How banks can transform trade finance

Current operational challenges amid broader banking disruption

While its products (e.g., letters of credit, collections, standbys/guarantees) are among the oldest in the banking industry’s history, the traditional trade finance market remains a critical input to supporting international trade around the globe. It also provides capital to often-underserved emerging markets as well as small and midsize enterprises. Although the banks that support this market are well versed in its complexity, the manual, paper-based processes they often leverage today with minimal technology enablement will not be sufficient to address growing customer and regulatory expectations. The legacy approach to trade finance also increases banks’ reliance on an ever-shrinking workforce of skilled trade professionals, who must perform and deliver with accuracy, efficiency and consistency.

Perhaps now more than ever, business model transformation is essential to driving value and efficiency in the traditional trade finance space. While many banks have undertaken digitalization initiatives (and some have seen progress), these efforts are frequently ad-hoc in nature (e.g., changes in how documents are received, how banks exchange information with their customers), and these digital islands are not connected across the broader trade ecosystems.

For banks that operate in trade finance, these piecemeal digital solutions don’t always provide the anticipated benefits due to complex or unproven technology, often resulting in programs that are delayed or over budget. Additionally, banks are digitalizing parts of company systems without leveraging a complete transformation approach to address their most pressing end-to-end business and operational challenges.

How business model and digital transformation in trade finance creates value for banks

To drive long-term success and resilience in trade finance and beyond, banking leaders will need to take a holistic, cross-functional approach, developing a target operating model to reimagine the business through the lens of three key pillars — people, process and technology.

People

With a retirement wave looming for many of today’s highly skilled trade finance operations professionals in key markets, recruiting and training new staff will be essential for banks to drive competitive advantage. Centralizing operations staff in locations that are better suited to recruiting will also help alleviate this pressure. In addition, centralization can drive down costs, improve scale efficiency and allow for better load sharing. For example, deploying technology around automating checks for trade-based money laundering (TBML) or other types of financial crime can not only drive efficiency by reducing the number of manual checks, but also provide consistency around implementing compliance policies. In addition, deploying the right technology around document examination, which typically relies upon very experienced resources, can shift many of these tasks to lesser experienced resources who can help share the load. This approach frees up scarce experienced resource capacity to address higher-value activities, such as providing customer advice and customer service and executing other tasks that drive business growth.

Process

Reimagining company operations and business processes to address the challenges discussed above at a functional level is another key element of business model transformation in trade finance. As such, industry executives need to take a strategic approach to achieve enhanced risk controls and the following efficiencies:

• Streamlined end-to-end business processes
• Minimization of manual touch points by the workforce
• Delivery of an enhanced customer experience, meeting or exceeding customers’ expectations around transaction turnaround time and service quality
• Balanced workloads across roles and company functions and the ability to shift resources based on workflow and bottlenecks

Although traditional trade has become a low-growth area, the volumes of data generated as part of every transaction can bring significant value. By analyzing customer and counterparty behavior, banks can both reduce manual compliance escalations and create new potential sources of revenue. This approach can also help banks meet customer demands by sharing information in a responsible manner across authorized counterparties, ultimately driving efficiency across the entire trade ecosystem. Data-driven insights also can also yield operational metrics (e.g., processing times, performance against customer service-level agreements (SLAs), transaction backlog) that help banks fine-tune processes to drive a more streamlined trade finance function.

Technology

Historically, banks have made limited investments in their technology platforms, instead relying on personnel who perform manual activities. As such, many banks today continue to rely on outdated legacy technology that is costly to maintain or upgrade. Some banks have invested in vendor-managed platforms that, in some ways, keep pace with modern technology. However, vendor dependency makes it difficult to keep pace with all of a bank’s changing business needs. Given these conditions, trade finance leaders need to develop cross-functional processes to book transactions and complete similar tasks more effectively.

The industry and its ecosystem partners, including shippers, insurers, customs agencies and standards organizations, have begun to make progress on digitalizing key paper-based documents. Additionally, some governments have started supporting digital transformation initiatives. However, to fully address this issue, banks will still need to move beyond the ad-hoc digital adoption of today and enhance their internal processes beyond merely digitalizing documentation. 

For example, some banks have seen success with trade process automation across customer-facing systems, transaction handling and booking, document examination and compliance screening. This approach leverages tools such as application programming interfaces (APIs), optical character recognition (OCR), natural language processing (NLP), artificial intelligence (AI) and machine learning (ML). While OCR is important in driving automation, the data it derives can be used to automatically extract information for sanction screening and then input into a transaction booking system that is used to perform checks for TBML and other financial crime activities as well as document examination. Given the complexity and quantity of unstructured data and the breadth of trade documentation, implementing these technologies requires a strategic approach to drive excellence. Although industry usage is relatively low today, delivering this type of automation across the banking industry will be table stakes in the near future, underscoring the need for industry leaders to act now.

Actionable steps for trade finance and banking executives

From the outset of the digital transformation journey around trade finance, banks need to develop a target operating model with a roadmap that helps them define the initiative’s goals, prioritize required steps to drive progress, and secure required investments. While this journey won’t happen overnight, some banks are already planning or implementing the following strategies now to drive long-term growth and resiliency.

1. Define your end-to-end client, business, operational and risk objectives and design a target operating model around achieving these goals.
2. Enable digitalization of documentation and your internal processes through the use of AI, ML and NLP to extract information from semi-unstructured documents to improve consistency, compliance, risk management controls and overall efficiency (among other benefits).
3. Prioritize all other manual activities where proven automation technologies can be deployed.
4. Consider a more efficient technology approach supported by both the banking and technology industries.