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Home/Real Estate/MORTGAGE APPLICATION VOLUME

Canadas banks treat collective savings as suspicious. For thousands of newcomers, that blocks the path to homeownership.

TR

Taylor Ravenscroft

mortgage application volume · Apr 15, 2026

Canadas banks treat collective savings as suspicious. For thousands of newcomers, that blocks the path to homeownership.

Source: DojiDoji Data Terminal

Thousands of racialized newcomers down payments are being rejected not because they lack funds, but because they saved collectively. Banks routinely treat lump-sum deposits from mutual-aid groups like equb, hagbad and susu as suspicious—even when the money is saved steadily over years. The result: mortgage applications denied, applicants flagged for anti-money laundering reviews, and homeownership out of reach.

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Borrower abandonment during the application process decreases when lenders reduce the friction of fragmented application journeys. These journeys become faster and less fragmented as lenders process information more efficiently. This efficiency is driven by the reduction of manual review for routine administrative tasks. Lenders achieve this by integrating AI-powered systems for document processing that automatically verify whether documents are correct, confirm they cover the required time period, and identify inconsistencies.

These savings practices are widespread across African diaspora communities in Canada. Ethiopian Canadians use equb, a rotating savings and credit association, to build capital for education, business and housing. Somali Canadians organize hagbad. Ghanaians use susu. Each operates on the same principle: members contribute regularly, take turns receiving the pooled sum and rely on trust, not paperwork. One Ottawa woman, a single mother who arrived as an asylum-seeker with no family, used an equb to save for rent, groceries, school supplies, Christmas presents—and eventually, a home. That woman was the authors mother.

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But equb payouts do not come with bank statements or gift letters. When a participant deposits $20,000 from a rotating savings group, lenders often demand proof the money is not illicit. Yet banks routinely accept family gift letters for down payments—unverified, unsecured and equally informal. The difference is recognition: one is legible within the financial system, the other is not.

Related Brief7h ago
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Parental Co-signing Boosts First-Time Buyer Purchasing Power by 72%

First-time homebuyers in Canada are purchasing homes worth $787,000 on average when a parent co-signs their mortgage, compared to $458,000 without a co-signer. This 72 per cent increase in purchasing power allows adult children to take on larger mortgages than they could afford on their own. The Bank of Canada reports that the share of first-time buyer mortgages co-signed by parents rose from 4 per cent in 2004 to 11 per cent in 2025. The practice is most prevalent in expensive markets like Toronto and Vancouver, and among buyers who are younger, have lower credit scores, and lower incomes. In 74 per cent of cases, adult children would not have qualified for mortgages without parental assistance. This financial linkage leaves both the first-time buyer and the parents more vulnerable to a sharp deterioration in either party's financial situation.

The Office of the Superintendent of Financial Institutions does not require federally regulated lenders to accept documented participation in equb or similar as a valid down payment source. The Canada Mortgage and Housing Corp. does not offer standardized verification for these savings. Lenders have no clear guidance on what constitutes acceptable evidence. As a result, collective savings remain financially invisible.

Related Brief18h ago
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FHA spousal debt rule creates a debt-to-income imbalance for borrowers in community property states

Married homebuyers in community property states find their purchasing power reduced and some families are pushed out of the market because of a mortgage underwriting rule. The Federal Housing Administration (FHA) requires lenders to count a non-borrowing spouse’s debts when processing mortgage applications in Arizona, California, Idaho, Louisiana, Nevada, New Mexico, Texas, Washington, and Wisconsin. Lenders are prohibited from counting that same spouse’s income unless the spouse is an official co-borrower. This inflates a borrower’s debt load on paper, which increases their debt-to-income ratio. The National Association of Real Estate Brokers (NAREB) argues this creates a punitive double standard. Black borrowers in community property states face higher loan denial rates and receive smaller approved mortgage amounts than their White counterparts.

The Financial Consumer Agency of Canada does not track complaints about loan denials tied to rotating savings, nor do banks disclose whether their assessment methods disproportionately affect racialized communities. Settlement programs funded by Immigration, Refugees and Citizenship Canada do not routinely include mortgage readiness training tailored to mutual-aid savers.

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AI and Property Data Are Exposing Hidden Links Between PPP Fraud and Inflated Home Values

Home valuations in some Texas markets rose by 25% without renovations or market justification — a surge tied not to demand, but to Paycheck Protection Program (PPP) loan fraud. Researchers from the University of Texas found that fraudulent PPP claims artificially inflated property prices in cities like Chicago, New Orleans, and Atlanta, where fraud rates approached 30%. The mechanism is direct: illicit funds entered real estate, distorting valuations and triggering ripple effects across lending and tax enforcement. Automated valuation models (AVMs), which rely on tax records, sales data, and mathematical modeling, now serve as frontline detectors, flagging outliers that deviate from historical trends or neighborhood comparables. When an appraisal shows a sudden spike in value with no structural improvements, AI flags it for investigation. So do discrepancies in square footage, room counts, or the use of distant or dissimilar comparables — all signs of potential collusion between borrowers and appraisers. Lenders layer these valuation signals with ownership history, income verification, and geospatial data to uncover broader fraud patterns. The National Mortgage Application Fraud Risk Index shows undisclosed real estate activity — including hidden debts, occupancy misrepresentation, and unreported credit events — rose 9.1% year-over-year. AI systems detect when a property listed for rent contradicts an owner-occupancy claim, or when tax mailing addresses diverge from declared residences. These mismatches are not just underwriting risks. They are also evidence. The IRS and Department of Justice now deploy AI to trace illicit flows through real estate. Under the Centralized Partnership Audit Regime (CPAR), the IRS targets large partnerships and real estate firms with over $10 million in assets, using machine learning to scrutinize 1031 exchanges, depreciation claims, and “real estate professional” designations. The agency cross-references reported income against third-party property records, hunting for high-value acquisitions that don’t align with tax filings. The DOJ uses the Consolidated Asset Tracking System (CATS) to track seized properties and identify ownership structures designed to hide illicit funds. By analyzing non-public rental data, geolocation records, and rapid financial transfers, AI exposes networks used for money laundering — where overvalued homes aren’t just a fraud tactic, but a laundering vehicle. The consequence is clear: property data and AI are no longer just risk management tools. They are forensic instruments reshaping how financial and legal systems trace the movement of dirty money.

One change would end the arbitrary rejection: OSFI issuing national guidance that rotating savings, when documented, are a legitimate source of down payment funds. CMHC creating a verification framework—certification templates, savings pattern guidelines, acceptable evidence standards—would make the system work. Without it, thousands of consistent savers remain locked out.

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Rely Mortgage Rates Drop by Up to 0.54 Percentage Points

A one-year fixed mortgage rate from Rely is now 3.68%, a decrease of 0.54%. A two-year fixed rate is 3.80%, down 0.54%. A five-year fixed rate is 4.73%, down 0.49%. These changes follow a confirmation from Rely, part of OneSavings Bank, that it has reduced rates across its range, including limited edition products.

mortgage application volume

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