Pricing the Unpriced Asset: A Standards-Based Method for Valuing Enterprise Data under IAS 38 and IAS 2

2026-06-21

AI Summary

This study addresses the challenge that enterprise data assets often fail to meet the capitalization criteria under IAS 38, resulting in unreliable measurement and fair valuation, which in turn causes market mispricing. To resolve this, the paper proposes a dual-layer valuation framework: D-Val, grounded in verifiable production costs and amortization mechanisms consistent with the IAS 38 cost model, and A-Val, which incorporates business-relevant attributes—such as scarcity, accuracy, and verifiability—to derive reasonable valuations in inactive markets. Innovatively integrating accounting standards with the unique characteristics of data assets, the framework treats data rights confirmation and independent audit as prerequisites for asset recognition. It thereby establishes an auditable cost basis and a defensible commercial valuation for certified data assets lacking active trading markets, advancing their financial reporting and pricing mechanisms.

Abstract

The recognition and measurement of data assets under current accounting standards presents significant challenges. While International Accounting Standard 38 (IAS 38) provides a framework for intangible asset recognition, data assets frequently fail to meet capitalisation criteria due to difficulties in demonstrating separability, establishing reliable cost measurement, and proving probable future economic benefits. The widespread failure to easily and reliably value data causes mispricing and allocative distortions across data and artificial intelligence markets. This paper introduces a two-layer valuation progression for authenticated data assets, that is, datasets that have met IAS 38 recognition criteria through established legal provenance and contractual boundaries. The first layer, D-Val, is the auditable cost-basis valuation consistent with IAS 38. D-Val is defined as D-Val = Cp * Avt, where Cp is the reliably measurable production cost and Avt is the appreciation or depreciation factor applied over time. Under prevailing interpretations of IAS 38, Av is constrained to values less than or equal to one absent an active market revaluation, rendering D-Val a strictly cost-less-amortisation figure. The second layer, A-Val, is a theoretically grounded commercial valuation that incorporates scarcity, rivalry, completeness, accuracy, and explicit premia for provenance authentication and independent audit. A-Val is not auditable as fair value under current practice but serves as a defensible commercial valuation during the period before active markets for authenticated data assets mature. As authenticated data markets mature parameter assumptions improve providing a foundation for iterative refinement of the model.

Problem

• data assets
• IAS 38
• valuation
• intangible assets
• accounting standards

Innovation

• data asset valuation
• IAS 38
• two-layer valuation model
• authenticated data
• intangible assets