Driving Regulatory Innovation: Automated Swap Data Reporting and Exception Management

Abstract

In this article, I discuss the ways in which technology has been used to build, implement, and maintain an automated report for the purpose of reporting swap transactions that are covered by the European Market Infrastructure Regulation (EMIR) and Dodd-Frank Act (DFA) Rule 12b-2. The automated report will use advances in technology, including but not limited to Artificial Intelligence (AI), Machine Learning (ML), and Natural Language Processing (NLP), to enhance the regulatory reporting process, exception management, and compliance with EMIR, DFA and across all regions of the globe. All automated reports will be designed so that companies can minimize their need to perform manual processing and maximize the quality, accuracy, and transparency of their reports by converting them to a single format and standardizing the way they collect and submit data to regulators. By utilizing the advanced analytics capabilities in combination with a real-time monitoring, companies will benefit from more timely swap reporting and will ultimately enhance the efficiency of markets for all types of securities. The automated reporting of swaps improves the environment for regulatory reporting in regard to the marketplace, provides a new baseline for the financial services industry's compliance with regulation, eliminates or reduces the possibility of violating regulatory requirements within the financial services sector, decreases the cost of regulatory penalties associated with non-compliance, and improves the reputation of the organization overall.