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Why poor data keeps borrowing costs high

Colorful collection of credit rating labels illustrating data quality issues in finance.

Many developing countries are discovering that years of economic reforms—ranging from improving fiscal transparency to completing IMF programs—do not always translate into better credit ratings or lower borrowing costs. While critics often blame bias in rating methodologies, a deeper issue lies in fragmented and incomplete data systems. Crucial financial and institutional information is scattered across agencies and often hastily compiled, leaving credit assessors with an incomplete picture. As a result, analysts tend to adopt conservative ratings, keeping borrowing costs high. Now, global discussions, including recent UN meetings, are shifting focus upstream—toward building stronger, coordinated data infrastructure. By improving how countries assemble and present their financial narratives, stakeholders hope to ensure reforms are accurately recognized, ultimately unlocking fairer credit assessments and more affordable access to capital.

The Conversation

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