What Banks Can Automate Today Without Big Budgets
Payments and cards have set an uncomfortable benchmark for the rest of the bank. Near-perfect STP, predictable turnaround times, minimal human effort. It’s natural for senior management to ask why Trade Finance cannot look the same.
The moment that question is asked, the discussion usually jumps to extremes. Full automation. AI platforms. Core system replacement. Multi-year transformation programmes.
That is where the conversation goes off track.
Most banks already run mature Trade Finance systems. They may not be new, but they have been upgraded repeatedly and are far more capable than they are often given credit for. The real problem is not technology. It is that processes have barely evolved alongside the systems.
This piece focuses on what banks can automate today with low effort, low cost and minimal disruption, largely by using what they already have.
Reframing Automation in Trade Finance
Automation works beautifully in payments because the data is structured and the rules are deterministic. Trade Finance is different by design.
It is document-driven, exception-heavy and judgment-oriented. Expecting zero human touch or 100 percent STP is neither realistic nor desirable.
But that does not mean Trade Finance must remain labour-intensive.
A large portion of operational effort today is spent on activities that do not add judgment or mitigate risk. They exist because of legacy process design, not necessity.
Automation in Trade Finance should therefore be viewed as effort reduction, not human removal. The objective is to assist operations, shorten turnaround times and improve consistency, while keeping accountability and controls intact.
Where Low-Effort Automation Actually Exists
Low-effort automation starts by identifying touchpoints where human involvement adds little value, or where the same data is handled repeatedly.
Across instruments, there are several such areas where meaningful gains are possible without changing core systems or workflows. LC advising, documentary collections, LC issuance data entry and certain export payment stages are good examples.
Even partial automation in these areas can materially reduce effort and improve efficiency.
LC Advising: Systems Are Ready, Processes Lag
LC advising is often treated as a high-touch activity, even though the risk involved is limited.
When an LC is received via MT700, authenticity is already ensured. Most Trade Finance systems ingest the message, map the data and perform basic validations. Authorisation matrices and audit trails are already in place.
In practice, the only real human action required is identifying the beneficiary customer. Even this can usually be validated using beneficiary name matching.
There is no justification for multiple manual touchpoints here. Achieving this level of automation does not require system change. It requires aligning the process with capabilities that already exist.
Documentary Collections: High Effort, Low Risk
Import and export collections remain among the most manual processes in Trade Finance.
Not because they are complex, but because they rely on reading documents and manually re-keying data from covering schedules into systems. From a bank risk perspective, collections carry no funded exposure, making them ideal candidates for effort reduction.
This is also a practical entry point for banks’ internal AI teams. Advanced models are not required. Basic OCR, NLP and standard LLM capabilities are sufficient to extract key data from covering schedules and documents.
That data can be populated directly into the Trade Finance system. The system or AI effectively becomes the maker, while the operations team acts as checker.
The benefits are immediate: lower effort, lower cost and faster turnaround.
LC Issuance: Automate the Effort, Not the Controls
LC issuance remains slow in many banks primarily due to manual data entry.
Banks should insist on receiving applications through typed smart PDFs or corporate portals. Most customers, including SMEs, already operate digitally.
Once applications are structured, data can be mapped directly into the Trade Finance system. Maker-checker controls, authorisations and governance do not need to change.
This is not full automation. It is assisted processing that removes unnecessary effort without weakening controls.
Export Payments: Extending Proven STP
During export LC or collection processing, beneficiary details and charge structures are already captured in the Trade Finance system.
SWIFT messages are also already mapped, though often only Trade Finance messages. By extending this slightly and mapping MT910 credit confirmations and matching them with MT756, payment events can be triggered automatically where confirmations are received electronically.
This is a small enhancement that applies proven payment STP concepts within the Trade Finance context.
Other Low-Effort Opportunities
Several smaller activities also lend themselves to automation.
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Tracers for export payments and collections are a good example. Most systems already support automated generation, but banks avoid using it due to content variations. With simple rule-based configuration using ageing and sequence, this can be automated with minimal effort.
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Periodic commission recovery under LCs and guarantees is another area. All required data already exists at issuance. Triggering recovery automatically is a small system change with disproportionate benefit.
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Free-text MT799 messages can be triaged using basic AI to identify intent and route them to the right team.
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Enabling direct collections for corporates handling high volumes of collection documents, reducing bank-side manual handling.
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Auto-closure of LC and guarantee liabilities a defined number of days after expiry, based on configurable rules.
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Automatic settlement of usance documents, TRs and similar instruments based on predefined conditions.
Venzo Perspective
In our experience, high operational effort in Trade Finance is rarely due to system limitations. It is due to processes that have remained static while systems evolved.
Automation in Trade Finance does not require replacing platforms or removing people. It requires questioning manual steps that exist by default rather than necessity, and using technology to remove effort, not responsibility. This is exactly where focused process re-engineering helps banks assess whether their existing Trade Finance systems are being used optimally before investing in new platforms or tools.
The examples above are not exhaustive. They illustrate a broader point.
Meaningful efficiency gains in Trade Finance usually come from small, deliberate changes, not large transformation programmes. Most of these changes are achievable within the existing ecosystem, with limited vendor involvement and modest investment.
That is where banks should start, before committing to larger transformation bets.