DataGov-Factory: An Empirical Evaluation of Managed vs. Custom LLM Agent Architectures for Financial Data Governance

This paper presents the first controlled empirical comparison of three LLM deployment architectures for financial data governance: (A) platform-managed agents, (B) custom multi-agent factory, and (C) direct API calls. Key finding: platform-level prompt caching reduces context costs by ~90%, making managed agents competitive while delivering 16% higher quality. v2: Fixed broken LaTeX references.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-04-11
DOI
https://doi.org/10.5281/zenodo.19520901
Primary Topic
Financial Reporting and XBRL
Type
article
Field-Weighted Citation Impact
0.00
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article

DataGov-Factory: An Empirical Evaluation of Managed vs. Custom LLM Agent Architectures for Financial Data Governance

Karl J. Mollan Neyra
Zenodo (CERN European Organization for Nuclear Research)
Financial Reporting and XBRL
article

DataGov-Factory: An Empirical Evaluation of Managed vs. Custom LLM Agent Architectures for Financial Data Governance

Karl J. Mollan Neyra
article en

Abstract

This paper presents the first controlled empirical comparison of three LLM deployment architectures for financial data governance: (A) platform-managed agents, (B) custom multi-agent factory, and (C) direct API calls. Key finding: platform-level prompt caching reduces context costs by ~90%, making managed agents competitive while delivering 16% higher quality. v2: Fixed broken LaTeX references.

Zenodo (CERN European Organization for Nuclear Research)
Industry, innovation and infrastructure
Openalex Percentile: Top 14%
Financial Reporting and XBRL
DOIOpen Access PDFOpenAlex
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DataGov-Factory: An Empirical Evaluation of Managed vs. Custom LLM Agent Architectures for Financial Data Governance — Karl J. Mollan Neyra · Zenodo (CERN European Organization for Nuclear Research) (2026) | TGRS Research Map | TGRS