
Systemic handling of regulatory data - Are capital management companies on an equal footing with CRR institutions?
In the increasingly data-driven world of finance, asset management companies (KVGs) are faced with the challenge of meeting regulatory requirements efficiently and systematically. The topic of data management is increasingly coming into focus – both in terms of quality, availability and security as well as with regard to the strategic use of data.
Looking at the banking sector, the advantages of holistic data strategies, central governance structures and the reduction of data silos have been emphasized for some time. Institutions in particular see this not only as a way to meet regulatory requirements, but also as a basis for data-driven innovations. At the same time, there is a growing recognition in the industry that data is viewed as a strategic asset.
The KVGs lack a correspondingly clear marker and the range in development is likely to diverge widely. But are fund companies really at a disadvantage compared to institutions when it comes to handling regulatory data?
1. Changing regulatory requirements
For institutes, the focus in 2025 will be on topics such as CRR III, DORA, CSRD, FiDA and MiCAR. These regulations require a high level of data quality, availability and security. Institutions have responded with massive investments in data governance, data lineage and automated reporting systems.
AIFMs are also increasingly affected – for example by CSRD (Corporate Sustainability Reporting Directive), SFDR (Sustainable Finance Disclosure Regulation) and AIFMD II. Or when special investor groups pass on their regulatory reporting requirements largely unfiltered and the KVG thus have to become experts in Solvency II,, CRR III and the GroMiKV. There is growing pressure to manage ESG data, risk metrics and reporting packages in a consistent, traceable and audit-proof manner, for example.
2. The status quo in asset management companies
While institutions were forced to standardise at an early stage by requirements such as BCBS 239, the regulatory maturity of AIFMs varies greatly. Many institutions have begun to modernize their data architectures in recent years. Nevertheless, there are still structural differences to the banking sector:
- Fragmented system landscapes: While institutions often use centralized data warehouses, fund companies often work with isolated solutions – especially for smaller companies.
- Manual processes: Excel-based workflows are still widely used in the fund industry, which increases the susceptibility to errors and makes auditability more difficult.
- Lower IT budgets: Compared to institutes, AIFMs have significantly fewer resources for data-driven transformations.




