BNM, DoSM collaborate on data sharing

by TMR / pic source: BNM

BANK Negara Malaysia (BNM) and the Department of Statistics Malaysia (DoSM) have signed a memorandum of understanding (MoU) to enhance collaboration on data sharing and other related matters. 

The MoU was signed by BNM governor Datuk Nor Shamsiah Mohd Yunus and DoSM chief statistician Datuk Seri Dr Mohd Uzir Mahidin. It expands the scope of prior collaboration by enhancing research and development, technical consultation and guidance, and training and capacity building. 

DoSM stated the MoU is anticipated to assist the development of subject matter knowledge in both agencies to address current and upcoming data demands, through the adoption of advanced statistical techniques, application of data science and analytics, and other inventive ways. 

“The MoU is expected to support the development of subject matter expertise in both agencies to meet current and emerging data needs, through the adoption of advanced statistical techniques, application of data science and analytics, and other innovative approaches,” the statement read. 

DoSM successfully organised the 62nd International Statistics Institute World Statistics Congress 2019 and the Regional MyStats Conference in Kuala Lumpur as the country’s official statistical agency on an international stage.

“MyStats Conference is organised annually, besides dissemination of data, ongoing exchange of expertise in the field of statistical and analytical compilation and human capital capacity building.”

In a separate statement, BNM said the new MoU enhances the inter-agency MoU previously signed in 2008 by further strengthening the scope of data sharing and utilisation for surveillance, analysis, and policy formulation. 

“The MoU also sets out new areas of partnership between both agencies, such as in research and development (R&D), technical consulting and advice, and training and capacity building,” the central bank said. 

This partnership is expected to support the development of subject matter expertise in both agencies to meet current and emerging data needs, through the adoption of advanced statistical techniques, application of data science and analytics, and other innovative approaches.