This transformation is freeing skilled trade professionals from low-value administrative tasks, allowing them to focus on client relationships and structuring solutions.

Mitigram, the end-to-end trade finance platform for corporates and financial institutions which digitises and automates pricing requests in a marketplace, have recently partnered with Complidata, specialists in AI-driven trade finance automation and financial crime compliance. The partnership adds another layer of intelligence – AI-driven document checking that uses sophisticated rules to validate trade finance documentation – strengthening and automating the communication workflow for export and import letters of credit (LCs).

The timing is right because the technology is ready, and demand from banks and corporates has become urgent. This combination of technological readiness and market need makes it the right moment to embed AI into the heart of trade finance operations. 

The data foundation challenge

Effective AI implementation requires structured data – a prerequisite that has historically been lacking in trade finance. The industry’s paper-based heritage means that much critical information remains trapped in unstructured formats. Organisations cannot leap directly from scattered, unstructured data to AI implementation; the foundation must be built methodically.

This challenge is particularly acute for small and medium-sized enterprises (SMEs), which face a persistent trade finance gap. The Asian Development Bank estimates this shortfall at $2.5 trillion, with SMEs often excluded due to limited credit history and high compliance costs. By organising and standardising data, AI has the potential to make SMEs more “bankable” and unlock financing opportunities previously out of reach.

Contrary to expectations of varied regional receptiveness, industry players operating across more than 100 markets report no significant resistance to AI adoption. The global conversation has shifted from scepticism about AI’s capabilities to discussions about maximising its potential in trade finance operations.

Market forces driving adoption

The Mitigram-Complidata partnership responds to several concurrent and imbricating factors that accelerate the need for AI in trade finance. Trade tariffs and market uncertainty are pressuring institutions to find competitive advantages. Shrinking margins demand operational efficiency gains. Rising client expectations require faster, more transparent service delivery.

The regulatory environment also plays a crucial role. Enhanced requirements for compliance, sanctions screening, and anti-money laundering checks create operational burdens that AI can help alleviate. Automated document checking using sophisticated rules can validate trade finance documentation, reducing the manual effort required for compliance while improving accuracy. 

Responding to market demand

IDC (International Data Corporation) predicts that AI will contribute almost $20 trillion to the global economy by 2030, and with global trade supporting that economy, the implications for trade finance are substantial.

There is already tangible evidence of this shift. In 2024, Mitigram processed record volumes of over $41 billion, driven by growing demand for automation from both banks and corporates. What’s changed? Institutions have moved past experimentation and are actively looking for proven, mission-critical solutions that can deliver measurable value: that is, with structured data. Today, with demonstrated results, the conversation has shifted. Clients no longer ask if AI can work, but ask how fast they can implement it. 

The momentum is being reinforced by market uncertainty due to trade tariffs, shrinking margins and rising client expectations. Together, these factors create the right environment for scale. The industry now recognises that structured data and AI are not just tools that drive efficiency, but enablers of compliance, risk management and financial inclusion. 

Addressing critical inefficiencies

The traditional trade finance process has been plagued by inefficiencies, particularly in document handling and compliance checks. Errors and discrepancies often went undetected initially, forcing banks to review the same documents multiple times. Third-party complications from shipping and logistics companies added additional friction to an already cumbersome process.

The request-for-quote process for LC confirmations exemplified these challenges. Previously conducted through phone calls, emails, and chat, with quotes manually recorded on spreadsheets, obtaining a bank quote could take days. AI automation has compressed this timeline to minutes while improving accuracy.

Mitigram’s platform features a drag-and-drop upload functionality. Users can simply drag trade-related documents into the platform, without the need for manual data entry, and their AI-powered engine will automatically read, interpret, and extract relevant data points. The benefits are numerous: reducing manual entry mistakes, speeding up processing, approvals, and notifications, and enhancing visibility for clients.

The collaboration with Complidata adds another missing piece – compliance and identifying discrepancies. Both Mitigram and Complidata clients can pre-check trade documents for compliance, sanctions screening, and trade-based money laundering (TBML) risks. This will result in reduced operational risk, faster turnaround times, lower days sales outstanding (DSO), and decreased processing costs. 

These improvements deliver concrete benefits: corporates achieve faster liquidity while lowering risk, and banks benefit from stronger data integrity. It’s a competitive bottleneck turned into a competitive advantage. 

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The evidence suggests that trade finance is not only ready for AI but actively demanding it. The combination of technological maturity, demonstrated results, market pressure, and universal demand has created conditions ripe for widespread adoption. The Mitigram-Complidata partnership helps reduce back-and-forth communication, cutting down on discrepancies and speeding up the end-to-end export LC process. 

What used to take days, such as clearing discrepancies or validating documents, can now be done in hours or even minutes. Corporates will become more productive and achieve faster liquidity while lowering their risk; banks, on the other hand, will benefit from stronger data integrity. By applying AI to extract, validate, and check documents against compliance requirements, redundant manual effort can be eliminated.

The next wave of disruption in trade finance is already underway, driven by the recognition that digital transformation is not optional but essential for survival in a rapidly evolving global trade environment.