Improving Operational Efficiencies through Artificial Intelligence in Capital Markets
Since its founding in 1944, the World Bank has leveraged approximately $20 billion in shareholder equity contributions in IBRD (International Bank for reconstruction and Development) to mobilize more than $800 billion in lending to finance projects and policies that promote sustainable development in middle income countries across the globe. The World Bank funds these loans by issuing triple-A rated bonds in international capital markets. A portion of this funding is invested in high-grade fixed income securities to support the World Bank’s financial strength, preserving capital while generating reasonable returns. Leveraging this experience and expertise in asset and liability management, the World Bank Treasury also provides capacity building services to its clients.
As a large issuer, investor, and trusted advisor to its clients, the World Bank is a large player in global capital markets. This size, franchise, and convening power has enabled the World Bank to lead several market innovations, such as the first swap, the first global bond, the first green bond, and the first blockchain bond. Innovations in the capital markets have contributed to the World Bank’s digitalization knowledge overall. This in turn has played a catalytic role in supporting digitalization and automation in the World Bank Treasury’s work with its clients.
Two new Innovations focus on Post-Trade Efficiency
While many of World Bank Treasury’s earlier innovations have focused on the markets-facing activities (i.e., issuance), an important part of the capital markets ecosystem - the post-trade life cycle flows of fixed income securities - has not yet kept pace with the changing times. This includes post-issuance process flows involving issuers, dealers, paying and calculation agents, clearing systems, custodians, third-party data providers, and end-investors. With a focus primarily on accuracy, stakeholders spend time, money, and effort in recreating and reconciling the same securities data across different systems and stages of the trade life cycle. For investors in particular, any discrepancies in data can mean high opportunity or overdraft costs.
“Technology will continue to play a transformative role in turbocharging productivity. At the World Bank Treasury, we are focused on deploying emerging technologies to enhance the efficiency and accuracy of our treasury operations. These AI solutions strengthen the World Bank’s role as a leader in systemic innovation in financial data management,” said Jorge Familiar, Vice President and Treasurer, World Bank
To address these issues and increase efficiency while maintaining accuracy, the World Bank Treasury has implemented two innovative projects (SHASTRA and ASTRA). The projects, developed for issuers and investors respectively, leverage the latest technological advancements in artificial intelligence and desktop programing languages, and tools like Python and Microsoft Power Apps to create digital copies of securities terms using a bond data taxonomy promoted by the International Capital Markets Association (ICMA). Both projects address a common data problem and can be widely adopted by other financial market participants. To learn more, please contact us at capitalmarketops@worldbank.org (for SHASTRA) and troal_imd_operations@worldbank.org (for ASTRA).
