Toward reducing the operational risk of emerging technologies adoption in central counterparties through end-to-end testing

Emerging technologies, such as artificial intelligence (AI) and distributed ledger technology, are increasingly being adopted by financial institutions, promising functional efficiency and cost reduction to stakeholders and users. However, the structural and functional changes associated with the technological transformation of software platforms pose significant operational risks. While some aspects of these risks are well known and studied (such as AI trustworthiness, data privacy and consistency, platform availability and information security), others are underestimated. The extreme complexity and nondeterministic nature of existing technology infrastructures still need to be addressed, as they will soon be inherited by the platforms built with new technologies. The only way to mitigate these risks is extensive endto- end professional testing. This paper discusses the software-testing challenges of traditional central counterparties as well as the risks, biases and problems related to new technologies. It also outlines a set of requirements for an end-to-end validation and verification solution aimed at the new generation of clearing platforms.;Focusing on one of the most common use cases in the capital markets industry, this paper considers the challenges posed by the introduction of blockchain and AI into the post-trade area.