A Valuation Methodology for Authenticated Data Assets: Addressing Recognition Challenges in Data Portfolio Management

The recognition and measurement of data assets under current accounting standards presents significant theoretical and practical 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. Where data assets do meet IAS 38 recognition criteria, the default accounting position produces a carrying value based on capitalised production cost adjusted downward for amortisation and impairment, with no appreciation contemplated, no market premium, no scarcity adjustment, and no quality weighting. This cost-adjusted floor represents the pre-authentication accounting baseline: a position that captures what was spent to produce the data but not what it may be worth as a commercially deployable asset.

This paper introduces a systematic valuation methodology for authenticated data assets, that is, datasets that have met IAS 38 recognition criteria through established legal provenance and contractual boundaries. Authentication is the mechanism through which a dataset is separated from the broader data estate, given contractual boundaries, and made capable of participating in an active market. That separation is the precondition for valuation above the IAS 38 cost floor and the pathway through which cost-based carrying value can progress toward a valuation that more accurately reflects commercial reality. The methodology explicitly distinguishes between the quality-based A-Val indication, capturing the commercial and economic characteristics of the dataset, and the auditable value satisfying the verification standard required for formal balance sheet recognition. We propose a theoretically grounded A-Val formula incorporating explicit cost floors, systematic rivalry factor determination, and a stable scarcity function to produce conservative, auditable valuations, with provisional premiums for authentication and audit verification derived from related certification markets and economic theory. Parameter assumptions are explicitly identified for empirical validation as authenticated data markets mature and active market comparables become available.