The increasing prevalence of big data, large stores of data that enable businesses to generate previously inaccessible insights, has resulted in performance gains for the firms that harness its capabilities. However, the impact that big data has on a firm’s profitability and financial position is rarely captured in its financial statements due to big data’s status as an internally generated intangible asset. As per the current IFRS regulations, big data is not eligible for recognition.

We argue that the true impact of big data on a firm is not appropriately reflected in a firm’s financial statements. The IFRS as currently written does not allow firms to capitalize data assets, thus compromising the goal of financial statements: to provide relevant and reliable information.

Analysis of the current standards reveal gaps in measuring the future economic benefit and costs of big data, primarily attributable to the lack of clarity surrounding the unit of account used to measure big data. Furthermore, IAS 38′s dichotomization of research and development does not accurately represent the applicability of big data assets.

Therefore, we propose a conceptual framework for understanding the economic value of big data. These include the use of a database as a unit of account, costing methods derived from user-based metrics, and a renewed focus on the intention to apply data assets.

大数据和大量数据存储的日益普及，使企业能够产生以前无法获得的见解，为利用其能力的公司带来了绩效提升。然而，由于大数据作为内部产生的无形资产的地位，大数据对公司盈利能力和财务状况的影响很少在其财务报表中体现。根据现行国际财务报告准则的规定，大数据不符合认可资格。

我们认为，大数据对公司的真正影响并没有适当地反映在公司的财务报表中。目前的国际财务报告准则不允许公司将数据资产资本化，从而损害了财务报表的目标：提供相关且可靠的信息。

对现行标准的分析揭示了衡量大数据未来经济效益和成本方面的差距，这主要归因于用于衡量大数据的记账单位缺乏明确性。此外，IAS 38对研发的二分法并不能准确体现大数据资产的适用性。

因此，我们提出了一个理解大数据经济价值的概念框架。其中包括使用数据库作为记账单位、从基于用户的指标得出的成本计算方法以及重新关注应用数据资产的意图。