In property insurance, accurately recorded living area is a key factor in determining premiums, the sum insured, and policy valuation. This relationship is particularly direct in household property insurance. However, living area also plays a central role in many home insurance policies and valuation methods.
If the recorded square meters differ from the area determined using the relevant calculation method, this can affect insurance coverage amounts, premiums, and risk assessment. Such discrepancies add up across large portfolios. A systematic living space audit makes these discrepancies visible. For large portfolios, it is particularly feasible when it is automated and scalable.
A living space verification compares the living space recorded in the insurance portfolio with a reference value calculated using a standardized and transparent method. It reveals discrepancies across the board, creates a robust database, and supports risk-based pricing and portfolio valuation—from individual contracts to the entire portfolio.
Why Living Area Is Relevant to the Sum Insured, Premium, and Policy Portfolio
Homeowners insurance has been under pressure for years. For the first time since 2020, the industry’s average combined ratio fell below 100 percent in 2024, reaching 96.47 percent, down from approximately 101 percent in 2023. However, the underwriting results of the fifty largest providers have remained consistently negative in recent years. The slight improvement in 2024 was primarily due to a favorable claims experience and higher premiums, not to structural improvements [1].
Furthermore, the related residential property insurance line has been profitable only four times since 2002 and is therefore considered a persistently challenging line of business [2]. In this situation, the quality of the portfolio data and the accurate representation of the insured risk also become increasingly important.
Living space is by no means relevant only for traditional living space-based rates. It can also be directly factored into the calculation when determining a building’s insurance value. In the VdS 772 method, for example, the 1914 value is derived, among other things, from the living area and a building-specific valuation rate per square meter. Incorrect area measurements can thus carry over throughout the entire valuation and rate-setting process.
The connection is even more direct when it comes to home contents insurance. Many insurers determine the flat-rate sum insured based on the living area and a set value per square meter. For example, if the rate is 650 euros per square meter, a difference of just 20 square meters results in a discrepancy of 13,000 euros in the flat-rate sum insured. In many policies, correctly reporting the living area is also a prerequisite for waiving the underinsurance clause.
The quality of the living space information is therefore not merely a matter of master data. Depending on the line of business and the rate schedule, it affects the sum insured, the rate calculation, and the quality of the risk assessment.
How Discrepancies in Living Area Arise
Discrepancies rarely result from intentional misconduct, but are often caused by differences in calculation methods, historical data sets, or inaccurate information provided at the time the contract was signed.
In Germany, several calculation methods coexist, most notably the Living Space Ordinance (WoFlV), DIN 277, and insurance-specific methods such as VdS 772. They consider or evaluate building areas differently. As a result, the same building can yield different values depending on the calculation method used.
The measurements themselves also vary. In a 2015 survey conducted by the property owners’ association Haus und Grund, three appraisers arrived at figures that differed by as much as 16 percent [3]. Added to this are renovations, attic conversions, or additions that were not always fully accounted for in older contract records.
Across an entire portfolio, such discrepancies can develop into a significant—and often undetected—portfolio risk, both in household contents insurance and in home insurance.
What a robust living space assessment must achieve
A living space assessment is only as good as the data on which it is based. Three requirements are crucial.
First, methodological traceability: The calculation is based on recognized calculation standards such as DIN 277, VdS 772, and WoFlV, ensuring that results are transparent and consistent.
Second, scalability: Manual individual checks are not cost-effective when dealing with several thousand objects.
Third, consistency: All objects are evaluated using the same method, ensuring that the results remain comparable within a given set.
Only when these three elements come together can a database be created that serves as the foundation for inventory audits, rate adjustments, plausibility checks, and pricing decisions.
The SkenData Living Space Check
This is exactly where SkenData’s WohnflächenCheck comes in. It automatically calculates the floor areas of single-family and multi-family homes based on recognized calculation standards such as DIN 277, VdS 772, and WoFlV. The system is based on official 3D building data for 61 million buildings in Germany and Austria. This results in uniformly calculated floor area values: comprehensive, efficient, and without the need for time-consuming on-site inspections.
The WohnflächenCheck is designed for large property portfolios and is suitable for portfolios with 1,000 or more buildings. Insurers can integrate it in two ways: directly into their existing systems via API, or as data enrichment via a CSV file. Both options deliver structured results quickly and without the need for additional manual verification.
Employees in portfolio management, underwriting, or product management can use it to analyze entire portfolios instead of manually recalculating individual policies. This tool is relevant for both home insurance and household contents insurance portfolios, provided that living space is factored into the premium calculation, the sum insured, or the risk assessment.
From Data Validation to Improved Inventory Quality
The actual value is determined after the reconciliation. Once uniformly calculated living areas are available, it becomes clear for each specific property where the recorded values deviate from the reference value and where this may necessitate verification or adjustment.
In home contents insurance, this applies in particular to policies in which the sum insured and the waiver of underinsurance are linked to the reported living area. In home building insurance, variations depending on the rate plan and valuation method can affect the premium calculation or the determination of the insured value.
Underestimated floor areas may indicate previously unidentified potential for premiums and returns. It is therefore crucial that the inventory data used for rate setting and risk assessment correspond to the actual condition of the building or to a uniformly calculated reference.
At the same time, underwriting, portfolio management, and product managers work from a more consistent data foundation. Decisions become more transparent, portfolios can be segmented more effectively, and anomalies can be systematically prioritized.
Particularly in a sector such as residential property insurance—which has been struggling with profitability for years—the quality of living space data thus evolves from a seemingly minor detail in master data into a concrete lever for pricing, portfolio quality, and profitability.
Conclusion
Discrepancies in living space can affect the insured amount, premium rates, and risk assessment—often unnoticed and across large portfolios.
In residential property insurance, the living area is also directly factored into the insured amount, premium calculation, and risk assessment, depending on the rate plan and the valuation method used.
An automated living space audit highlights these discrepancies and provides a consistent basis for portfolio reviews, rate setting, and other decisions. SkenData’s WohnflächenCheck audits portfolios on a scalable basis—via API or data enrichment.
Find out how much premium potential your residential building portfolio holds. Efficiently assess your portfolio with the WohnflächenCheck: Request a quote now.
Sources:
[1] Versicherungsbote (2025): Homeowners Insurance 2024: Some Relief, but with Reservations. Available online at: https://www.versicherungsbote.de/id/4946498/Wohngebaeudeversicherung-2024-Entspannung-mit-Vorbehalt/ (accessed on September 8, 2026).
[2] Gehrmann, Dirk (2025): Property and Casualty Insurance in Germany in 2024: Homeowners Insurance Remains a Loss-Maker. In: Wohnungswirtschaft heute, March 25, 2025. Available online at: https://wohnungswirtschaft-heute.de/schaden-und-unfallversicherung-2024-in-deutschland-wohngebaeudeversicherung-bleibt-unveraendert-ein-verlustbringer/ (accessed September 8, 2026).
[3] Haus & Grund Rheinland Ruhr (2015): Haus & Grund: “Actual living space doesn’t exist in practice!” News release dated November 16, 2015. Available online at: https://www.hausundgrund-verband.de/aktuelles/einzelansicht/haus-grund-die-tatsaechliche-wohnflaeche-gibt-es-in-der-praxis-nicht-2601/ (accessed on September 10, 2026).
