PETALING JAYA: The government plans to use big data analytics and artificial intelligence (AI) to determine affordable housing needs based on locality, income levels and demand, says Nga Kor Ming.
The Housing and Local Government Minister said the RM300,000 ceiling for affordable homes was a “one-size-fits-all” approach that did not take into account differences in local housing needs.
Nga said, based on information from the National Property Information Centre (Napic) under the Finance Ministry, affordable housing in the Klang Valley could be priced at about RM500,000, compared with about RM300,000 in Kelantan.
“Imagine affordable housing in Kuala Krai, Kelantan, being priced the same as in Bukit Bintang, Kuala Lumpur.
“As such, our big data analytics will take into account income levels based on locality and region, as well as the type and location of the area.
“This will ensure that when developers build homes for consumers, they do so based on pricing that better reflects the reality on the ground,” he said at a press conference following the launch of the National Housing Policy 2026-2035 on Monday (Aug 10).
The approach is part of the National Housing Policy 2026-2035, a national strategic policy that will guide the housing sector development, including addressing rising living costs, changing demographics, mismatches between supply and demand, unsold homes and delayed, troubled and abandoned housing projects.
Supported by six focus areas, 17 strategies and 59 action plans, the policy also sets a target of providing one million affordable homes by 2035 through a more comprehensive, integrated and data-driven approach.
Nga also said the ministry had obtained approval from the Finance Ministry to introduce big data analytics from next year to address the mismatch between housing supply and demand.
He said Malaysia’s main housing problem was not a lack of supply, but a mismatch between the homes being built and what the market needed, contributing to the overhang of unsold properties.
“This will be introduced next year so that developers can refer to data on each locality, region and state before developing a project.
“It will also allow feasibility studies to be data-driven and enable developers to build homes that are actually needed by the market,” he said.
Nga said the approach would also be used to assess the government’s target of building one million affordable homes over 10 years under the 13MP.
On the reported decline in home ownership among the M40 group, Nga said this could be attributed partly to lifestyle choices and a preference among some people to rent.
Citing a survey by Rehda Institute, he said some graduates and young people were also choosing to rent rather than buy homes.
“24% of people surveyed were more than happy to rent as they did not want to be tied to bank loans and preferred to have more disposable income. It is a lifestyle and we respect that,” he said.
