Alan Shapiro

About Alan Shapiro

I work at S&P Global Market Intelligence helping investment teams plug the world\'s best financial data directly into the AI tools they already use. Our MCP connector lets you query S&P\'s datasets: financials, segment level estimates, earnings transcripts, transactions, private company data, and business relationships, natively inside Claude, ChatGPT, etc, in plain English, with sourced, auditable answers and flat pricing. No hallucinations, no overage fees, no data gaps. Visible Alpha sits on top of that foundation and shows you what the street actually thinks at the driver level: sell-side models normalized across 170+ industries, so you can test your thesis line by line, spot where you\'re non-consensus, and track which analysts have been right over time. The underlying platform, Capital IQ Pro, pulls together auditable fundamentals on 99% of global market cap, 60M+ private companies (14.5M with current financials), private capital benchmarks, and asset level sector data across energy, TMT, insurance, real estate, metals and mining, and banking, all in 1 place instead of 5 different tools. If you want to upgrade your research or plug better data into your AI workflow, send me a DM!

Experience

1. Account Executive

   S&P Global

   Jul 2025 — Present · New York, NY, US

   We help investment teams work faster and make smarter decisions by giving them:• S&P\'s MCP connector plugs financials, segment-level estimates, earnings transcripts, transactions, private company data, and business relationships directly into Claude, ChatGPT, etc. Queryable in plain English, sourced and auditable, with no overage fees• Auditable fundamentals covering 99% of global market cap, traceable to the original filing on every number• 60M+ private companies (14.5M with current financials, 200+ standardized line items): 4x the coverage of any other data platform, with ownership, headcount trends, and valuation data to size markets and find targets• Visible Alpha: sell-side models normalized across 170+ industries so you can test your thesis line by line against the street, spot where you\'re non-consensus, and catch surprises before they move price. • Machine Readable Transcripts covering 13,600+ entities back to 2004, with speaker tagging, entity linking, and seamless integration into NLP workflows• Deep sector data across Energy, TMT, Insurance, Real Estate, Metals and Mining, and Banking. Real operating drivers, not just headline financials• Cross-reference mapping to clean and match messy IDs across vendors so data actually lines up in your modelsIf you want to upgrade your research or plug better data into your AI workflow, send me a DM!

Education

• Baruch College

  Business/Corporate Communications

  2015 — 2018