Trade finance is one of the most complex procedures in enterprise finance. According to Maersk, hundreds of documents are exchanged regularly among supply chain entities. These include payments, letters of credit, foreign exchange, board of compliance documents, shipping documents, and import and export documents. They must be approved by multiple entities including suppliers, manufacturers, distributors, customers, and government agencies.
Processes such as determining credit for a potential trading partner are complex, expensive, time consuming and even frustrating. Trade finance automation is the need of the hour to overcome the weaknesses in the conventional manually-driven processes. Automation in trade finance can accelerate the process with smart use of digital technologies such as machine learning (ML), natural language processing (NLP), artificial intelligence (AI) etc. Trade finance automation eliminates complexity in every step of the trading process, frees up resources from handling cumbersome tasks, and cuts down costly errors.
Applying Digital Technology
Digital technologies such as Artificial Intelligence (AI), machine learning (ML), natural language processing (NLP) and chatbots, promise to revolutionize the automation in trade finance. They are good at exactly the processes where humans are poor: handling complicated, well-defined tasks that demand constant attention to detail. Humans tend to get bored. When the mind wanders, they are prone to make errors. Smart use of technologies such as AI and machine learning in trade finance can help drive productivity by automating the processes with 90% and above accuracy. AI in trade finance can help make even complex decisions based on well-defined parameters (such as recommending a potential trading partner’s credit limit based on data automatically gathered from multiple trusted sources).
With natural language interfaces, the use of digital technologies can communicate recommendations directly to the manager responsible for the final decision. You can ask ad-hoc questions and get answers based on the best available data. Predictive analytics can help you anticipate and plan for specific problems and opportunities in the market rather than constantly reacting after the fact. The use of AI in trade finance can help you understand your trading partner’s concerns and probable actions, recognize patterns in orders, and better anticipate demand.
AI can automate completing all those trading documents and make sure that the right electronic forms are received by the right entities at the right time in the trading process, without missing anyone. At any time it can produce a detailed report showing exactly where each active trade is in terms of what is filed, what has been processed, what still needs to be done. And this all happens literally at the speed of light, cutting the time required to the fraction of what it is today. Such is the power of automation in trade finance.
Natural language processing (NLP) can understand both spoken conversation and printed documents, translate them fill them out, and send them to the correct people in the supply chain in the language of the recipient. AI and block chain can be used to increase transaction security using smart contracts that have can use embedded computer intelligence to strengthen the trust on which trading is based.
Digital Assistants for Trade Finance
Digital assistants such as Emagia’s Gia, are the equivalent of Alexa or Siri but specifically trained with finance skills. They become the access point for AI tools and can perform multiple functions including credit and business license verification, handling passwords in multiple languages, and other tasks associated with both domestic and international trade finance.
For example, Emagia is working with a Napa Valley winery that ships wines worldwide. It has a manual onboarding process for new distributors and retailers that includes a detailed credit check process to determine the level of credit the winery should extend to the new partner. This is very time consuming, delaying the opening of new business channels and creating other business problems.
Gia can capture all the data required for the credit application from multiple sources such as Experian and other credit rating entities. It can confirm that the partner has the required business, alcohol consumption, and any other licenses. And it does all of this in minutes rather than days. It delivers its recommendations with full drill-down capabilities into the data in natural language, allowing business executives to work directly with it rather than needing to work through a programmer. It can communicate with the prospective trading partner in her native language, simplifying and speeding the process while minimizing misunderstanding.
Conclusions: The AI/Human Partnership
Artificial intelligence (AI) and Machine Learning (ML) are valuable new tools in business that can do amazing things. Gia, for instance, can automate the process of on-boarding new trading partners, solving a major business problem for many companies.
Automation in trade finance can free your employees from the constant distraction of completing boring, repetitive tasks and processes to focus on higher-level, more value-adding tasks. This not only makes the staff more efficient but also improves the productivity of routine businesses processes with utmost precision.