Brazil’s financial regulator launches regulatory blockchain

The Banco Central do Brasil (BC) recently declared the launching of a new blockchain platform called PIER (Platform for Information Integration of Regulatory Entities). It allows quick exchange of data between regulatory authorities relating to financial institutions.

Until now, the solution is under process with the Central Bank, Brazil’s Authorities the Comissão de Valores Mobiliários (CVM), and the Private Insurance Superintendence (SUSEP). The National Superintendency of Complementary Welfare (PREVIC), the pension regulator, is initiating tests to use the platform. 

The shared information includes sanctions against financial institutions or their employees, registration status, financial performance, and details about the employees of regulated firms and key stakeholders. In the future, there are chances of having information from the judiciary, trade boards or international financial bodies.

The financial institutions’ queries can take about a month to process. Regulatory authorities communicate with each other through physical mail and data has to be accessed from other sources to reply back. By enabling automation, the central bank stated PIER could substantially reduce this time. This means the regulators would be able to quickly respond to queries from institutions and companies.

“This makes it possible to drastically reduce the time period for assessing requirements and relieves participants from attending to requests for information that previously required manual procedures,” said Daniel Bichuette, Deputy Head of the BC’s Financial System Organization Department.

Additionally, the blockchain traces all queries made.

“PIER makes the access to information of participants regulated by these institutions (regulators) broader, safer and more direct, strengthening and reducing the bureaucracy of the tasks of supervision, investigation, and investigation of irregularities in the sphere of each one,” said Frederico Shu, Analyst of the Development Center in Data Science at CVM.