.
All processes in the solution are built around the main types of input data:
The system processes this data sequentially:
To ensure fast and accurate document processing, SMART business designed the solution so that all operations are transparent, controlled and highly automated. This is enabled by the following technical features:
1. The solution is built on Power Platform (Power Apps) and uses Azure AI services:
2. The system automatically organizes all files for each case — it creates separate folders for the letter of credit, its amendments and the document package, uploads the required files and processes them to extract key information and correctly classify documents for further verification.
3. Easy manual intervention when needed — when manual intervention is required, for example, due to poor document quality or non-standard templates, users can easily enter the required data manually through the interface.
4. Full process transparency for users — all changes and document and checklist statuses are stored in the system and available for review.
The solution was introduced into the client's business processes step by step, ensuring clear control and a smooth transition to the automated system.
At the first stage, the client and SMART business formed the team responsible for implementing the solution, agreed on the baseline schedule and held a kickoff meeting. This gave all participants a clear understanding of the goals, roles and timelines and established a foundation for coordinated work at the next stages.
Next, the project team held a series of meetings with key users to gather requirements, discuss the specifics of working with letters of credit and documents, and approve the business process flow. This provided a complete picture of the current processes and helped identify where the solution could make day-to-day operations more efficient.
Based on the requirements gathered, the team developed a high-level system architecture diagram and defined non-functional requirements such as security, processing speed and scalability. This ensured that the solution would be efficient and flexible enough to support the client's future growth.
Once the architecture was approved, development of the system core began: data processing, automatic recognition of key letter of credit requirements, development of a user-friendly interface based on Power Platform, and integration with Power Automate flows (a business process automation tool that enables sequences of actions to be configured without manual intervention). SMART business used the latest AI capabilities from Microsoft and OpenAI to find the optimal balance between document processing accuracy and system cost. Each component was designed to help users complete their tasks quickly and accurately.
The final stage involved training key employees and providing administrative support from the SMART business team in the production environment. Regular project team meetings made it possible to resolve issues in real time and adapt the system to users' needs, ensuring a smooth transition to a new level of automation.
This consistent and structured approach enabled us to implement a system that automates routine processes and makes working with letters of credit transparent, controlled and convenient for users. Our team now has a tool that improves efficiency, reduces the risk of errors and gives us confidence that our documents fully comply with the bank's requirements.
Even without quantitative KPIs, the trading company saw tangible qualitative benefits as early as the implementation stage. These benefits have a direct impact on the business's operational stability and financial flexibility.
A key result was a significant reduction in the risk of errors when preparing letter of credit documents. Automated recognition of Letter of Credit terms, incorporation of all amendments, and document verification against a single checklist moved this critical process from a manual workflow to a controlled system.
The client's team no longer relies solely on the attention to detail of individual employees. The system highlights potential discrepancies before the documents are submitted to the bank.
All actions — from receiving the letter of credit to generating the final report — are now transparent and traceable. Users can see which requirements have been checked, where risks exist, and which documents need to be corrected. This simplifies day-to-day work and provides a clear audit trail that is important both for internal control and for interactions with financial institutions.
Fewer document returns from the bank mean a shorter path to receiving funds. For a trader working with large volumes and high-value transactions, this directly affects liquidity and the ability to launch new transactions quickly.
The solution laid the foundation for scaling, because as the number of transactions, documents, or letter of credit amendments increases, the process does not become more complex — the system reduces the workload on the team. This allows the business to grow without a proportional increase in operational risks and manual work.
The approach implemented in this case is fully aligned with global trends. According to McKinsey research, finance leaders are increasingly investing in AI-powered solutions. In particular, 65% of CFOs planned to increase their investments in AI tools in 2025, and this trend continues to grow. Just a few years earlier, only about a quarter of respondents reported such plans. This clearly demonstrates the shift in how AI is perceived — from an emerging technology to a practical tool for improving the accuracy, speed, and control of financial processes.
In practice, the use of AI in finance teams is already delivering tangible results. McKinsey cites examples of global companies where AI solutions have taken over a significant share of manual data processing. In such cases, companies were able to free up around 30% of working time and redirect it to analysis, risk management, and business decision-making.
The SMART business solution for this client follows the same logic: AI does not replace the team's expertise but augments it by reducing routine workload, minimizing reliance on human input, and providing transparency at every step of the document verification process.
It is important to note that AI approaches like the one used in this case are relevant not only to the parties to a transaction (the seller or buyer), but also to banks that verify letter of credit documents. Specifically:
As part of another McKinsey study, executives from 44 financial institutions worldwide, from global banks to regional players, were surveyed to assess the progress of AI adoption in business processes. The results showed that:
McKinsey also notes that banks that systematically use AI can achieve a 20–40% reduction in servicing costs, including through automated verification, reduced manual work, and faster decision-making.
Although the SMART business solution was developed to automate the verification of letter of credit documents in international trade, its practical value is much broader. Essentially, it is a universal approach to working with complex, regulated documents where accuracy, compliance with requirements, and change tracking are critical. For companies handling large volumes of financial, legal, or contractual documents in logistics, manufacturing, energy, agribusiness, distribution, or financial services, similar processes often look much the same: dozens of document versions, numerous revisions, strict requirements for wording, and a high cost of errors.
The SMART business AI solution enables you to:
Ultimately, the solution evolves from a specialized tool into a scalable platform for working with regulated documents that can be adapted to different industries, scenarios, and levels of business process complexity.
Experience shows that tasks like those we encountered while implementing this case rarely have universal, off-the-shelf solutions. They require a deep understanding of business processes and the adaptation of technology to real-world workflows. So, if your company also works with large volumes of financial, legal, or contractual documents and wants to improve the accuracy, speed, and predictability of its processes, we can help design a solution tailored to your needs—from idea to implementation.
Artem Stepanov
Product Owner SMART Decision Hub SMART business
