According to a top RBI official, the Reserve Bank of India (RBI) is implementing advanced analytics, artificial intelligence, and machine learning into supervisory data while taking the required precautions to obtain even more insight into the activities of monitored companies.
“These initiatives reflect the Reserve Bank’s commitment towards harnessing the power of technology and data-driven approaches to strengthen its supervision,” said Deputy Governor MK Jain at the 25th SEACEN-FSI Conference of the Directors of Supervision of Asia Pacific Economies held at Mumbai.
The RBI has made use of a variety of analytical methods to improve the efficacy of supervisory frameworks, according to Jain. Some of these are, according to Jain, an early warning system, stress testing models, vulnerability assessments, cyber key risk indicators, phishing and cyber reconnaissance exercises, targeted evaluations of compliance with KYC/AML standards, and data analytics.
“This evaluation should delve into the level of business growth projections, sustainability of earnings potential, extent of diversification, provisioning cover, and appropriate pricing mechanisms, etc,” Jain averred
“The recent bank failures in advanced economies have underscored the pressing need to address governance concerns head-on,” Jain added.
“Future-proofing by banks of their IT infrastructure becomes imperative, necessitating strategic investments in both capital and operational expenditure. As virtual work environments and cyber risks become more prevalent, effective IT governance takes on heightened significance,” Jain averred.
The RBI official added that supervisors should concentrate on the effectiveness of the assurance functions of risk management, compliance, and internal audit. “The assurance functions serve as a critical safeguard providing independent and objective assessment of the bank’s operations, risk management practices, and compliance with regulatory requirements,” Jain observed.
The RBI official added that supervisors should concentrate on the effectiveness of the assurance functions of risk management, compliance, and internal audit.
