Management and Economics | Open Access | DOI: https://doi.org/10.37547/tajmei/Volume07Issue06-14

Designing a Scalable Knowledge Library for Asset Managers: Hierarchical Taxonomy (Stacks–Categories–Subcategories), Metadata Schemas, and Multi-Fund Content Inheritance

Ekaterina Dmitrieva , MVision Private Equity Advisers New York, USA

Abstract

The paper proposes an integrated approach to designing intelligent knowledge management systems for the asset management domain. Against the backdrop of the accelerated expansion of global assets under management, which reached USD 147 trillion by mid-2025, alongside a parallel deterioration in operating profitability by 19% relative to the 2018 level, the ordering and reproducible structuring of corporate information becomes a critically important condition for business resilience. The analysis centers on the formation of a three-layer hierarchical taxonomy as the foundational framework of a domain model, as well as a methodological shift from document-centric descriptions toward system-oriented metadata schemes that ensure end-to-end interoperability of entities, attributes, and relationships across the data landscape. Substantial attention is devoted to the implementation of object-oriented content inheritance mechanisms, enabling the standardization of reusable knowledge fragments, reducing variance in phrasing, and sustaining interpretive consistency as scale increases.

The impact of changes in SEC regulatory requirements and the codification embedded in ILPA 2.0 standards is examined separately, with emphasis on how these developments reshape data architecture principles and elevate requirements for source traceability, version control, and demonstrable compliance alignment. Quantitative performance indicators are provided for the deployment of automated mechanisms supporting responses to due diligence questionnaires (DDQ), reflecting the effects of knowledge formalization and metadata anchoring. The results indicate that integrating semantic knowledge libraries can reduce labor inputs and documentation processing time by up to 75%, while simultaneously improving accuracy, response stability, and conformance with compliance-control requirements.

Keywords

asset management, hierarchical taxonomy, metadata schemes, content inheritance, SEC Marketing Rule, ILPA 2.0, DDQ automation, knowledge library, private markets

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Dmitrieva, E. (2025). Designing a Scalable Knowledge Library for Asset Managers: Hierarchical Taxonomy (Stacks–Categories–Subcategories), Metadata Schemas, and Multi-Fund Content Inheritance. The American Journal of Management and Economics Innovations, 7(06), 130–140. https://doi.org/10.37547/tajmei/Volume07Issue06-14