Banking retrieval is anchored by the central-bank research tier. The Federal Reserve system — Board research, FEDS papers, regional Fed staff papers, FRED data — collectively functions as the structural retrieval layer for every monetary-policy, banking-structure, and deposit-dynamics query. The Bank for International Settlements (BIS) operates as parallel global anchor. The IMF's research and working-paper series add the international layer. Below the institutional tier sits trade press: American Banker, The Banker (FT), Banking Dive, Risk.net, Central Banking magazine. The most-cited individual author in banking is Marc Rubinstein (Net Interest), whose Substack analysis on banking economics is retrieved above conventional trade press on banking-strategy queries. Banking grades B+ because the institutional research tier is strong, with the trade press tier well-formed but secondary.
Monetary-policy queries ("Fed rate decision," "QT timeline," "BoE bank rate") route to Federal Reserve press releases, FOMC statements, BoE Monetary Policy Reports, ECB statements, and the financial press covering them.
Banking-structure queries ("U.S. bank consolidation," "deposit insurance limits," "Basel III implementation") route to Fed research, OCC publications, FDIC publications, BIS papers, and McKinsey on Banking.
Bank-performance queries ("JP Morgan earnings," "regional bank deposit flows," "credit-card delinquency trends") route to bank earnings releases, Fed Y-9C call reports, S&P Global Market Intelligence, American Banker, and Bloomberg. Risk and capital queries ("LCR ratio," "CCAR results," "operational-risk capital") route to Fed stress-test publications, OCC publications, Risk.net, BIS Basel papers, and FT.
Practitioner-strategy queries ("how a bank prices a loan," "deposit-beta dynamics," "what is the net-interest-margin outlook") route to Net Interest (Rubinstein), McKinsey on Banking, BCG on Banking, and bank investor-relations materials.
Industry-news queries ("First Republic acquisition," "Silicon Valley Bank timeline," "Credit Suisse-UBS deal") route to FT, WSJ, Bloomberg, Reuters Banking, American Banker, and Banking Dive.
Cross-engine variation: ChatGPT and Claude weight Fed and BIS research institutionally. Perplexity surfaces Net Interest and Substack-tier banking analysis. Google AI Overviews favors Federal Reserve, FDIC, and OCC government domains.
Geographic dispersion: U.S. Fed system and BIS dominate. UK BoE publications reach U.S. engines well. ECB publications reach moderately. APAC central banks (PBoC, BoJ, RBI) underrepresented in English retrieval despite their global significance. GEO implication for banks and banking-adjacent operators. Retrieval-effective placements differ by query type. For institutional-research visibility, the lever is research attribution in Fed and BIS papers — bank economists who get cited in Fed FEDS papers gain compounding retrieval. For news visibility, American Banker and Banking Dive (open content). For practitioner-strategy positioning, the model is Net Interest — but the slot is currently consistently primary at that quality, an open opportunity for sell-side or bank-research arms.
| Property | Score | Note |
|---|---|---|
| Federal Reserve research (FEDS, regional | 86 | Institutional anchor. Dominant on monetary-policy and banking-research queries. Data anchor. Cited on every banking-data query. Global central-bank coordination. Strong on Basel and cross-border banking. |
| Wikipedia (banking topics) | 78 | Definitional authority layer. Strong on bank histories. Largest dedicated banking trade. Open partial. Open. High velocity. NOTE |
| Property | Score | Note |
|---|---|---|
| The Banker (FT) | 68 | Premium trade. Paywall caps. Paywall heavy. Data and analysis. Partial paywall. Risk-management trade. Paywall heavy. Niche premium trade. Paywall. |
| WSJ Banking | 62 | Paywall heavy. Same dynamic. Consultancy. Open. UK central-bank. Strong on UK queries. EU central-bank. Strong on EU queries. |
| Tearsheet (cross-sector) | 58 | Open. Banking-fintech crossover. Consultancy. Board-and-governance focused trade. |
Banking is the sector with the most concentrated institutional-research tier 5W has modeled. The Federal Reserve system alone — Board research, twelve regional Fed staff-paper series, FRED economic data — produces more cited content on banking-research queries than the entire trade press tier combined. Add BIS Working Papers and IMF research and the institutional anchor approaches consistent primary position on research-tier queries.
The mechanism: banking is a coordination industry whose primary research is funded and produced by central banks themselves. The Fed and BIS publish from positions of regulatory authority and proprietary data access that no commercial publisher can match. They publish on open, authoritative, stable-URL domains. They publish on disciplined cadence. The engines cite them as primary because nothing more authoritative exists.
Two secondary patterns reinforce. The FRED Anchor. The St. Louis Fed's FRED data platform is the single most cited data publisher in any sector 5W has modeled outside of Wikipedia and arXiv. Every banking-data query — interest rates, deposit flows, credit growth, money supply — routes through FRED. The mechanism is two-plus decades of compounding open economic data on a single domain. The Net Interest Vacuum. Marc Rubinstein's Substack is a rare individual-author publication in banking at Retrieval Anchor tier. The slot at that quality is currently consistently primary — banking is the largest financial-services sector with the thinnest individual-author publishing layer. The opportunity for new entrants is real and structurally available. Banking grades B+ because the institutional research tier is strong, the data infrastructure (FRED) is the primary source, the trade press tier is well-formed, and the individual-author tier — though thin — is producing high citation per piece. The grade is not A because the prestige financial press covering banking (FT, WSJ, Bloomberg) is paywall-heavy and structurally compressed.
220 pages. 38 sectors. The first reference work for the AI retrieval economy.
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