Climate resilience for Financial Institutions
Physical risk is a financial variable. Iris quantifies it with the rigor your risk frameworks demand. Banks, asset managers, and lenders face growing regulatory requirements to assess, disclose, and act on physical climate risk across their portfolios.
The data behind those disclosures needs to withstand internal model review, auditor scrutiny, and regulatory examination. Iris produces traceable, engineering-grade loss estimates at portfolio scale, with the methodology documentation and audit trail that institutional risk teams expect.
How financial institutions use Iris
From deal diligence to portfolio risk to regulatory filing.
Transactions
Climate risk due diligence embedded in the acquisition workflow.
Quantify asset-level losses under current and forward scenarios, surface the cost the headline price misses, and deliver within deal timelines.
Portfolio-wide physical risk screening across asset classes and geographies.
Identify risk concentrations, rank assets by exposure, and produce loss metrics compatible with existing risk frameworks.
Outputs aligned to ISSB / IFRS S2, the EU Taxonomy, SFDR, and CSRD, expressed as modeled losses.
Scenario analysis across SSP pathways and time horizons, with methodology documentation built for auditor and regulator review.
Audit-ready methodology at portfolio scale
Vulnerability variety
Two assets of equal value can sit in the same flood zone and carry very different risk. A trophy office tower, a garden-style multifamily community, and a hyperscale data center hold their vulnerability in different places: the structure, the critical systems, the cost and time to make each one whole.
Grid-based scores hand all three the same rating. Iris quantifies the gap, and that gap moves expected loss, valuation, and what you disclose to auditors and LPs.
Portfolio coverage
Most funds and loan books hold hundreds of positions, with a long tail of small ones. Iris screens every asset for multi-hazard exposure first, then puts engineering-grade modeling where the exposure actually concentrates.
The same platform that screens 400 assets across a fund can deliver component-level loss estimates on the 20 positions that carry 80% of the value-at-risk. Broad enough for disclosure, deep enough for the investment committee.
Component-level loss estimates
Iris models the systems that actually drive loss: structural frame, building envelope, mechanical and electrical systems, and the mission-critical infrastructure inside. Fragility functions are matched to the real building type, its vintage, and its components.
Loss comes back as a probabilistic range of repair cost and downtime, reported with confidence intervals. Those figures drive how a climate event flows into value, income, and expected loss, and a loss number you can show with its uncertainty is what survives an IC memo and an audit.
