Regulatory reporting 2027
SREP data capability, RDARR for LSIs, the data core, crypto-asset reporting and the AMLR break – eight topic pages with a roadmap 2026–2028.
To the topic pagesAbout
Management consultant for regulatory reporting, data architecture and AI compliance in banks and insurers – owner of Mag. Eiler & Partner OG in Vienna. Author of the topic pages on this website and of the LinkedIn series.

For more than twenty years Patrick Eiler has worked at the interface of regulatory reporting, accounting and IT: business analysis for ABACUS/GMP, OeNB reports, AnaCredit, FINREP and COREP, business intelligence and data science – and, since the EU AI Act, the AI compliance of Austrian financial institutions.
One thesis runs through all topic pages: regulatory reporting is moving from the report to data capability. Validation rules remain important, but from 2027 supervisors and auditors ask where a figure comes from, who owns it and how quickly it can be recomposed. The answer is the same in every rulebook – a complete inventory, documented lineage, named ownership – and it can be built once and used many times. AI has a clear place in this: as detector and explainer, never as the calculator of the report.
Four: regulatory reporting 2027, AI compliance, the Cyber Resilience Act, and data science and business intelligence.
SREP data capability, RDARR for LSIs, the data core, crypto-asset reporting and the AMLR break – eight topic pages with a roadmap 2026–2028.
To the topic pagesEU AI Act, AI inventory, FRIA, ISO/IEC 42001, board liability – with the AI Compliance Staircase as maturity model and the AI Governance Maturity Assessment.
To the AI compliance pagesScope, reporting obligations since 11 September 2026, SBOM, conformity and the Austrian status – for institutions as manufacturers of their own apps.
To the CRA pagesData models, analyses and reports that business and IT carry together – from SAP BW to models on reporting data.
To the servicesOn 23 September 2026 Patrick Eiler spoke at the expert session of the Hypo-Verband on “Lösungsansätze, die belegbar sind” (approaches that can be evidenced): the supervisory framework in which regulatory reporting is assessed from 2027, from DORA and NISG 2026 to the revised SREP Guidelines. On LinkedIn his topics appear as series (in German); the first, “Who sees the payment”, follows a 15-euro purchase through six payment methods in twelve parts and tests four theses on the digital euro. All series are listed in the series overview.
Agile, as part of a team and traceable. For years Patrick Eiler has worked in Scrum teams made up of business, regulatory reporting and IT – as business analyst and product owner, among others for an ABACUS/GMP platform and in agile insurance projects with Jira and Azure DevOps. Requirements sit in a prioritised backlog, are delivered in two-week sprints and accepted in the review on the running system. Every user story carries its source in the regulation or reporting schema, its acceptance criteria and its test – from backlog entry to acceptance, the path of every requirement stays documented.
An example from regulatory reporting: The EBA intends to shrink its harmonised reporting framework by around half of its data points, net; the first reference date is planned for 30 September 2027. The first sprint compares the draft with the institution's own reporting chain. Every data point that is dropped becomes a backlog item with one check question: do internal reports, disclosure or national requests still need it? Only then are data feeds decommissioned. A test run with real data from a past reference date shows that the remaining positions stay unchanged. Mag. Patrick Eiler takes on the role that is missing in-house: product owner, business analyst or coach for the reporting team.
Education, career stations and anonymised project examples will be added to this page; until then the LinkedIn profile reflects the career.
In a non-binding first conversation we clarify which question is on your institution's agenda – data capability in the SREP, an AI use case or CRA reporting readiness – and which limited first engagement answers it.