Thomson Reuters Calculates Benchmarks For Three Of Africa’s Most Dynamic Economies
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Thomson Reuters, the world’s leading source of intelligent information for businesses and professionals, has won a competitive process to provide currency benchmarks for three of Africa’s most vibrant and dynamic economies – Kenya, Ghana and Zambia. Starting this week, Thomson Reuters Benchmark Services Ltd will operate currency benchmarks for the Kenyan shilling, Ghanaian cedi and Zambian kwacha, beginning a process which will see the benchmarks move from a manual telephone-based system to a state-of-the-art automated analysis, ensuring the integrity and transparency of the rates.
“These three global-standard benchmarks are integral to the development of three of Africa’s most exciting economies,” said Sneha Shah, head of Financial & Risk, Africa, Thomson Reuters. “Kenya is the major trading hub for east Africa, Ghana is growing in the west and Zambia is a country to watch in the south with exciting developments in its commodities and derivatives markets.
“Of the key benchmarks globally for which we are the official calculator, 22 are on the African continent. Now there are 25, contributing to the seamless and efficient flow of currencies among the African countries and their global trading partners.” EMTA Inc. and its African Currency FX Working Group selected Thomson Reuters to provide support to the market for these three benchmarks.
There now follows a three stage transition process to reduce the reliance on manual reporting. The first stage is the transition to Thomson Reuters, with no immediate alteration to the current manual, quote-driven methodology in which calculators gather quotes from market participants. This will be done on a Thomson Reuters platform, which will provide a fully-auditable record of submissions. The second stage begins in August with automated collection of data from the 10 most active contributors to the rates and semi-automated submissions from others. Thomson Reuters will then launch an open consultation on the possible use of transaction data in a subsequent phase.
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