A global database of emerging market debt statistics created by top development banks is utilizing artificial intelligence to parse risk more comprehensively for investors and help lower borrowing costs for developing countries. The Global Emerging Markets Database (GEMs), launched in 2009 by the World Bank Group and the European Investment Bank, is a collection of data on debt defaults, recovery rates, and other data across emerging market companies and countries.
UK-based AI firm Galytix is creating a framework to crunch numbers in GEMs, aiming to attract more private money into developing countries and address the gap between real and perceived risks of investing in the developing world. The partnership will turn the database's decades of risk knowledge into actionable market intelligence, enabling more investment and helping developing countries access much-needed capital.
The initiative comes as developed countries slash aid spending and cut bilateral finance, narrowing sources of capital for some developing countries just as spending needs for infrastructure, climate change mitigation, and social costs like health and education intensify. By leveraging AI, the GEMs database can provide more granular information to potential investors, making it easier for them to parse the data in a useful way and invest in emerging markets.
This development is crucial, given the growth of the emerging market debt landscape, which has reached a market capitalization of over $8 trillion. Emerging markets bonds now represent about 11% of the global bond market, with debt issued in local currency leading its growth. As the asset class continues to mature, the use of AI in emerging market debt is expected to play an increasingly important role in navigating the complexities of this market.
