The key findings of the study
The study reveals that data protection can generate economic benefits for data-driven organisations:
- a factor that builds trust among customers, partners, investors and authorities;
- a differentiating advantage for organisations with robust data governance;
- a lever for improving risk management and control;
- a factor promoting responsible innovation and the development of projects based on data and artificial intelligence.
Data protection should be viewed not only as a regulatory requirement, but also as a factor contributing to trust, organisational resilience and value creation.
Data governance, utilisation and value creation
The report analyses the conditions under which data assets can generate sustainable economic value.
It highlights the following value creation chain:
Data assets → Data governance → Compliance and risk management → Trust and usability → Future economic benefits → Valuation → Sustainable value creation
According to this approach, the ability of a data asset to generate future economic benefits depends, in particular, on:
- its quality and reliability;
- its usability;
- its governance;
- its security;
- the lawful use of the data;
- its longevity and sustainable use over time.
The report begins by analysing the conditions under which data assets can generate sustainable economic value through their positive impact on trust. Trust is an intangible asset which, in turn, can underpin the valuation of data and its ability to generate future profits.
The study examines how these considerations can be incorporated into economic valuation and financial valuation approaches, as well as into discussions regarding the accounting treatment of intangible assets. Best practices enable these economic benefits linked to data and compliance to be better recognised and safeguarded.
Data-related risks and value destruction
The report also examines the reverse logic, whereby governance or compliance shortcomings can affect the economic value of a data asset:
Governance weaknesses → Data risks and non-compliance → Reduced trust and usability → Decline in expected future profits → Risk of impairment or loss of value → Destruction of value
Risks likely to influence the value of a data asset or an organisation’s valuation may include, amongst others:
- inadequate data quality;
- non-compliant processing;
- cybersecurity incidents;
- personal data breaches;
- governance shortcomings;
- regulatory investigations or sanctions;
- reputational damage;
- restrictions on the future use of data.
The report emphasises that the economic value of data is not measured solely by the profits it generates, but results from the interplay between value creation, risk management and regulatory compliance.
Valuation, accounting and data assets
The study examines the links between data assets, their capacity to generate future economic benefits, and certain approaches to financial valuation.
In particular, it analyses how considerations relating to governance, compliance, data quality and risk management can be taken into account in asset and business valuation exercises.
The report also addresses considerations and best practices regarding the recognition of data as intangible assets under International Financial Reporting Standards (IFRS). It explains how to better realise the valuation potential of these assets within the framework of current standards, which, incidentally, would benefit from further development in this regard.
Mergers and acquisitions, investments and due diligence
The study highlights that data protection issues are playing an increasingly significant role in financial transactions (mergers and acquisitions, investment, financing) involving companies whose business model relies heavily on data or artificial intelligence.
These factors can influence the valuation of the assets in question as well as the assessment of the risks associated with a transaction, ultimately affecting the transaction’s chances of success, its terms and its price.
The study highlights best practices for taking data and compliance into account within the framework of financial due diligence procedures and explains how these can be integrated into valuation methods based on future revenue streams (the DCF method).
Governance, cybersecurity and artificial intelligence
The report also highlights the increasing integration of data protection into organisations’ governance structures, risk management frameworks, cybersecurity strategies and artificial intelligence projects.
This trend reflects the growing importance attached to trust, accountability, resilience and risk management in digital environments. In particular, effective data protection is proving to be a prerequisite for the robust deployment and use of AI systems within organisations.