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  • Casual Articles - RTGS Systems – Progress to Date and Future Growth

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    spread of RTGS systems is consistent with the standard S-curve prediction (initially take-on is low led by “innovators” after which the rate increases as “early adapters” introduce the system after which the rate of increase levels out).

    The chance that a country introduces RTGS in a given year increases significantly in the level of real GDP per capit

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    Real Time Gross Settlement (RTGS) is a specialized central bank application that ensures the settlement of critical payments in the financial system. Given the relatively small number of countries on our planet, one would think that the proliferation of such systems is universal. This is not the case as recent research has shown.

    This Fall saw the publication by the New York Federal Reserve Bank of, Staff Report (No. 260, September 2006) entitled “Technology Diffusion within Central Banking: The Case of Real-Time Gross Settlement”.

    The report examines the speed and the rate of the introduction of RTGS systems and technology to central banks. At the time of publication there were 174 central banks around the world. Starting in 1985 when only 3 central banks operated RTGS systems, the end of 2005 saw 90 central banks operating such systems. The remaining 84 banks are expected to have all introduced RTGS systems by about 2020.

    The paper summarizes what RTGS is as well as the role of the G10 and the BIS in setting the standards and being the driving force in the move to RTGS adoption. Interlinked systems, such as TARGET (and also CLS to a lesser extent) have helped force the pace of change.

    The introduction period is exceptionally long, having taken 20 years to move from 3 central banks to 90 central banks and the anticipated additional 15 years to cover the remaining 84.

    The report finds that the spread of RTGS systems is consistent with the standard S-curve prediction (initially take-on is low led by “innovators” after which the rate increases as “early adapters” introduce the system after which the rate of increase levels out).

    The chance that a country introduces RTGS in a given year increases significantly in the level of real GDP per capita

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    cation by the New York Federal Reserve Bank of, Staff Report (No. 260, September 2006) entitled “Technology Diffusion within Central Banking: The Case of Real-Time Gross Settlement”.

    The report examines the speed and the rate of the introduction of RTGS systems and technology to central banks. At the time of publication there were 174 central banks around the world. Starting in 1985 when only 3 central banks operated RTGS systems, the end of 2005 saw 90 central banks operating such systems. The remaining 84 banks are expected to have all introduced RTGS systems by about 2020.

    The paper summarizes what RTGS is as well as the role of the G10 and the BIS in setting the standards and being the driving force in the move to RTGS adoption. Interlinked systems, such as TARGET (and also CLS to a lesser extent) have helped force the pace of change.

    The introduction period is exceptionally long, having taken 20 years to move from 3 central banks to 90 central banks and the anticipated additional 15 years to cover the remaining 84.

    The report finds that the spread of RTGS systems is consistent with the standard S-curve prediction (initially take-on is low led by “innovators” after which the rate increases as “early adapters” introduce the system after which the rate of increase levels out).

    The chance that a country introduces RTGS in a given year increases significantly in the level of real GDP per capit

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    d the world. Starting in 1985 when only 3 central banks operated RTGS systems, the end of 2005 saw 90 central banks operating such systems. The remaining 84 banks are expected to have all introduced RTGS systems by about 2020.

    The paper summarizes what RTGS is as well as the role of the G10 and the BIS in setting the standards and being the driving force in the move to RTGS adoption. Interlinked systems, such as TARGET (and also CLS to a lesser extent) have helped force the pace of change.

    The introduction period is exceptionally long, having taken 20 years to move from 3 central banks to 90 central banks and the anticipated additional 15 years to cover the remaining 84.

    The report finds that the spread of RTGS systems is consistent with the standard S-curve prediction (initially take-on is low led by “innovators” after which the rate increases as “early adapters” introduce the system after which the rate of increase levels out).

    The chance that a country introduces RTGS in a given year increases significantly in the level of real GDP per capit

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    e in the move to RTGS adoption. Interlinked systems, such as TARGET (and also CLS to a lesser extent) have helped force the pace of change.

    The introduction period is exceptionally long, having taken 20 years to move from 3 central banks to 90 central banks and the anticipated additional 15 years to cover the remaining 84.

    The report finds that the spread of RTGS systems is consistent with the standard S-curve prediction (initially take-on is low led by “innovators” after which the rate increases as “early adapters” introduce the system after which the rate of increase levels out).

    The chance that a country introduces RTGS in a given year increases significantly in the level of real GDP per capit

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    spread of RTGS systems is consistent with the standard S-curve prediction (initially take-on is low led by “innovators” after which the rate increases as “early adapters” introduce the system after which the rate of increase levels out).

    The chance that a country introduces RTGS in a given year increases significantly in the level of real GDP per capita. Moreover, countries with a lower relative price of capital and countries whose major trading partners adopted RTGS are also more likely adopters.

    This suggests that, beyond market forces reflected by real GDP and capital costs, spillovers seem to play a significant role in the adoption of this financial innovation. These spillovers seem to be transferred mainly through trade relationships. To what extent the pattern of RTGS adoption reflects central banks’ technology decisions is uncertain and is suggested as a source of further research.

    Other factors that are seen as determining when a central bank will switch to RTGS are:

    •Price of information & communications technology – The lower the relative cost the more likely the central bank is to switch to RTGS.

    •Relative size of the central bank – the more central bank staff in relation to the overall population, the slower the rate of switching to RTGS.

    •Financial market development – the more sophisticated/ developed the faster the pace of RTGS implementation.

    •Membership of international organizations – Membership if bodies such as BIS, EU force the rate of RTGS adoption.

    •Bilateral trade – the level of international trade also appears to be a positive factor especially if trading partners have RTGS systems.

    From a systems developer's point of view there is still a lot of life left in the central bank RTGS market. Added to t

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