acePublic technical disclosure of AI implementation in finance: Python-framed evidence from 253 NYSE-listed financial companies
Abstract Artificial intelligence (AI) claims in public markets increasingly raise disclosure, comparability, and investor-protection questions, yet evidence on how listed financial firms publicly describe implementation remains fragmented and difficult to compare. This study examines public technical disclosure rather than internal adoption by constructing a screened, exchange-bounded corpus for 253 NYSE-listed financial companies. The source intake contained 554 rows; six exact repeated rows were removed before…
Public disclosure of AI implementation by NYSE-listed financial firms is thin: few name specific tools and almost none quantify outcomes, limiting comparability and investor scrutiny.
The study examines public technical disclosure rather than internal adoption, and covers a bounded population of NYSE-listed financial companies, so it does not show actual AI use inside firms.
Evidence
- Peer-reviewedFinancial Innovation2026-10-16
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Truvace Impact Record TRV-2026-1716, v1: “Public technical disclosure of AI implementation in finance: Python-framed evidence from 253 NYSE-listed financial companies.” Truvace, 2026-10-17. /record/TRV-2026-1716 (accessed at citation time). sha256 8b5b8a03e902db15…
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