UrbanAgents, a property platform that connects home sellers to a curated selection of agents in Singapore, has raised a $2 million seed round from FarSight Capital, APAC Realty and angel investors.
While we see no lack of firms claiming their model will evolve the proptech scene, UrbanAgents indeed brings something new to the table:
It uses AI to help home sellers project the value of their property, then allows them to choose between three different ways of paying their agent for a successful sale.
In the first result-based option, the property agent’s commission is pegged to the projected final sale price—in other words, customers pay the full 2% (the usual market rate) only if their agent manages to sell at the targeted value.
The commission rate lowers if the house is sold for less, or increases if it’s sold for more, to motivate agents to help their clients achieve the best price.
The other two methods allow users to pay based on their personal rating of satisfaction with the agent’s service, or stick to the traditional fixed fee.
Led by founder Michael Cho, the startup soft-launched its service just a few months ago, and it’s hard to say right now if their model will spark a revolution.
Vulcan Post reached out to Michael, who shared that he’s had “hundreds of enquiries and converted dozens into actual clients” with just “a handful” ending in actual transactions so far.
However, he acknowledged that these are “still very early days”, and now plans to put the new funds towards more R&D to further develop their AI and reach even greater accuracy.
A Tool Used By Gov’t Agencies, Banks, And Startups
Before UrbanAgents came to be, Michael previously set up UrbanZoom in late 2017, an AI-enabled research tool for property, which was then publicly launched in March 2018.
Formerly doing investment and finance at CapitaLand and an investment firm in Abu Dhabi, Michael is now focused on data at the core of his startup.
Under UrbanZoom, he and his team developed their proprietary tech Zoom Value, that predicts HDB and condominium valuations with a median error of less than 3%.
They later released API access, which saw Zoom Value being taken up by users like the Monetary Authority of Singapore (MAS), Urban Redevelopment Authority (URA), major banks DBS and OCBC, and other startups like MoneySmart, Ohmyhome, and SoReal.
Their AI tool is now supporting banks in areas such as mortgage lead generation flow, or helping fintech firms analyse their users’ financial standing.
But this wasn’t Michael’s intention for creating Zoom Value.
Prior to our launch, we were only thinking about the user case for end consumers. But we were pleasantly surprised with the amount of inbound interest from corporates and other startups on the AI that we’ve built.
Unexpectedly gaining government agencies and major banks as their clientele is no doubt a good way to validate the accuracy and usefulness of their tech.
And now it has helped them start to offer the customer-facing product that the company was built for in the first place.
Will UrbanAgents’ Solution Take Off With S’poreans?
Now on track with their main purpose of using auto-valuation to help customers, UrbanAgents wants to eliminate the ‘lemons problem’ home sellers face with a lack of trust for property agents due to unequal knowledge possessed.
Besides relying on AI for a highly accurate property valuation that is transparent to users, UrbanAgents also selects only the top 5% of Singapore agents using data.
Their belief is that data and AI will help home sellers make more informed decisions, while they still get to complete the process with a trustworthy “human expert or advisor”.
Among current clients, UrbanAgents said most are “overwhelmingly [choosing] the performance-based option over conventional fixed rate structure”, which nods to an interest to try this new model.
Michael also added that they’ve “already seen transactions where the UrbanAgent achieves [a sale price] above the ‘target rate’, and therefore [earns themselves] higher fees”.
It’s possible to see that Singaporeans could enjoy having more say and control over how much commission to pay, as many are often skeptical and want to avoid getting ripped off for shoddy work.
However, UrbanAgents is barely recognised by anyone yet and they will need to grow their clients to show their credibility.
We also wonder if using just the top 5% of agents will limit the business from scaling.
To answer this, Michael said having a small pool of agents is “by design” in order to ensure quality, and UrbanAgents will “give [their selected agents] a constant pipeline of clients”.
As the company’s money is in lead generation where they charge agents a fee only for successful transactions, their profitability is highly reliant on the agents’ performance too.
“If they do well, we do well,” Michael summed it up.
Even with the high standards set out, it doesn’t keep them 100% risk free when the business is largely in the hands of their agents, especially only a small pool of them. A lot is based on trust that agents are motivated to complete jobs well for their mutual benefit.
Jack Chua, CEO of UrbanAgent’s investor APAC Realty, said they “hope to create a win-win situation [where] homeowners are assured of great outcomes while agents can receive a healthy pipeline of clients to offer [their] professional consultancy services to”.
What do you think? Will UrbanAgents’ AI-driven, performance-based commission model work out for the long run, and will you try it?
Featured Image Credit: UrbanAgents/UrbanZoom
