Malaysia
Rafizi maintains Padu built all internally, data scientist only did staff training
In a statement today, Rafizi said he contacted the Department of Statistics Malaysia to verify this after hearing of the claim and found this to be incorrect. —Picture by Hari Anggara

KUALA LUMPUR, Jan 9 — Economy Minister Rafizi Ramli today rejected the claim that an external company was involved in developing the Central Database Hub (Padu) system, maintaining that the system was developed entirely in-house by civil servants.

During a recent interview with the BFM89.9 radio station, Accio Technologies chief executive officer Lau Cher Han claimed that his firm had played a role in developing Padu.

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In a statement today, Rafizi said he contacted the Department of Statistics Malaysia to verify this after hearing of the claim and found this to be incorrect.

"I can confirm that the allegations by Han Lau that his company was involved in the Padu development process are not true,” he said.

He said that neither Lau nor any personnel from his company was involved in developing Padu, including the collection or cleansing of information compiled for the central database.

Rafizi said Lau was invited by the Padu analytical team to conduct personnel training, based on his experience with data science, machine learning, and big data.

"I would like to emphasise once again that Padu was developed entirely by civil servants without the involvement of any third party,” he said.

On January 2, Prime Minister Datuk Seri Anwar Ibrahim officially launched Padu to pave the way towards a fairer distribution of targeted subsidies for Malaysians in need.

Padu — now considered the most comprehensive database established by the government to date — is a system containing individual and household profiles encompassing citizens and permanent residents in Malaysia.

The objective of Padu is to provide a safe, comprehensive and near real-time national main database that enables more accurate data analytics to be produced as well as for policy formulation and data-driven decision-making processes, besides enabling targeted policy implementation to balance the fiscal position.

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