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Top 3 Trade Finance Instruments in 2024 & Their Automation

Cem Dilmegani
Updated on Feb 14
6 min read
Top 3 Trade Finance Instruments in 2024 & Their AutomationTop 3 Trade Finance Instruments in 2024 & Their Automation

Trade finance is an umbrella term attributed to all the financial instruments at the disposal of buyers and sellers engaged in international trade. The World Trade Organization (WTO) proclaims that between 80-90% of world trade relies on trade finance for realization.1

But even though it’s the backbone of international trade that facilitates our accessibility to goods from faraway corners of the world, we might not be aware of what trade finance actually is. This theory can somewhat be backed up by “trade finance” not seeing any rise in interest on Google Trends.

Therefore, in this article, we will explore all the financial instruments that finance trade offers exporters and importers. Moreover, we will also look at ways by which each of these processes can be automated, mostly by RPA, for faster and more accurate processing of paperwork.

What is trade finance?

Trade finance is the category of all financial instruments that facilitate trade. If you think the formal definition is vague and “too Wall Street,” you could be right: It is just a fancy way of saying there is no cash exchange at point-blank, but there are “instruments” that allow settlement of trade down the line. 

The reason why such elaborations exist in the first place is due to the mistrust between the importer and the exporter. Both are fearful of the other going AWOL after shipping the goods before receiving payment and sending payment before receiving the goods. It’s a classic prisoner’s dilemma scenario. And besides, humans are not the most trusting of species.

In the graph, China is the only country for increasing interpersonal trust. UK remain flat while the rest experience a decrease at different levels.
Figure 1: Interpersonal Trust across countries and years in the lates WVS.

Banks, as veneered institutions, step in as impartial third parties to act as mediators. They assure the counterparties that one would be paid, and the other would receive their goods as advertised. 

Open account trade, letters of credit, and bank guarantees are the most popular instruments which can be automated. It should be noted that there are two more instruments, consignment and documentary collections (D/C), as well, but due to their nature to heavily favor one party over the other, they are not used much around the world. And so we won’t be covering them.

1. Open account 

An open account is an arrangement between the buyer and the seller in which the seller will ship the goods first and then receive payment, up to 90 days later at the latest. There is very little that separates open accounts and cash transactions. The only difference is that the buyer pledges to actually pay for the goods after receiving the bill of lading. 

In cash transactions, unless previously agreed upon and stipulated, there are few binding agreements in place. That stands to reason, for if there are any additional terms and conditions, then the cash transaction becomes something else in nature, such as an open account transaction, thus taking on a different name. 


Open account transactions have their advantages, contrary to them looking rather reckless and dangerous to the exporter. The first is that the exporters could make themselves more competitive than their compatriot traders by offering more lenient payment terms and luring importers in, albeit at the cost of assuming a great deal of risk. The second reason is that the risk they assume could actually have a price: they can mark up their selling price to the importers because they are receiving payment after shipping the goods. 

But regardless of the markup, if you are an exporter wishing to partake in open account international transactions, it’d be paramount that you check the credit history of the buyer, regardless of whether or not you have marked up your commodity to mitigate the risk you are taking on. 


An O2C automation solution can automate the financial side of selling a good. Specifically, it can:

  • Evaluate the credit of the customer
  • Create an invoice
  • Calculate debts provisions for the next fiscal period
  • Estimate how much free working capital would be needed until payment is collected
  • Record the sale on the journal
  • Send an email to the buyer with a payment link for collection
  • Reconcile the accounts

2. Letter of credit (LC) 

Letters of credit are issued by the buyer’s bank to the seller as a guarantee that it will be the bank that will make the payment to the seller instead of the buyer. There are two important stipulations and implications in an LC: 

  1. The LC lays out terms and conditions that the seller will be paid upon providing a bill of lading confirming the shipment of the good. 
  2. The LC passes the risk of non-payment from the buyer to the bank. As far as the seller is now concerned, it’s the riskiness of the bank that should be assessed and not the importer. 


The advantage of a letter of credit is that it creates a win-win scenario for all parties. The seller will receive their payment if they can prove to the shipping company that they have fulfilled their obligations by sending the invoiced goods. The buyer, on the other hand, can rest comfortably, knowing that if the seller doesn’t keep up their end of the bargain, they won’t be paid, the bank voids the agreement, and frees their collateral. Finally, the bank will receive a mediation fee for their trouble. 


The processing of letters of credit by banks can be automated by the combination of different technologies that will work sequentially to undertake the task: 

  1. Overview of documents: The financial documents that the buyer submits to the bank to complete a transaction with an exporter should be thoroughly reviewed. If the documents are in paper form, they should be converted into a machine-readable format, such as PDF. If they are already digitized, RPA and OCR are used to scan the document, read the data, extract it, and enter it into ready-made templates. 
    • The important information includes the applicant’s name, tax number, credit score, credit line, etc, all of which are a factor in granting them an LC. 
  2. Assessment of documents: The numbers on the templates, such as the credit rating, limit, and trade amount, should then be compared and measured against the bank’s metrics and policies. Technologies such as machine learning and NLP are used in this stage:
    • NLP reads the numbers, compares them with reference points, and applies a rating to it based on predefined, conditional framework frameworks (if X, then Y). 
    • The ML technology then uses its historical data to compare the application results of the older, similar applicants to the one at hand. If an LC has been extended to similar applications, this one follows suit. 
  3. Release of result: After the information has been read and evaluated, a verdict is automatically issued. Thanks to RPA, the result, which would be a binary “Y/N” answer, will automatically be copied from the evaluation documents and pasted on the original application form via EDI
    • If the result is positive, thanks to the rule-based approach and schedule triggers, the RPA will copy and paste all the pertaining information of the LC document, and forward it to the clerks for final approval. 

3. Bank guarantee (BG)

A bank guarantee is similar to a letter of credit in that the bank provides exporters with official documents stating that they will pay on behalf of the importer in case of a default. The distinction here is that wherewith an LC it was the bank making payment, with a bank guarantee it’s the bank making payment if the importer doesn’t come through. 


A bank guarantee benefits the exporter by ensuring them that they will be paid, regardless of whom they honor their obligation. The importer can rest assured knowing that the exporter has to ship goods as advertised if they want to receive payment, thus having a strong incentive to act sincerely. Moreover, the importer knows that if they fail to make payment, the bank will seize their collateral – which would be equally valued to the commodity they are importing –  to make the payment on their behalf. So, they, too, have an incentive. And just with the LC, the bank gets commissions for the arbitration. 


E-guarantees are the digitized versions of traditional bank guarantees that have been around for some time. E-guarantees in 2022 could use a combination of different technologies, such as RPA, EDI, workload automation, and blockchain. 

  1. The importer requests a bank guarantee from their bank’s website or mobile app, specifying their intent, the counterparty, the trade amount, etc. 
  2. OCR reads the information and the RPA transfers all the information accordingly onto a worksheet. 
  3. As with an LC, inputs are measured against specified metrics; a decision is made using ML.  
  4. The file is sent to staff via RPA and EDI for review and approval. 
  5. Once the application is approved, the approval serves as a trigger schedule. RPA automatically emails the issued guarantee to the beneficiary, the exporter.   
  6. Now, some institutions, such as IBM, are partnering with banks to integrate blockchain into their mobile applications. This would allow the storage and validation of the BG, in immutable form, on an electronic ledger. 
    • Storage on the blockchain has broader use cases. Tenants, for instance, to rent a new house, can request a bank guarantee, and the bank would store it on the blockchain. The landlord could then take comfort in the fact the bank guarantee is authentic, proven by the digital footprint of the bank creating the guarantee and storing it on a specific date. 
Access Cem's 2 decades of B2B tech experience as a tech consultant, enterprise leader, startup entrepreneur & industry analyst. Leverage insights informing top Fortune 500 every month.
Cem Dilmegani
Principal Analyst
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Cem Dilmegani
Principal Analyst

Cem has been the principal analyst at AIMultiple since 2017. AIMultiple informs hundreds of thousands of businesses (as per similarWeb) including 60% of Fortune 500 every month.

Cem's work has been cited by leading global publications including Business Insider, Forbes, Washington Post, global firms like Deloitte, HPE, NGOs like World Economic Forum and supranational organizations like European Commission. You can see more reputable companies and media that referenced AIMultiple.

Throughout his career, Cem served as a tech consultant, tech buyer and tech entrepreneur. He advised businesses on their enterprise software, automation, cloud, AI / ML and other technology related decisions at McKinsey & Company and Altman Solon for more than a decade. He also published a McKinsey report on digitalization.

He led technology strategy and procurement of a telco while reporting to the CEO. He has also led commercial growth of deep tech company Hypatos that reached a 7 digit annual recurring revenue and a 9 digit valuation from 0 within 2 years. Cem's work in Hypatos was covered by leading technology publications like TechCrunch and Business Insider.

Cem regularly speaks at international technology conferences. He graduated from Bogazici University as a computer engineer and holds an MBA from Columbia Business School.

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