RegTech and SupTech in Central Banks

In a recent sponsored report published by Central Banking, regulatory reporting firm Regnology explores how supervisors from Brazil, Qatar, Georgia, and Peru are using regulatory and supervisory technologies (RegTech and SupTech) to identify emerging financial risks and modernize stress-testing.

The Central Bank of Brazil (BCB) monitors bank balance sheets daily, using machine learning to filter anomalies that could indicate cyberattacks, money laundering, or fraud. It also uses AI to scan financial news for alerts involving FinTechs. BCB’s Aristides Andrade Cavalcante Neto noted that the central bank’s systems “already signal which banks are most exposed” to interest rate and exchange rate volatility.

Peru's Superintendency of Banking, Insurance, and Private Pension Funds (SBS) has automated stress-testing across baseline, stress, and severe-stress scenarios, reducing operational time and freeing analysts to focus on validation. Georgia’s National Bank is exploring machine learning models to detect non-linear relationships between risk factors. Qatar Financial Centre Regulatory Authority (QFCRA) emphasizes international collaboration, with Ewald Müller arguing that “data accuracy is very important, but continuous improvement and monitoring relevance, through collaboration, is just as critical.”

A shared theme across all four institutions is the push toward real-time data processing. Perttu Korhonen of the QFCRA warned that fragmented systems “kill efficiency,” arguing that supervisors must become digital-first or risk becoming “a barrier to entry” for new kinds of institutions.