For years, biodiversity has largely been viewed through an environmental lens. But for financial institutions, it's increasingly becoming a business issue.
When ecosystems deteriorate, businesses that depend on them become more vulnerable. Crop yields can decline. Revenue becomes less predictable. And for banks and lenders, that means financial risk may be changing in ways traditional models don't fully capture.
The challenge is that biodiversity has historically been difficult to quantify in financial terms.
That may be starting to change.
During the SAS Hackathon, Team Green Finance Lantern set out to explore whether analytics and AI could help connect biodiversity loss to corporate credit risk. Their proof of concept focused on a surprisingly influential part of the ecosystem: pollinators.
The project demonstrated how environmental data can move beyond sustainability reporting and become part of everyday financial decision-making.
See biodiversity analytics in action
See how Team Green Finance Lantern used SAS Viya to connect biodiversity data to financial risk in the full SAS Hackathon project.
Why pollinators matter to lenders
Pollinators are essential to many agricultural crops, including apples, berries, melons and other high-value produce. When pollinator populations decline, crop yields can suffer.
For farmers, lower yields can reduce revenue. For lenders, that can translate into higher credit risk.
Team Green Finance Lantern asked a straightforward question:
Can biodiversity become a measurable input into lending decisions?
Instead of treating biodiversity as an abstract sustainability concept, the team explored whether changes in pollinator habitat could help predict financial outcomes for individual farms.
Turning environmental data into financial insight
To answer that question, the team combined several sources of information.
They mapped agricultural parcels across France's Provence-Alpes-Côte d'Azur region, incorporated ecological projections showing how pollinator habitats could change over time and applied scientific research on crop dependence on pollination.
Using SAS® Data Maker, the team then generated a synthetic portfolio of 3,000 farmers, allowing them to model realistic financial outcomes without exposing sensitive customer information.
The result was a framework that connected ecological change with business performance.
As pollinator habitat declined, projected crop yields fell for farms growing pollinator-dependent crops. Lower yields reduced projected profitability, which increased estimated credit risk.
Rather than viewing biodiversity as an external sustainability concern, Team Green Finance Lantern demonstrated how it could become a measurable financial variable.
From analytics to lending decisions
Understanding risk is only valuable if organizations can act on it.
Using SAS® Viya®, Team Green Finance Lantern built an interactive dashboard that combined biodiversity data, financial metrics and AI-powered recommendations into a single view.
Users could explore individual farms, compare current and future pollinator habitat, review projected financial impacts and evaluate lending recommendations based on changing levels of environmental risk.
Instead of producing another sustainability report, the prototype showed how analytics could help financial institutions make more informed lending decisions while considering environmental resilience alongside traditional financial measures.
Biodiversity risk isn't everywhere – but it is material
One of the project's most interesting findings was that biodiversity risk was highly localized.
Out of roughly 140,000 agricultural plots analyzed, only a subset experienced meaningful declines in pollinator habitat. But for farms growing highly pollinator-dependent crops, the projected financial consequences were significant.
That distinction matters.
Rather than treating biodiversity as a universal risk, lenders can identify where environmental changes are most likely to influence financial performance and tailor lending strategies accordingly.
The result is a more targeted approach to both sustainability and risk management.
Looking beyond the Hackathon
While Team Green Finance Lantern built this solution during the SAS Hackathon, the broader implications extend well beyond the competition.
Financial institutions are increasingly being asked to understand how environmental risks affect portfolios, investments and lending decisions. Projects like this demonstrate that analytics and AI can help bridge that gap by translating ecological change into measurable business outcomes.
Today, that may mean pollinators.
Tomorrow, the same approach could help organizations evaluate water scarcity, soil degradation, wildfire exposure or other forms of natural capital risk.
As sustainable finance continues to evolve, the organizations that gain the greatest advantage may be those that can connect environmental intelligence with business decisions – and act on those insights with confidence.
