PropTech startup MilikiRumah has launched an AI-powered mortgage-readiness SaaS tool aimed at helping Indonesia’s real estate developers assess whether prospective buyers are likely to qualify for home loans. The Company says the tool can predict mortgage approval probability in under 10 seconds, compared with the three to four weeks typical in Indonesia’s banking sector.

The mortgage-readiness tool, delivered as software as a service (SaaS), is part of MilikiRumah’s broader strategy to build a rent-to-own ecosystem that targets Indonesia’s large underbanked population. Developers pay for the tool using credits based on consumer volume.

Rising demand from Indonesia’s property sector

MilikiRumah said more than 100 projects in Indonesia now use its SaaS stack, with expectations to exceed 1,000 projects by end-2026. The Company projects these projects represent a combined gross development value of IDR 4.5 trillion (about US$268 million) and could generate 1.2 million consumer leads.

The Company expects to expand regionally across Greater Asia following the Indonesia launch.

Co-founder and CEO Winston Lee said the tool is designed to support both developers and underbanked consumers. “Our SaaS offering is one of the Company’s diverse revenue streams while staying true to our mission of helping more people own a home,” he said.

AI-driven profiling for underbanked home seekers

The AI mortgage-readiness system screens credit risk profiles — including applicants with weak or limited credit histories — and identifies potential delinquency risks. MilikiRumah says it is building a repository of underbanked consumer leads expected to reach hundreds of thousands by 2026 and “millions” within three years.

Technology director Prasma Anindita said the system creates “a dynamic financial profile” mapping consumers’ readiness for traditional mortgages. Developers can also use the tool to direct non-qualifying buyers into MilikiRumah’s rent-to-own ecosystem, which allows users to build a payments track record.

The Company describes its AI stack as a multi-purpose assistant that uses big data to assess financial health, spending patterns and repayment capacity. MilikiRumah claims this helps sales teams accelerate home-buying workflows and improve conversion rates.

Growing interest among developers

Several Indonesian developers have publicly endorsed the product, citing improvements in sales efficiency and consumer responsiveness.

William Liusudarso of Easton Urban Capital said the tool helps his team “focus our efforts on the needs and conditions of prospects faster and more accurately.” Sakura Land, Winland Development and MAS Group also reported enhanced responsiveness to customers.

Rent-to-own model targets Indonesia’s housing gap

MilikiRumah positions its rent-to-own model as a complementary pathway for Indonesians rejected by banks due to non-fixed income streams or lack of credit history. Indonesia’s underbanked — including freelancers, gig workers and applicants with debt-to-income ratios above 50 per cent — often struggle to meet strict banking criteria.

The country faces a housing backlog of 9.9 million units, and about 60 per cent of the population are non-fixed income earners. Despite government programmes such as the Housing Financing Liquidity Facility, millions remain excluded from mortgage access.