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Digital Agriculture Services (DAS), a location intelligence and technology company, concluded in its ‘New Agri Lending Landscape’ report that the confluence of insurability, climate risk, non-financial production signals, borrowing complexity, and AI had left Australia’s traditional lending approaches inadequate to tackle issues in today’s $140 billion agri-lending market.
According to the report, lenders will increasingly need to look beyond traditional financial metrics and incorporate climate, operational, and asset-level data when assessing agricultural lending risk.
The report also noted the importance of the agricultural sector, which now spans 55 per cent of Australia’s landmass, with average farm capital values increasing almost sixfold over the past two decades.
“For a long time, agri-lending has relied on many of the same principles,” Sarah Gorman, co-founder and head of growth at DAS, said.
“What’s changed isn’t agriculture itself, it’s the amount of information now available about rural assets and how quickly the risks are evolving.
“Record lending, rising land values, climate variability, changing borrower profiles and better access to parcel-level intelligence are all converging at the same time. Collectively, they’re changing what ‘good lending’ looks like.”
Climate risk is now being priced into lending decisions
A key component of the report’s position was that historical data alone was no longer a reliable guide to climate risk and that viewing chronic changes throughout the lifetime of the loan (such as rain variability and shifting productivity) were superior indicators of risk as opposed to one-off weather events.
The Department of Climate Change, Energy, the Environment and Water said that Australia has warmed, on average, by 1.51 degrees Celsius from 1910 to 2023 and that extreme heat, intense rainfall, and drought across the south of the country have become more frequent.
Earlier in the year, extreme weather severely impacted farming businesses across Australia, brokers reported to Broker Daily.
The report said that rather than looking backwards, lenders would soon be assessing future climate conditions throughout the life of a loan.
“Chronic climate factors are already being priced into rural land values,” it said.
“High-rainfall regions now trade at materially higher premiums than lower rainfall equivalents – a spread that has widened in recent years and reflects the market’s own reading of long-term productive resilience.
“The trigger is no longer theoretical. Physical evidence requirements are now pushing lenders to evidence exposure at the asset level – where the risk actually exists.”
Insurability becomes a lending consideration
The DAS report also said that insurability has moved upstream in the lending process, shifting from a downstream compliance check to a leading indicator of whether an agricultural asset is financeable.
“If it is not insurable, it is not investible. In practical terms, this is no longer an insurance-only problem – it is a credit constraint,” it said.
DAS added that the increased salience of insurability is compounded by the underinsurance issue that can be apparent in rural areas.
According to the report, rural policies “routinely list just a fraction of the structures on the ground... leaving lenders with collateral gaps that they cannot see”.
The report said that at least one Australian bank now explicitly incorporates insurability as a physical climate risk driver within its portfolio disclosure.
“Insurability must be treated as a credit variable – assessed at origination, monitored across the life cycle and embedded in how risk is priced, not a condition checked and forgotten,” the report said.
Looking beyond the balance sheet
While financial statements remain an important part of agricultural lending, DAS said they no longer tell the full story of a farm’s long-term performance or resilience.
The report said the next generation of lending decisions would increasingly incorporate “non-financial lending signals” alongside traditional financial metrics to determine a property’s ability to generate income.
“Financial statements remain important, but they only tell part of the story,” Gorman said.
“Farm productivity, its resilience over multiple seasons, its carrying capacity, land condition and climate exposure all influence long-term repayment capacity. We call them non-financial lending signals and they’re measurable today.”
Technology is also playing its part.
The report noted that many of these measures are now observable at scale through geospatial data, remote sensing, and rural intelligence platforms, allowing lenders to assess characteristics that were previously difficult or impossible to quantify consistently.
“The advantage lies not in access to this data but in how consistently it is applied, within credit workflows and valuation assessments, not as an occasional data reference,” the report said.
Brokers take on a more complex role
Within this emerging context, the report highlighted the growing role brokers were playing in agricultural finance.
The report noted that the changing agri-lending environment had exposed a widening informational gap between loan origination and credit assessment.
DAS noted that residential deals were manageable at scale because collateral is standardised and comparable. In agri-lending, however, properties are often complex and highly variable, and the risk drivers discussed, such as productivity, climate exposure, water security, and land condition, are not visible in traditional statements or data feeds.
“Lenders who embed rural-specific data standards into their broker channels, and who support brokers with the right tools at origination, will build more consistent and more defensible loan books over time,” it said.
“The quality, industry knowledge and skill sets of the broker are very important as part of the lending approval process.”
AI will augment, not replace, decision-makers
With many of the data and decisioning tools now in market to the entire agri-lending ecosystem, DAS said that the added value will come in how tools are applied.
“AI does not replace experienced agri-lending judgement. It extends it, supports it and makes it scaleable,” it said.
“In valuation – this shift is already underway – AI-assisted comparables, satellite-derived land classification and automated data capture are reducing the time spent on manual property reconstruction and back-and-forth between valuers and relationship managers.”
Gorman said that the sector had reached a point where rural intelligence had become foundational for agri-financial services.
She said: “Agri lending has always been about understanding the land and the people managing it, what’s changing is our ability to see risk more clearly, more consistently and at a much finer level of detail. That’s the shift we have identified, and we believe it’s the next chapter of agricultural finance.”
[Related: Agriculture remains robust despite fuel and fertiliser shock]
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