Artificial Intelligence (AI) through Machine Learning (ML) along with Natural Language Processing (NLP) and Optical Character Recognition (OCR) technologies can read and understand texts, then extract important information from a document and check its compliance with other documents or set of laws or rules under predefined parameters which allows the system to interpret data and take decisions. Fintechs have developed AI-based software to take the checking role as a replacement for the current highly manual process of document examination under trade letter of credit (LC) process, which is time-consuming, labor-intensive, and requires skilled and experienced staff to examine the documents for compliance with the terms and conditions of the LC and applicable rules. This paper reports our preliminary studies in using AI and ML in document checking and examination. Specifically, we conducted experiments to compare AI and deep learning results with human checking experts' results. Our findings showed a significant reduction in errors and processing times using this automation and an increase in operational efficiency and optimization of resources. AI-based solution does not mean digitization as human intervention is still required for discrepancies articulated by the automated checks, but it is an important automation step that can assist in the development of hybrid solutions aligning paper to digital toward complete digitization of the trade process under the supply chain.

Keywords
Artificial Intelligence, Machine Learning, Trade finance, Letter of Credit, Document Examination.