The Standard for Climate Risk Modeling
First Street (firststreet.org) scores 80 out of 100 on Brand Analyzer, placing it in the Brand-Ready tier among Finance brands, Technology brands, Government brands, in the 66th percentile of 8125 Finance brands.
First Street is an organization focused on quantifying the financial impact of climate risk. It provides data-driven climate risk modeling designed to translate environmental hazards into actionable financial insights for financial institutions, companies, and government entities. The organization positions itself as a trusted, authoritative source for climate risk assessment at scale, operating within the finance, technology, and government sectors.
| Brand Name | First Street |
|---|---|
| Domain | firststreet.org |
| Industry | Finance, Technology |
| Main Competitors | Jupiter Intelligence (71/100), Moody's RMS (78/100), CoreLogic (76/100), Verisk (85/100), XDI (Cross Dependency Initiative) (75/100), ClimateAi, Four Twenty Seven |
Moz Domain Authority 60/100 vs category average 40 / leader 95 - a strong backlink profile, so AI systems frequently encounter mentions of the brand.
Ranked #139,790 on the Tranco list of most-visited sites - modest traffic makes the brand easy for AI models to overlook.
No Wikipedia presence was found - a major gap, since Wikipedia is among the most heavily weighted sources in AI training data.
The homepage meta description reads "We exist to make the connection between climate and financial risk at scale for financial institutions, companies and governments." (Meta description: 19 words (ideal length). OG description present and descriptive) - this is the summary AI engines are most likely to quote.
Structured data on the homepage: og:title, og:description, og:image, og:type, Twitter cards. Adding Organization and FAQ schema would further help AI crawlers parse the brand's identity.
AI-crawler access: robots.txt mentions GPTBot, ChatGPT-User, ClaudeBot, Google-Extended, PerplexityBot - all allowed - robots.txt controls whether engines like GPTBot and ClaudeBot can read the site at all.
Detected tech stack: Next.js.
Social footprint: verified profiles on X (Twitter), LinkedIn, Facebook, Instagram, YouTube, GitHub - consistent profiles reinforce the brand's identity across the web.
0 Reddit mentions - community discussion signals real-world reputation to AI models.
Live results from asking a general-purpose AI assistant about the brand, checked September 2026.
When asked "What is First Street?", Claude could identify the brand as of September 2026. First Street is a nonprofit research and technology organization that quantifies climate risk, particularly flood, wildfire, and heat risk, and translates it into financial terms for individual properties across the US. Best known for Creating Flood Factor, the property-level flood risk score now integrated into major real estate sites like Realtor.com and Redfin.
When asked "Best brands similar to First Street?", Claude would recommend First Street as of September 2026. It's the leading name in property-level climate risk data used widely in real estate and finance, so it's a natural mention for anyone asking about climate risk analytics.
Common questions people ask in Google, ChatGPT, Claude, Gemini, Perplexity, and other AI search engines.
First Street's main competitors in Finance: Jupiter Intelligence (71/100), Moody's RMS (78/100), CoreLogic (76/100), Verisk (85/100), XDI (Cross Dependency Initiative) (75/100).
Sources: Brand Analyzer scan
First Street has limited AI-search visibility, scoring 34/100 on Brand Analyzer's AI visibility composite (visibility 20, trust 27, recommendation 66). This estimates how likely AI engines like ChatGPT, Claude, Gemini and Perplexity are to know, trust, and recommend the brand.
Sources: First Street official site
First Street scores 66/100 on Brand Analyzer's AI recommendation signal, indicating it is reasonably likely to be surfaced when AI assistants like ChatGPT suggest Finance options. Recommendation depends on crawlability, structured data, and category authority.
Sources: First Street official site
First Street can improve AI discoverability by strengthening structured data (Organization and FAQ schema), maintaining an accurate Wikipedia/Wikidata entity, earning authoritative citations, and keeping content crawlable for AI bots. Brand Analyzer measures these as visibility, trust, and recommendation signals.
Sources: First Street official site
First Street is an organization that develops climate risk financial modeling used to quantify the connection between environmental risk and financial risk. It serves financial institutions, companies, and government entities that need to assess climate-related exposure at scale.
Sources: First Street official site
First Street creates data-driven models that translate climate and environmental risks-such as flooding, wildfire, heat, and other hazards-into quantifiable financial risk metrics. These models are designed to help financial institutions, companies, and governments understand and manage exposure to climate-related financial risk at scale.
Sources: First Street official site
First Street's models are used by financial institutions, companies, and government entities that need to assess and manage climate-related financial risk. These users rely on First Street's data-driven risk assessments to inform financial decision-making related to climate exposure.
Sources: First Street official site
First Street scores 34/100 for AI visibility - how well ChatGPT, Claude, Perplexity and Google AI Overviews can discover, identify and cite the brand.
First Street has a weak AI-visibility profile at 34/100 - a proxy for how readily ChatGPT, Perplexity and Google's AI Overviews can recognise and cite it. Its strongest area is recommendation likelihood (66/100) and its weakest is visibility (20/100). It benefits from a Wikidata knowledge-graph entry, a global traffic rank of #139,790 (Tranco) and a Moz Domain Authority of 60/100. The main gaps holding it back: no clear Wikipedia entity to anchor it in LLM training data, thin schema.org structured data and no llms.txt to steer AI to its best pages. In a live check, Claude could already identify First Street from memory (September 2026) - a sign these signals are paying off.
The score combines seven dimensions - name quality, digital presence, visual identity, messaging clarity, trust foundation, AI discoverability, and brand authority - into a single objective benchmark.
Ranked closest to First Street: Fina (80/100), Fi Money (80/100), Fiska (80/100), Flexi (80/100).
A step up - brands to learn from: Zurich Insurance Group (81/100), Zoya (81/100).
Category leader: TradingView (97/100).
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