PADS Financial secures $3 million CAD in pre-seed funding, launches online mortgage platform

PADS looks to leverage AI and blockchain with its online mortgage servicing platform.

Montréal-based FinTech startup PADS Financial has secured $3 million CAD in pre-seed funding for its now-launched online mortgage platform.

The company said the funding was raised from angel investors it described as “leaders in the Québec real estate market,” but declined to disclose who specifically participated in the round. PADS said it is using the funding to work on artificial intelligence (AI) and blockchain offerings.

Launched in 2022 by co-founder and CTO Stephane Perez, PADS provides users with an online portal to apply for a home equity loan. Once they have applied, users can track their application status, get approved, and manage funds. In a statement to BetaKit, Perez said the loans issued through its platform on behalf of “pooled investors,” adding that the startup uses “internal resources” to underwrite the loans.

PADS said it aims to offer the industry’s fastest mortgage approval and funding times, and claims users can learn of the status of their application within 48 hours.

The startup currently only offers home equity loans, but plans to eventually support full property loans and mortgage refinancing.

A report by the Financial Consumer Agency of Canada found the percentage of Canadian mortgage holders who are able to keep up with their financial commitments with no problems has decreased by 22.2 percentage points since August 2020, stating only one in three mortgage holders now say they can meet their financial commitments without difficulty.

In response to this market, many startups come to market touting quick mortgage approvals made easier through online applications.

Pine came out of stealth in May 2022 saying it was looking to eliminate the lengthy process of mortgage application with its online platform. Earlier this month, Pine acquired fellow real estate-tech startup Properly in a move to expand beyond just mortgages.

Bigger players like Nesto and Questrade have also looked to cut down mortgage application time, boasting “quick” approvals on their digital lending platforms.

On top of the typical claims of speediness in the digital mortgage space, PADS is differentiating itself by promising the integration of AI and blockchain, two active sectors for investment, into its platform.

PADS said it is building AI and decision-making models to rate borrowers and provide instant property valuation. The startup also wants to leverage tokenization and blockchain to allow the platform and investors to sell or liquidate tokenized packages of its home loans instantly.

“When a borrower initiates a loan and accepts our terms (amount, rate and duration) – we will allow our pool of accredited investors to take a position on these loans based on their portfolio and risk exposure criteria,” Perez said in a statement to BetaKit. “PADS will always top up any loan that isn’t 100 percent-funded by investors to accelerate the funding process. With our tokenization initiatives we will be in a position to sell those loan positions post-disbursement to the borrower.”

PADS’ pre-seed funding round, which officially closed in July, was raised entirely on a simple agreement for future equity (SAFE) note. Perez told BetaKit the investors have committed an additional amount ranging from three times to 10 times their initial investment to fund the loans users may take out through PADS’ platform.

PADS said it is actively looking for additional sources of loan funding beyond its angel investors, and that those angel investors have joined its advisory board. The company plans to formalize a board of directors within the next three to six months.

Image source Unsplash. Photo by Tierra Mallorca.

Alex Riehl

Alex Riehl

Alex Riehl is a staff writer and newsletter curator at BetaKit with a Bachelor of Journalism from Carleton University. He's interested in tech, gaming, and sports. You can find out more about him at or @RiehlAlex99 on Twitter.

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