Automating and Enhancing Derivatives Confirmation Processing Using AI/ML Technologies
Capital markets operation teams face numerous challenges throughout the post-trade lifecycle, including delays in trade settlements, booking errors, and inaccurate regulatory reporting. For derivative trades, it’s even more challenging. The timely settlement of derivative trades is an onerous task. This is because trades involve different counterparties and there is a high degree of variation among documents containing commercial terms (such as trade date, value date, and counterparties). We commonly see the application of screen scrapping solutions with OCR in capital market organizations. These applications come with the drawback of being inflexible and high-maintenance.
Artificial intelligence and machine learning (AI/ML) technologies can assist capital market organizations overcome these challenges. Intelligent document processing (IDP) applies AI/ML techniques to automate data extraction from documents. Using IDP can reduce or eliminate the requirement for time-consuming human reviews. IDP has the power to transform the way capital market back-office operations work. It has the potential to boost employee efficiency, enhance cash flow by speeding up trade settlements, and minimize operational and regulatory risks.
In this post, we showcase how capital market organizations can automate and intelligently process derivative confirms at scale using AWS AI services. The solution combines Amazon Textract, a fully managed ML service to effortlessly extract text, handwriting, and data from scanned documents, and AWS Serverless technologies, a suite of fully managed event-driven services for running code, managing data, and integrating applications, all without managing servers.
The solution focuses on the trade clearing and settlement phase of the derivative trade lifecycle. During this phase, counterparties to the trade and their agents determine and verify the exact commercial terms of the transaction and prepare for settlement. The solution utilizes event-driven principles with Amazon S3, Amazon SQS, AWS Lambda, Amazon Textract, and Amazon DynamoDB to automate the document processing pipeline. A web-based human-in-the-loop UI is built for reviewing the processing pipeline and updating schemas to train services for new formats.
The human-in-the-loop process allows end-users to verify the accuracy of the results and intervene as needed to update document configuration mappings. The combination of human and machine intelligence creates an iterative feedback loop that improves the accuracy and efficiency of the document processing pipeline.
Amazon Textract is a key AI service used in the solution, allowing for the automatic extraction of text, handwriting, and data from any document. With the Queries feature, users can specify the data they need to extract from a variety of documents without worrying about variations across formats.
In conclusion, the automation of derivatives processing using AI/ML technologies can significantly improve the operational efficiency of capital market organizations. By reducing manual interventions and speeding up trade settlements, organizations can minimize operational risks and costs. The use of intelligent document processing services like Amazon Textract sets a pattern for many back-office documents processing use cases, benefiting the capital markets industry in reducing costs and enhancing staff productivity.
To learn more about the solution and pricing details, review the pricing of Amazon Textract, Lambda, and Amazon S3. The integration of AI/ML technologies in back-office operations can provide the resilience and flexibility required to adapt to evolving market structures and regulatory requirements.