Context: A small policy change with outsized ripple effects

ANZ’s decision to tighten credit requirements for residential mortgages where a company or trust is the borrower lands at the intersection of three forces. First, a cooling credit growth cycle: ANZ’s own analysis, drawing on Fitch’s Mortgage Market Index for Australia, has highlighted that slower economic momentum typically maps to slower lending growth. Second, regulatory discipline: prudential settings continue to emphasise robust serviceability and risk oversight in mortgage portfolios, and anti-money laundering requirements demand deeper visibility into beneficial ownership structures. Third, competitive signals: Commonwealth Bank tightened company and trust lending policies in late 2025, and brokers report a steady tightening in verification and serviceability expectations across the majors.

Company- and trust-borrowed home loans are a niche by volume but heavy on complexity. They involve layered legal structures, director guarantees, cash-flow variability (especially for SMEs and professional services operators), and heightened know-your-customer and anti-money laundering checks. When majors reprice risk in this segment, capital allocation and process friction shift in ways that affect business borrowers’ timelines, costs, and borrowing capacity.

Decision: Risk-based pricing and portfolio hygiene over raw volume

Viewed through a risk-return lens, this is a portfolio hygiene move. The working hypothesis: when growth slows and credit costs normalise, banks reweight towards segments with clearer risk signals and lower operational drag. Company-borrowed mortgages often require additional due diligence (trust deeds, constitutions, shareholder agreements, beneficial ownership maps) and can display cash flows less predictable than PAYG income. For a major with a large broker channel, small increases in exception rates, rework, and time to decision can materially raise unit costs. Tightening here improves underwriting consistency, reduces variance in recoveries, and reins in tail risk—especially where security cross-collateralisation with business assets complicates enforcement.

The strategy is also defensive. As the housing cycle matures and serviceability buffers remain high (Australian lenders commonly assess borrowers with a three-percentage-point interest rate buffer), reshaping exposure to more complex borrowers keeps regulatory dialogue straightforward and protects capital efficiency.

Implementation: The policy levers that move the dial

While ANZ has not publicly disclosed every knob turned, industry practice and broker communications point to several common levers:

• Serviceability tightening: Higher shading on company income, stricter add-backs, and lower acceptance of volatile revenue lines. For SMEs, historical rather than forward projections tend to dominate, with conservative treatment of director distributions.
• Security and LVR discipline: Lower maximum loan-to-value ratios for company/trust borrowers than for comparable individual borrowers, and closer scrutiny of multiple security properties and cross-collateralisation.
• Director guarantees and recourse clarity: Broader use and tighter wording of guarantees to ensure enforceability and reduce recovery uncertainty.
• Beneficial ownership and AML/CTF depth: Enhanced verification of ultimate beneficial owners and related-party transactions, in line with AUSTRAC expectations, adding documentation overhead but reducing regulatory exposure.
• Documentation and audit trails: Requirements for executed trust deeds, company constitutions, resolutions, and evidence of borrowing powers; any gaps often push deals into manual underwriting queues.

Technical deep dive: Expect greater use of data-driven underwriting. Lenders increasingly deploy automated bank-statement analytics, cash-flow modelling, and Consumer Data Right (open banking) feeds to cross-check SME income stability and related-party flows. Where AI/ML models are used to triage or detect anomalies, explainability controls are critical—consistent with Australia’s AI ethics principles and regulator expectations around transparency. The near-term payoff is lower rework rates and faster exception handling; the long-term prize is more accurate probability-of-default estimates for complex borrowers.

Results: Early signals, measurable impacts, and what to track

Because the policy change is new, hard outcome data will lag. But there are reliable leading indicators and metrics executives should watch:

• Approval and conversion rates: Brokers typically see an initial dip in approvals for company/trust borrowers as policies re-cut pipelines. Watch for conversion stabilising after documentation practices adapt.
• Time to yes: Expect longer decisioning where structures are complex; digital verification and complete packs can claw back days. A practical KPI for lenders is reducing manual referrals as a share of files.
• Borrowing capacity: Tighter income shading and serviceability buffers often shave borrowing power. For SMEs with variable income, it is common to see materially lower assessed capacity versus PAYG borrowers under the same buffer settings.
• Channel shift to non-banks: When majors tighten, non-bank lenders and specialist financiers tend to pick up overflow, albeit at higher rates. The Reserve Bank’s data historically show non-ADI housing credit share in the mid-single digits; watch for incremental gains here if major-bank appetite stays tight.
• Competitive response: With CBA already tightening in late 2025 and ANZ moving now, monitor NAB and Westpac policy bulletins for alignment or selective loosening to win share in narrow niches (e.g., professional practices with strong retained earnings).

For ANZ specifically, the bank’s global footprint (29 markets, per its 2024 reporting) means policy coherence and operational efficiency matter at meaningful scale. Tighter criteria in a complex segment can lift underwriting productivity and reduce loss volatility, even if it trims near-term growth in that niche.

Business impact: Who gains, who pays

SME directors and property investors using corporate structures face more documentation, longer timelines, and potentially higher equity contributions. Major banks gain cleaner portfolios and lower process costs over time. Non-banks and specialist lenders may win volume at higher margins. Brokers become even more central, optimising lender selection and pack quality to navigate tighter rules. In aggregate, the bottom line is a modest rise in cost of capital for complex borrowers and a small but persistent redistribution of mortgage flows towards lenders with higher risk tolerance.

Market trends and future outlook

This is unlikely to be a one-off. We’re seeing a structural preference for simplicity in mainstream mortgage books while complexity migrates to specialist credit. Expect:

• Continued emphasis on serviceability buffers around three percentage points until rate cycles convincingly turn and arrears stabilise.
• More data-driven underwriting across the majors, blending open banking, bank-statement analytics, and anomaly detection to reduce manual touch and tighten fraud controls.
• Selective risk re-opening if funding costs ease and arrears remain contained—potentially via tightly defined professional segments (e.g., medical, legal) with consistent earnings patterns.
• Regulator focus on beneficial ownership transparency and AML/CTF execution, reinforcing the need for deeper KYC across company and trust borrowers.

Lessons and actionable steps

For CFOs and SME directors:

• Assume tighter shading of company income and prepare for a three-percentage-point serviceability buffer; build capacity scenarios at base, +3%, and +4% rates.
• Pre-empt documentation friction: keep trust deeds, constitutions, resolutions, and director guarantees ready; ensure beneficial ownership charts are current.
• Consider hybrid structures: personal borrowing with guarantees versus company borrowing, balancing tax, asset protection, and borrowing capacity.
• Shop funding channels: compare majors, regionals, and specialist lenders; model total cost over five years, not just the headline rate.

For lenders:

• Invest in explainable AI underwriting to cut rework and manual referrals on complex files; measure lift via reduced time-to-yes and lower exceptions per file.
• Tighten but don’t blunt: create clear, published pathways for strong SME borrowers (multi-year profitability, low gearing) to avoid unnecessary leakage to non-banks.
• Use portfolio analytics to track loss volatility and capital drag by borrower type; adjust risk appetite quarterly, not annually, in a volatile rate environment.

For brokers:

• Front-load evidence: tax returns, BAS summaries, bank-statement analytics, and trust documentation. Incomplete packs will blow out timelines under tightened criteria.
• Map lender appetite in real time: policy matrices should be living documents; update after every credit decision to avoid dead ends.

Bottom line: ANZ’s policy shift fits a broader major-bank pattern—prioritising clean risk over marginal volume. Early movers gain underwriting efficiency and regulatory clarity; late movers risk absorbing the industry’s complexity at subpar pricing. For borrowers, preparation and lender selection now matter as much as the property itself.