By Mahadiya Hamza
COLOMBO– Sri Lanka is looking at artificial intelligence and machine learning to improve off-site supervision of banks as part of an overall drive to boost its techno-regulation framework and supervision, Central Bank Governor W. D. Lakshman said.
Delivering an annual policy roadmap for 2021, Lakshman said the Central Bank will explore the possibilities of implementation of Supervisory Technology (SupTech) and Supervisory Technology (RegTech) solutions to streamline the data-intensive offsite supervision function by harnessing the capabilities of artificial intelligence (AI) and machine learning.
“Adoption of such frameworks and supportive human resource policies will enable the Central Bank to keep pace with the rapidly evolving technology-driven financial innovations, so that financial system stability could be further strengthened in the period ahead,” he said.
SupTech technology uses artificial intelligence (AI) and machine learning to digitalize report and regulatory processes.
The techno-regulatory framework will encourage licensed banks to upgrade their information systems and technology platforms in line with global standards due to the COVID-19.
“The Central Bank will continue to adapt its supervisory approaches to suit the new normal. A regulatory framework for technology risk management and resilience of licensed banks will also be introduced,” Governor Lakshman said.
“This would prompt banks to upgrade and strengthen their information systems and technology platforms in line with the international standards and best practices,” he added.
With the COVID-19 pandemic forcing a need for crisis preparedness, these technologies will play a role in crisis preparedness in Sri Lanka.
“The COVID-19 pandemic underscored the need for crisis preparedness. Licensed banks will be required to implement recovery plans to strengthen crisis preparedness, enhancing their ability to respond effectively to adverse scenarios,” he said.
“Directions will be issued in due course, providing necessary guidelines.”
Suptech applications using machine learning can spot quality issues such as data gaps, inconsistencies, and errors, and automate data cleaning, consolidation, validation, and quality assurance.
In data analytics, Suptech solutions can reduce the burden of data crunching through automation, and enable more complex analyses, according to proponents.