Australia’s first National Climate Risk Assessment projects a staggering A$611 billion in property value losses by 2050, with 1.5 million Australians at risk from rising seas. This projection signals a systematic revaluation of the collateral base that secures billions in lending, driven by predictive climate scenarios that conventional credit assessment frameworks were never designed to incorporate.
Traditional credit methodologies have long relied on historical financial performance, tangible asset values, and backward-looking ratios. However, these metrics increasingly fail to capture the predictive factors – climate projections affecting collateral represent just one pressure among several parallel forces including digital transformation creating non-traditional revenue streams, and alternative behavioural data predicting default – that determine borrower viability and security adequacy.
The architecture of credit assessment is being reconstructed through parallel adaptations: institutional methodology incorporating future-oriented indicators, digital lenders validating alternative data sources, and securitisation markets recognising evolved collateral types. This transformation occurs amid both environmental and technological pressures, as the Reserve Bank of Australia (RBA) has observed, rapid digitalisation has increased operational risks in the financial system.
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What Traditional Models Miss
Conventional credit evaluation focuses on historical financial performance, typically analysing three to five years of audited financials and tax returns. These methods rely on tangible asset security valued through backward-looking comparable sales or depreciation schedules for loan-to-value calculations. Standardised ratios, such as debt-service coverage and interest cover, are based on past results, while credit bureau scores reflect historical payment behaviour.
Emerging realities challenge these traditional models. Digital businesses can see revenue streams pivot or vanish within quarters, outside the historical data windows. Supply chains disrupted by climate events aren’t forecasted in financial statements. Platform-dependent businesses face viability changes overnight due to algorithm adjustments. Gig economy and digital-native workers have income streams that don’t fit conventional employment verification and tax documentation patterns.
The fundamental epistemological problem is that credit frameworks built to answer ‘What happened?’ are now being asked to answer ‘What will happen?’ in an economy where the past is becoming a weaker predictor of the future. It’s like trying to predict traffic ahead using only your rear-view mirror. As noted above, rapid digital transformation has increased operational risks, highlighting the need for a shift from backward-looking to forward-looking assessments to capture opportunities and identify risks that conventional metrics miss entirely.
The imperative is clear: bridging the gap between what traditional models measure and what predicts creditworthiness and security adequacy requires a fundamental rebuilding of assessment frameworks. Incremental adjustments to existing ratios and data sources won’t cut it.
Nowhere does that rebuilding feel more urgent than when property – long the bedrock of collateral – starts to lose its value overnight.
Property Security Challenges
Climate risk presents a materialised assessment challenge. Australia’s first National Climate Risk Assessment highlights substantial projected property value losses and significant population exposure due to rising seas by 2050, with A$40 billion in disaster recovery costs. Property valuations based on historical comparable sales fail to incorporate predictive climate impacts on insurability, saleability, and physical integrity.
Denis Nelthorpe, an Australian community lawyer, observes: ‘There is no doubt an increasing proportion of rural and regional Australia is becoming uninsurable under the current system. There’s lots of people being told that we won’t cover you for flood; if you want flood cover, it’s going to be $20,000.’ When property insurance becomes prohibitively expensive or unavailable, traditional loan-to-value security calculations become meaningless. It’s the perfect circular trap – security that becomes most insecure exactly when you need it to be secure. Conventional credit frameworks lack methodology for incorporating predictive climate assessments into collateral valuations, showing how future-oriented risk revalues backward-looking security assumptions.
Dr. Karl Mallon, chief executive of Climate Valuation, extends this implication: ‘That means that someone who’s got a property in a high-risk zone is going to be unable to sell that property. We’ll see communities where increasingly either people can’t sell a property, or they have to reduce the price so much that you can buy it without a mortgage.’ When collateral becomes unsellable at prices sufficient to satisfy debt, security adequacy fails catastrophically. This risk materialises through predictive climate projections and insurance market responses, not through backward-looking comparable sales data.
Australia’s 2035 emissions reduction target (62–70% reduction against 2005 levels) creates transition risks and opportunities across sectors – stranded assets in carbon-intensive industries, retooling costs for manufacturers, new revenue opportunities in renewable energy. Yet traditional credit assessment focuses on historical financial performance and existing asset bases, not prospective adaptation capacity or competitive positioning in a decarbonising economy.
Yet alongside climate risks, lenders also face the challenge of matching institutional rigour to swiftly changing business dynamics.
Adapting to Business Realities
Institutional lenders face the challenge of adapting traditional frameworks to incorporate predictive indicators while maintaining prudential standards. This requires practitioners who can apply institutional rigour whilst incorporating business-specific dynamics and future-oriented operational metrics rather than relying solely on standardised backward-looking ratios.
Martin Iglesias at Highfield Private provides an example of this approach. As a Credit Analyst since January, he brings over two decades of experience in corporate and institutional banking from ANZ and Commonwealth Bank of Australia, specialising in cash-flow funding and structured finance for mid-market corporates. His methodology addresses this challenge by applying cash-flow modelling, covenant design, and security structuring that aligns facilities with business dynamics rather than generic standardised ratios.
Iglesias supported an online retailer’s expansion from a medium-sized enterprise to a A$250 million operation by applying predictive cash-flow analyses and inventory/receivables controls to calibrate working-capital lines and term funding, negotiating facility terms with lenders to match seasonal cash cycles. Look, this isn’t just tweaking interest rates – it’s fundamentally rethinking how facility structures match cash generation patterns rather than historical averages. He also structured over A$30 million in lending facilities for a real estate agency’s portfolio growth by assembling term debt and working-capital lines against rental roll and property security, setting reporting undertakings around rent roll performance alongside loan-to-value and interest cover ratios to provide future-oriented operational indicators of borrower viability.
Iglesias’s methodology shows that rebuilding credit assessment frameworks doesn’t require abandoning institutional rigour but adapting methodology to incorporate predictive indicators matched to business dynamics rather than relying exclusively on historical performance metrics.
And in some cases, the single best forecast isn’t in the balance sheet at all but in real-time borrower behaviour.
Behaviour as a Predictor
Digital-native borrowers present creditworthiness patterns that backward-looking financial data doesn’t adequately capture. These borrowers often have income streams, transaction behaviours, and financial management patterns that fall outside conventional employment verification and historical credit scoring frameworks.
Digital lenders testing alternative data sources and behavioural indicators represent one approach to this challenge. Wisr Limited, Australia’s first Australian Securities Exchange-listed digital lender, under the leadership of founder Anthony Nantes (who died in April 2025), provided an example of how this was addressed through integrating predictive indicators and alternative data sources in credit evaluation. The company focused on financial wellness and fintech innovations, expanding its financial wellness ecosystem through strategic partnerships and launching the Wisr app, which quickly gained traction. This approach achieved a 300% increase in loan origination year-on-year by accessing transaction behaviour patterns, real-time income monitoring, savings trajectory data, and financial goal achievement indicators. The alternative data was working – creditworthy borrowers were getting approved whom traditional frameworks would’ve missed entirely. But explosive growth metrics and sustainable governance turned out to be different beasts entirely.
Nantes was dismissed in August 2023 over performance and governance concerns following a workplace affair. The trajectory revealed both validation and caution: alternative data sources and behavioural indicators successfully identified creditworthy borrowers conventional frameworks would miss, but scaling such approaches requires governance discipline alongside technological innovation. The data worked; the execution stumbled.
Shifting Collateral Standards
While predictive cash-flow modelling and alternative data sources represent reconstruction of assessment methodologies, the foundations of credit are also shifting in what constitutes acceptable collateral and adequate security – methodological adaptation and collateral evolution are parallel dimensions of the same fundamental rebuilding.
Standard & Poor’s Global’s September assignment of an AAA rating to CNH Industrial Capital Australia Receivables Trust Series 2025-1 demonstrates this shift. The class A asset-backed securities totalling A$358 million are backed by chattel mortgage and finance lease contracts secured by agricultural and construction equipment. This marks the 16th term-note backed by CNH Industrial Capital’s collateral, establishing a track record showing that alternative collateral types have achieved mainstream acceptance through demonstrated performance and rigorous structuring.
That stands in stark contrast with the climate-driven revaluation of traditional property security: while equipment-backed lending receives AAA ratings through predictive cash-flow analysis, property-backed lending faces systematic revaluation as climate projections affect insurability and saleability. The traditional hierarchy of collateral security is being inverted based on which assets can be evaluated through operational cash generation versus those vulnerable to future-oriented environmental projections. This collateral transformation reflects the same underlying shift driving methodological changes – the need to assess what will generate value rather than what has generated value.
Transition Finance and Coordination
Australia’s 2035 emissions reduction target creates immediate transition finance demands requiring approximately 33 million tonnes CO2-e per year reduction to reach the 70% target from current 440.2 million tonnes annual emissions. Businesses need retooling for lower emissions, supply chain adaptation, green technology adoption, and competitive repositioning in a decarbonising economy.
Evaluating whether a manufacturer’s current profitability will survive carbon pricing or whether its adaptation strategy is credible requires predictive scenario stress-testing that traditional debt-service coverage ratios don’t provide. Conventional credit assessment focused on historical financial performance cannot adequately evaluate transition viability or competitive positioning in transformed market conditions.
The RBA’s observation that operational risks from rapid digital transformation require enhanced coordination among regulators establishes that rebuilding credit assessment foundations similarly requires coordination between traditional prudential standards and innovative approaches. However, coordination remains imperfect, with regulatory frameworks adapting more slowly than market practices evolve.
Measuring Future Outcomes
Australia’s National Climate Risk Assessment projecting substantial property value losses by mid-century isn’t merely an environmental warning – it’s notification that the collateral base securing billions in lending is being systematically revalued by predictive climate scenarios conventional frameworks weren’t designed to measure.
Credit assessment is moving from measuring what happened (historical financials) to projecting what will happen (cash-flow scenarios under stress conditions). This shift requires not merely new data sources but new epistemological frameworks for what constitutes evidence of creditworthiness.
Practitioners are rebuilding assessment frameworks on terrain that continues shifting. The structures being built will determine not merely who can access credit but what constitutes creditworthy enterprise in an economy where old certainties no longer hold.
That A$611 billion revaluation figure isn’t just a number – it’s the price tag on learning that historical patterns alone can’t guarantee future outcomes anymore. Which, for an industry built on predicting the future, is either terrifying or liberating, depending on how quickly you adapt.