New FNA research finds retail CBDCs require a combination of attractive design options, stimulus policies and limits to foster adoption. 


New research, Simulating the Adoption of a retail CBDC, from FNAer’s Carlos León, José Moreno, and Kimmo Soramäki used an agent-based model to build a digital twin of Spain’s retail payment ecosystem to test various design options on adoption rates for a retail central bank digital currency (rCBDC).  


Using a Digital Twin of the Spanish payments ecosystem, León, Moreno, and Soramäki ran hypothetical scenarios, drawing on publicly available data on attitudes towards payment instruments to simulate adoption rates under certain conditions. 


The predominant finding from the paper revealed that introducing an rCBDC without attractive design options and stimulus for consumers and merchants would result in low and slow adoption rates. The analysis overlaps with the low adoption rates of CBDCs in Nigeria, The Bahamas, Jamaica and the People’s Republic of China. 


On the other hand, reverse waterfall functionality (the ability to make payments using funds from another payment instrument when an rCBDC balance is insufficient) and positive remuneration helped foster adoption. In contrast, top-up and balance limits could curb adoption rates while mitigating possible disintermediation generated by the issuance of a CBDC. 


Overall, the findings suggest that a combination of attractive design options, stimulus policies and specific limits to holding rCBDC could offer a sweet spot for adoption – one high enough to allow for the effective use of an rCBDC but low enough not to threaten the stability of the financial system. 


By implementing an agent-based learning-by-simulation approach, the complex interdependence between the initial conditions of the retail payment ecosystem and the rCBDC design options can be modelled and studied before incurring the costs and risks of a learning-by-doing approach.” Carlos León, the paper’s co-author and Director of FMIs and Digital Currency Solutions at FNA, commented. 


A Digital Twin – a replica of a payment or settlement system – allows central banks to safely test various options, including CBDC design, policies and wallet limits that could encourage the public to use a CBDC. Learning through simulation. CBDC stakeholders could iterate and test design options to find the optimal solution that supports the goals of a Central Bank, prove attractive to consumers and merchants alike and ensure the stability of the financial system. 


“Adopting a learning-by-simulating approach would enable central banks and other stakeholders to sufficiently and seriously iterate and test, with the simulation evolving into a reliable plan for the design, pilot, roll-out, and adoption of rCBDCs.” Carlos continues. 


The working paper features in Tilburg University’s Discussion Paper series, with Jose Moreno, Senior Data Scientist at FNA, presenting the paper at Bank of Finland’s 21st Simulator Seminar on the 31st of August. 

If you would like further information on FNA’s Digital Twin Solutions for rCBDC and how it aids in studying the adoption of a CBDC, visit our website or get in touch with a member of the team



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