The Bangko Sentral ng Pilipinas (BSP) is studying a cryptocurrency dispute mechanism and also assessing how issuing its own digital currency will address gaps in the digitalization of the country’s payments and settlement system.
BSP director Melchor T. Plabasan for the Risk and Innovation Supervision Department said the central bank could set up a cryptocurrency dispute body to settle any grievances or disputes arising from the exchange of digital currency such as bitcoin, but this will require prudent review and consideration.
“We are studying that,” said Plabasan during the BSP’s weekly online “GBED Talks” led by Governor Benjamin E. Diokno. “The dispute mechanism especially for cryptocurrencies has to be agile and technology-driven as well. But we have to carefully study that,” he added.
The BSP has issued new rules on virtual asset service providers or VASPs earlier this year, allowing for more online platforms where Filipinos can purchase bitcoins and other virtual currencies.
Diokno said they are currently assessing how its own central bank digital currency (CBDC) – when they have it -- will play a role in the future and how they could effectively align it with the BSP’s three-year digital payment transformation roadmap. Factors that would convince the BSP to finally issue its own digital currency would depend on the growth of privately-issued digital currencies in the country, capacity building, and its readiness to manage risks.
“We continue to monitor developments in private digital currencies and CBDCs in both the domestic and global markets (and we) are currently preparing to undertake (and to take stock) of our existing payments and settlement system vis-à-vis our digitalization agenda to assess any gaps that may be addressed by a CBDC and its value proposition against an existing payment system,” said Diokno on Thursday.
“We are also keenly aware of the need for capacity building to increase our understanding of the CBDC through bilateral consultations, not only with other multilateral agencies but also with other central banks on their CBDC experience,” he added.
Diokno also said that ongoing experiments around the region such as China’s digital yuan, will lead to a better understanding of the technology and operational aspect of CBDC including its challenges.
“More importantly, the BSP decision to issue its own CBDCs will be aligned with BSP’s digital payments transformation roadmap,” said Diokno. BSP’s digitalization effort is intrinsically linked to its financial inclusion agenda.
“Our focus has always been the provision of an enabling policy environment for digitalization with adequate consumer protection safeguards. Going forward, the same principle will apply to CBDC developments,” he said, adding that “should the usage of virtual currencies become more pervasive, a recommendation in the literature is for central banks to create and implement its own central bank digital currency.” The BSP is not keen on its own CBDC yet and Diokno has already said that he does not see its issuance during his term which ends in 2023.
In the meantime, the BSP is assessing continuously the impact of digitalizatin on policy formulation, and its effect not only on monetary policy but in banking and payment systems.
Potential effects could be downward pressure on prices as firms, particularly retailers, capitalize on economies of scale offered by digitalization, said Diokno.
Another possible implication is that as “more and more economic transactions become digital, official statistics used for gauging overall economic health such as inflation, investment and employment may not be fully capturing the shift. As we all know, data quality is essential for surveillance and forecasting under our inflation targeting framework,” he added.
Diokno also said that since digitalization has also changed the dynamics between unemployment and inflation. “Central banks, such as the BSP, could certainly make use of the data being made accessible through the greater digitalization of the economy. As such, the BSP is expanding its suite of models to nowcast and forecast key macroeconomic variables, including machine-learning based models. Machine learning is an approach to forecasting that uses an algorithm.”
Diokno also cited what he called a “critical transformation” in the banking industry which is the “cloud-based” technology. There are now 30 financial institutions as of the end-first quarter this year that are already hosting their core banking solutions in the cloud.