A New Era in Letter of Credit Document Examination: Scaling Human Expertise with Artificial Intelligence

It takes an average of 30 minutes for an expert to review a letter of credit file. At first glance, this duration might not seem excessive. However, when we consider that hundreds of document sets reach banks daily and that customers expect their documents to be reviewed on the same day—or within one to two days at the latest—the issue evolves into a significant operational challenge.

Speed ​​is not the only key issue here.

Letter of credit document examination is a highly specialized process requiring the simultaneous evaluation of letter of credit terms, SWIFT messages, UCP 600 rules, ISBP 821 practices, and the consistency among various documents.

Consequently, manual review—no matter how experienced the team performing it may be—is inherently prone to the risk of error.

Even a single discrepancy (or "discrepancy notice") incorrectly identified or missed can lead to serious consequences for both the bank and the customer.

Overlooking a discrepancy carries risk.

However, treating a non-existent issue as a discrepancy is equally critical. Incorrect discrepancy findings can damage customer relationships and lead to unforeseen financial losses or reputational damage in commercial processes.

Therefore, the fundamental question for the future of foreign trade operations will be:

Not "How can we find more experts?" but rather "How can we scale existing expertise using technology?"

This is because training a truly competent expert in letters of credit cannot be achieved in a short time. For a professional to gain strong expertise in this field, they need to work in a bank's foreign trade operations for years. Interpreting UCP 600, ISBP 821, ICC opinions, letter of credit terms, and numerous document types in conjunction requires significant experience.

Moreover, it is becoming increasingly difficult to find qualified talent willing to work in areas that demand such extensive knowledge of regulations and operational precision.

This is precisely where artificial intelligence is driving a major transformation.

From 30 Minutes to Under 5 Minutes

This was exactly our starting point when developing Trade Complize.

When letter of credit documents and the relevant SWIFT message are uploaded to the Trade Complize system, the system automatically initiates the review process.

The documents are analyzed against:

the letter of credit text,

UCP 600 rules, and

ISBP 821 practices,

while simultaneously undergoing cross-checks against one another.

The system compares names, dates, amounts, shipment details, document contents, and interrelated fields.

With Trade Complize, we can reduce a process that currently takes an average of 30 minutes manually to under 5 minutes—and to approximately 3–4 minutes for most transactions.

However, for us, the true value lies not merely in the reduction of processing time.

The real value is the ability to apply the exact same verification methodology to every file.

The Goal Is Not to Replace the Expert

There is a question frequently asked in discussions about artificial intelligence:

"Will this system replace experts?"

In the Trade Complize operating model, the answer is no. We design this as a "human-in-the-loop" system—a structure where human expertise sits at the heart of the process.

For instance, at a bank, Trade Complize performs the initial review of trade documents.

The system presents potential discrepancies, the reasons behind them, and references to relevant rules and documents to the expert user.

A senior trade finance specialist then evaluates the analysis generated by the system and makes the final decision.

This allows expert staff to focus their time on matters requiring genuine expertise and judgment, rather than scanning documents line-by-line for errors.

In other words, the artificial intelligence does not replace the expert.

It enhances the expert's capacity.

Instead of reviewing just 15–20 files a day, an expert becomes capable of overseeing a much higher volume of transactions. Operations teams can maintain consistent service levels during peak periods, and the organization's limited pool of expertise can be leveraged across a larger volume of transactions.

One of the Most Critical Issues in AI: Keeping Data Within the Bank

In banking technology, where data is processed is just as critical as the performance of the AI ​​itself.

Letters of credit and related documents contain highly sensitive commercial information.

These documents hold data regarding buyers, sellers, prices, products, shipping details, banking information, and various other commercial details related to customers.

For this reason, we developed Trade Complize using an on-premise architecture that operates within the banks' own infrastructures.

There is no need to transmit customer data to external third-party systems for document analysis.

This allows the organization to harness AI capabilities while keeping data securely within the bank's own boundaries. We believe that this approach will become significantly more important in the coming period, particularly for the true scalability of artificial intelligence in the financial sector.

The Real Transformation Is Just Beginning

Letter of credit processes have been conducted using similar methods for decades.
However, banks now face three significant challenges simultaneously:
Increasing transaction volumes, a limited pool of expert personnel, and ever-rising expectations for speed.
Solving these three issues simply by hiring more staff is not sustainable.
Future foreign trade operations will likely not be entirely devoid of human involvement.
Yet, neither will they remain purely manual.
We anticipate that hybrid operational models—where artificial intelligence performs the initial review while human experts handle verification, interpretation, and decision-making—will become the standard in banking.
We are developing Trade Complize precisely for this future.
The goal is not to eliminate human expertise, but to leverage technology to make that expertise—honed over years—faster, more consistent, and scalable.
And perhaps this is exactly where the most significant transformation in foreign trade operations will take place in the coming years.