Housing Analytics Solution

I geocoded more than a million addresses of property in Singapore so that it can visualized by users on the map at one glance.Users can filter by location, estimated budget, flat Type and room type and distance from flat to amenities. After they have filtered based on their constraints, they would have a shortlisted range of property they can look into. If they are interested, they can click on the hyperlink of the property to make the purchase

Users can explore ideal flats for raising children using the Ideality Prediction model. They can also understand the correlation of amenities distance with pricing.

Users can better understand the resale market’s general trend and use it to gauge the demand and supply trend of the resale flat that they have shortlisted the first 2 dashboards.

They can also understand the pricing trend across different flat types and towns. They can filter by different flat types and towns to funnel down to the flat type and town they want. They can also filter by date to view pricing, demand, and supply trends across different periods

This estimator is used to estimate the housing loan they are eligible for. Users will first enter the details of the property they have selected. Secondly, they would need to enter their salary.  Next based on the loan details, it will estimate the housing loan amount users are entitled to and the monthly installment user needs to pay. Next user can click on the red button to apply for an HDB loan eligibility letter. If the user is not eligible for the amount of loan that he requires, he can use money from housing grants or his CPF ordinary account to pay for the purchase. Else, he can opt for a cheaper property.