Automating Solvency II Reporting: Dedicated Software or Custom Data Chain?

Automating Solvency II reporting means replacing the manual production of the QRT, the SFCR and the ORSA with a replayable data chain, running from source data to XBRL filing. Two routes exist — dedicated regulatory software and the custom data chain (Power BI, Databricks) — and the right choice does not follow from dogma but from a single criterion: which architecture makes your closings traceable, reconciled and reproducible identically.

Every quarter, the same constraint returns in insurers' finance and actuarial departments: produce, within tight deadlines after the closing, a set of prudential returns that is coherent, justifiable and fit to be filed with the regulator. Quantitative QRT, the SFCR, the regular supervisory report, the ORSA: deliverables that all draw on the same source data — actuarial, accounting, asset management — but that too many organisations still assemble by hand, in spreadsheets circulating by email and requiring reconciliation at every closing.

The problem is not knowing how to calculate an SCR or populate a QRT: the teams know how. The problem is doing it quickly, without error, and replayably — that is, being able, six months later, to re-run exactly the same production on the same data and obtain the same result, tracing every step. That is where reporting automation is decided, and that is where the architecture choice matters.

What "Solvency II reporting" actually covers

Pillar 3 of Solvency II (Directive 2009/138/EC) structures transparency and reporting. In practice, an insurance undertaking produces:

• the QRT (Quantitative Reporting Templates), quantitative templates defined by EIOPA's implementing technical standards, filed with the national supervisor (the ACPR in France) in XBRL format — some quarterly, the full set annually;

• the SFCR, the public report on solvency and financial condition;

• the RSR, the more detailed regular report intended for the supervisor alone;

• the ORSA, the own risk and solvency assessment, which connects strategy to the capital trajectory.

These deliverables share a common base: the Pillar 1 results (SCR, MCR, technical provisions) together with accounting and asset data. The whole operational difficulty lies in that sharing — the same data point must be consistent across the capital calculation, the QRT and the financial statements, closing after closing.

The real cost of manual reporting

An artisanal production chain does not merely cost time. It creates three risks that management teams know well:

• Broken traceability. When a figure passes through several workbooks and manual adjustments, nobody can reconstruct with certainty where it came from. Faced with a question from the regulator or the statutory auditor, justification takes days.

• Non-replayability. A closing produced by hand is not reproducible identically: re-running the production on the same data does not necessarily give the same result, because part of the logic lives in unwritten gestures.

• Key-person dependency. The knowledge of the chain resides in the heads of two or three people. Their absence at closing time is a real operational risk.

Industrialising reporting means converting those three risks into guarantees: reconciled data, replayable production, a documented chain that no longer depends on an individual.

Two possible architectures — and the criterion that separates them

Two families of solution coexist, and the right choice depends on context, not on dogma.

Dedicated regulatory software. A specialised tool embedding the QRT templates, the XBRL taxonomy and part of the regulatory validations. Its advantage: format compliance is handled and maintained by the vendor at each evolution of the standards. Its limitation: flexibility. As soon as a need falls outside the anticipated scope — a specific business control, a particular reconciliation with the accounts, a cross-framework comparison — the tool constrains more than it helps, and vendor dependency becomes structural.

The custom data chain. An architecture that processes data at scale (with Databricks, for example), stores it in a governed warehouse, and renders it as steering dashboards and control reports (with Power BI, for example). Its advantage: it fits the organisation's processes exactly, reconciles frameworks natively, and makes every step traceable and replayable. Its counterpart: it demands initial engineering and a level of data governance that not every organisation has in house.

The criterion that separates these two routes is not "which one calculates the SCR?" — several do so correctly. It is: which architecture makes my closing replayable, traceable and auditable, without multiplying points of failure?

The Finengy position: the standard and the tool together

Knowing the regulation is not enough if its production remains slow and error-prone; mastering a tool is not enough if one does not understand the standard it must serve. Our conviction is that reporting automation succeeds precisely at the intersection of the two.

Concretely, we industrialise prudential reporting chains with market tools — Power BI for rendering and steering dashboards, Databricks for processing data at scale, accounting integration on the SAP side — in service of an operational objective: faster closings, traceable controls, and data reconciled between the prudential and financial views. From source data to the deliverable filed with the regulator, the complete chain becomes a managed asset rather than a constraint endured.

The same logic holds beyond Solvency II, for IFRS 17 or the CSRD: the value does not come from the tool alone, but from the engineering that puts the standard into practice. The underlying architecture is set out in our article on automated Power BI reporting architecture.

Market reference points

• Usual filing deadline for quarterly QRT: around 5 weeks after quarter-end (solo; around 11 weeks at group level); full annual reporting: around 14 weeks after the closing. (ITS reporting / Directive 2009/138/EC — orders of magnitude, to be re-verified against the applicable calendar.)

• Mandated format: EIOPA's XBRL taxonomy, versioned (2.8.x series) — a version mismatch is a classic cause of rejection.

• A shared base: QRT, SFCR, RSR and ORSA all derive from the same Pillar 1 results (SCR, MCR, provisions) — hence the value of a single chain rather than silos.

• Horizon 2027: the Solvency II review (changes to deadlines and taxonomy) — the chain must be maintainable, not frozen.

Frequently asked questions

Do you need dedicated software to automate Solvency II reporting? Not necessarily. Dedicated software handles the QRT formats and the XBRL taxonomy, but constrains as soon as a need falls outside its scope. A custom data chain fits the organisation's processes and reconciles frameworks natively. The right choice depends on context, not on dogma — the decisive criterion is the replayability of the closing.

What is "replayable" reporting? Reporting that can be re-run identically six months later, on the same data, giving the same result and tracing every step back to source. That is the condition of a closing that is auditable before the supervisor or the statutory auditor; manual production, where part of the logic lives in unwritten gestures, does not offer it.

Which returns are concerned by automation? The whole of Pillar 3: the quantitative QRT (filed in XBRL with the ACPR), the public SFCR, the RSR intended for the supervisor, and the ORSA. All share a common data base (SCR, MCR, provisions, accounting, assets), which makes a single chain more coherent than separate productions.

Are Power BI and Databricks enough to produce the QRT? They equip the chain — Databricks for processing and reconciling data at scale, Power BI for rendering and controls — but the value comes from the engineering that puts the standard into practice, not from the tools alone.

Sources: Directive 2009/138/EC (EUR-Lex, Pillar 3); EIOPA implementing technical standards (reporting / QRT); EIOPA XBRL taxonomy (2.8.x series); ACPR. Deadlines and taxonomy versions are usual orders of magnitude, subject to change (Solvency II review 2026-2027); re-verify against the applicable ITS. Informational content; this does not constitute regulatory advice.