6.5.3.1CapEx and Opex in relation to the action plans

a.s.r. uses CapEx and Opex as key performance indicators to monitor investments and funding that support the implementation and maintenance of action plans for climate change mitigation, adaptation, and transition. Investment amounts in euros are divided between actions taken during this reporting period and planned future allocations. To be included, expenditures must be allocated to an existing action plan. In addition, targets on business line level must exceed the €1 million materiality threshold to be included.

6.5.3.2Gross scope 1, 2, 3 and total GHG emissions

The disclosures on the Greenhouse Gases (GHGs) are related to the seven gases as mentioned in ESRS E1: carbon dioxide (CO₂), methane (CH4), nitrous oxide (N2O), hydrofluorocarbons (HFCs), perfluorocarbons (PFCs), sulphur hexafluoride (SF6) and nitrogen trifluoride (NF3). The general unit of measure for the GHGs is in tonnes of carbon dioxide (CO₂) equivalent, tCO₂e. This universal unit of measurement is used to indicate the global warming potential (GWP) of each greenhouse gas, expressed in terms of the GWP of one unit of carbon dioxide.

Scopes 1 & 2

Methodology and scope

Facilities, Robidus, D&S Holding, Corins, TKP, IT and Knab (up to 31 October 2024) contributed to the gross scope 1 and 2 GHG emissions. The GHG emissions resulting from IT's own operations, only accumulate to the scope 2 emissions. For a.s.r., scope 1 GHG emissions include the direct emissions of fossil fuel-based lease cars, refrigerant usage and leakage, fossil fuels used for heating and the fuel usage of emergency generators. The scope 2 GHG emissions of a.s.r. consist of purchased electricity used for office buildings and leased electrical vehicles and are divided in market-based and location-based emissions. The market-based emissions take purchased renewable energy into account and assume that regular power is delivered as residual power. The location-based emissions are calculated based on average country-specific emission factors.

Assumptions and limitations

Due to limitations in the data availability for lease cars, a.s.r. does not make a distinction between private and business kilometres and the fuel type. The inclusion of both private and business kilometres in the calculation leads to higher calculated scope 1 and 2 emissions as only business kilometres are required. To cover the emissions associated with refrigerants, a standard leakage of 5% is incorporated in the calculation. The emissions associated with small refrigerators are considered negligible and have therefore been placed out of scope. For the calculation of a.s.r.'s scope 1 and 2 emissions of some offices, estimations are made via an extrapolation factor based on m² surface or amount of employees.

Market- and location-based

The emissions factor for the calculation of the location-based emissions is retrieved from co2emissiefactoren.nl. a.s.r.’s market-based emissions factor is calculated by using the location-based emissions factor minus the amount covered by contractual instruments. These contractual instruments consist of bundled instruments such as energy contracts and unbundled instruments like the Guarantee of Origin (Garanties van Oorsprong - GvO) certificates. These energy contracts or certificates are issued by independent organisations and validate the origin of the renewable energy.

Measurement uncertainties

The percentages of contractual instruments are calculated using a weighted average, with the scope 2 location-based emissions as weighting factor.

Scope 3

Methodology and scope

The relevant GHGs and unit of measure mentioned at the start of this section also relate to scope 3 emissions. a.s.r.’s scope 3 emissions are reported in line with the GHG Protocol, which splits the scope 3 GHG emissions into 15 categories. a.s.r. will only report on the significant scope 3 categories in tCO₂e. The following scope 3 categories listed below, were found not material in a.s.r.’s double materiality assessment:

Category 2 – Capital goods
Category 3 – Fuel- and energy-related activities
Category 4 – Upstream transportation and distribution
Category 8 – Upstream leased assets
Category 9 – Downstream transportation and distribution
Category 10 – Processing of sold products
Category 11 – Use of sold products
Category 12 – End-of-life treatment of sold products
Category 14 – Franchises

The categories of scope 3 GHG emissions discussed hereafter were found to be material for a.s.r.

The percentage of primary data is calculated using a weighted average, with the tCO₂e amount as the weighting factor. The methodology is based on the GHG protocol. A step-by-step manual has been developed and shared with the product lines to guide them in calculating the percentage for their scope 3 GHG data.

Application of PCAF

a.s.r. applies the PCAF methodology to determine the emissions from the downstream leased assets (category 13 of the GHG-Protocol) and Investments (category 15 of the GHG-Protocol). The methodologies for carbon accounting are still evolving, e.g. a new update was published in 2024 for consultation.

Category 1 – Products and services

This category includes upstream emissions associated with purchased goods and services by a.s.r. in the reporting year.

Methodology

For the calculation of scope 3 emissions associated with purchased goods and services, a.s.r. selected the spend-based method in line with the GHG Protocol, which estimates emissions for goods and services by collecting data on the economic value of goods and services purchased and multiplying it by relevant secondary industry average emissions factors per monetary value of goods. The total spend per supplier is classified according to industry codes, the North American Industry Classification System (NAICS), which is the standard used by federal statistical agencies in classifying business establishments for the purpose of collecting, analysing, and publishing statistical data related to the U.S. business economy. In order to calculate the total CO₂ footprint of central procurement, the NAICS model is paired with the US Environmentally-Extended Input-Output (USEEIO), which is a family of models designed to bridge the gap between traditional economic calculations, sustainability, and environmental decision-making. To adjust for inflation and differences in currency, a.s.r. converted from USD to euros using the 2021 exchange rate, as well as adjusting the 2021 consumer price index (CPI) to 2024.

Efforts to obtain value chain information

The spend-based method was employed due to the current unavailability of precise value chain information. Efforts to improve value chain information include working more closely with value chain partners to improve data accuracy and reduce reliance on estimates.

Assumptions and limitations

The spend-based method is limited to 80% of total spend within central procurement, which includes the most significant suppliers in terms of total spend. Calculations will be performed per supplier for this 80% of total spend using the mentioned spend based model. The remaining 20% of total spend relates to smaller suppliers and is extrapolated based on the analysis of the 80% total spend that was covered.

Supplier expenditures also occur outside the central Procurement department within the a.s.r. product lines. For this spend, central procurement has included the spend of Real Estate (which is outside the central ProActis system) in their analysis. For Disability, Knab and TKP a separate analysis has been performed. With regard to supplier emissions for Disability, no clear guidance is present within PCAF or the GHG protocol on whether to classify these emissions as category 1 or 15. These costs could be considered as insurance-related expenses similar to Health or P&C. However they also relate to upstream suppliers. For 2024 at a best effort basis the emissions are included within category 1. While acknowledging this approach has limitations, it does include emissions for Disability activities in order to inform stakeholders of these emissions.

For other product lines the spend has been determined to be not material, to be included in other categories (for example category 15 – insurance associated emissions) or the supplier emissions are estimated using an estimation model. This model extrapolates the emissions of purchased goods and services per euro spent of central procurement (including Real Estate spend outside of the central ProActis system) to the distribution and services entities Corins, D&S Holding and Robidus.

Category 5 – Waste generated

This category covers the emissions associated with the disposal and treatment of waste generated from facilities owned or controlled by a.s.r. This includes general waste generated, waste from renovation activities and waste from disposed hardware.

Methodology

In addition to the GHG protocol scope 3 guidance, Facilities, TKP and IT receive reports stating the kilogrammes per waste type. The data for these product lines on waste type and kilogrammes are multiplied by the relevant emissions factors using the Carbon Manager tool. See section 6.5.3.4 for more information on the calculation methodology and assumptions used for waste generated. Corins and Knab assign a proportion of the waste generated by the whole building based on m². D&S Holding and Robidus calculate their emissions from generated waste with the estimation model.

Category 6 – Business travel

Category 6 of scope 3 emissions includes the emissions related to transportation of employees for business-related activities, not including daily commuting.

Methodology

In accordance with the GHG Protocol, a.s.r. applies the distance-based method to calculate the scope 3 category 6 GHG emissions. a.s.r. includes business travel by car, aeroplane and public transport, as per the claim and reimbursement processes. Travel with NS-Business Cards, hotel stays and taxi rides are out of scope for a.s.r. but in scope for TKP.

Efforts to obtain value chain information

Given current data availability and complexity of data collection, the distance-based method provides a fair estimation of emissions. a.s.r. aims to strive improving data quality and availability in the future.

Assumptions and limitations

The calculated emissions are based on travel claims for public transport and transport by car. Even though the emissions per car differ, the average emission per kilometre from CO2emissiefactoren.nl is used to calculate the emission of transport by car.

Category 7 – Employee commuting

Category 7 covers the emissions associated by employee commuting. The scope is limited in terms of travel modes to car, public transport and motorcycles for own employees of a.s.r.

Methodology

a.s.r. reports on this category in accordance with the distance-based method, as described in the GHG Protocol for scope 3 emissions. a.s.r. used information from the access control system in the office, along with employee declarations of their commuting distances.

Efforts to obtain value chain information

Given current data availability and complexity of data collection, the distance-based method provides a fair estimation of emissions. a.s.r. aims to strive improving data quality and availability in the future.

Assumptions and limitations

For the calculation of commuting distance, a.s.r. assumes that the distribution of travel modes is in line with insights provided in the National Traveler Survey 2023 (Landelijk Reizigersonderzoek 2023). Other assumptions include that for a.s.r. all motor vehicles are calculated as cars and all scooters are included as bicycles. Bicycles with a commuting distance more than 20 km are assumed to have travelled with public transport.

Category 13 – Downstream leased assets (Financed Emissions)

This category includes emissions from investment properties that are leased out by a.s.r.

Methodology

From Real Estate's side, this includes the emissions from the ASR Dutch Farmland Fund, which are calculated with data provided by the Nutriënten Management Instituut (NMI). The NMI uses the initiator model to calculate the emissions based on a.s.r. its properties. The initiator model is a publicly available model that gives insight into how carbon behaves and interacts in rural areas and is developed by scientists from the Wageningen University and Research (WUR).

Amvest's category 13 emissions result from the energy usage within its direct fund. Information with regard to the tenant spaces are supplied by the energy suppliers, while asset managers provide insight on the energy usage of the common spaces. In terms of data coverage, the direct funds have a coverage of 99.4% on 2023 data. Missing values are estimated based on ZIP code area.

The data quality score is calculated using a weighted average, with the AuM amount as the weighting factor. The methodology is based on the PCAF standard. A step-by-step manual has been developed and shared with the business lines to guide them in calculating the data quality score.

Efforts to obtain value chain information

Given the complexity and scale of the downstream leased assets portfolio, obtaining precise data is currently not feasible. Efforts to improve include potentially improving the granularity of reported data as a.s.r.'s technical capabilities and value chain relationships mature.

Assumptions and limitations

The calculation for Real Estate is based on a combination of actual measurements and model estimations provided by the NMI. In Q1 2022 a.s.r. Real Estate has requested a second opinion from an independent professor of the WUR on the research and calculation of the NMI over the 2020 CO₂ footprint of Rural. No findings were noted. If any, measurement uncertainty is minimal.

Category 15 - Investments (Financed Emissions)

For category 15, a.s.r. reports on financed emissions as reported in the financial statements for Asset Management, Mortgages, Real Estate, Knab and Amvest, where investments on behalf of policyholders are mentioned separately. a.s.r. reports on mortgages for which an a.s.r. entity is the originator, which excludes Robuust and Dynamic Credit mortgages. For an overview of the Real Estate portfolio in scope, see section 7.5.4.The financed emissions from Asset Management include the own account investments and investments on behalf of policyholders and consist of government bonds, corporate bonds, and equities. Investments via funds are allocated to these asset classes via look-through. Other assets such as derivatives, cash, hedge accounting and SME loans are not included in the emission calculation as there is no emission data or PCAF methodology available. For Amvest, the indirect funds; RCF and LCF are in scope for category 15.

The data quality score is calculated based on the PCAF standard, using a weighted average with the AuM amount as the weighting factor. A step-by-step manual has been developed and shared with the product lines to guide them in calculating the data quality score.

Efforts to obtain value chain information

Given the complexity and scale of the investment portfolio, obtaining precise data from all investments is currently not feasible. a.s.r. leverages various standards and methodologies to make estimates for emissions which are further described below. Efforts to improve include potentially expanding the scope of data collection and improving the granularity of reported data as a.s.r.'s technical capabilities and value chain relationships mature.

Methodology

With respect to Real Estate, the GRESB framework is used for external non-listed real estate investments. For the indirect funds of Amvest, the 2023 data is not available in time to be included in the Annual Report 2024 of a.s.r. Therefore, Amvest provides a.s.r. with 2022 data to calculate its emissions for indirect funds. Once the 2023 data becomes available, it is used to compare to the 2022 data and adjust the values in case this is required. Given the 82% data coverage of the RCF fund, missing values will be estimated based on the ZIP code area. For all other financed emissions, the PCAF methodologies are used. For Mortgages and Real Estate, a.s.r. uses internal and external data, for all other investments a.s.r. relies on external ESG data vendors' data.

Assumptions and limitations

Real Estate takes into account the PCAF methodology for estimating based on m2 of an asset, in case no direct meter reading was available and no ESG templates were filled in. Asset Management relies on external ESG data vendors, who provide the necessary datapoints. This external data includes emission data reported by companies as well as estimations. Data coverage of GHG emissions for government bonds, corporate bonds and equities is between 90% and 100%. The GHG emissions of externally managed investments can only be included if look through data is available. The methodology of Amvest contains limitations as it is relying on 2022 data and estimations for missing values. With respect to Mortgages, the attribution factor on gas and electricity usage is based on an extrapolated CBS dataset from 2019. As more recent events are not taken into account in this dataset, it is likely to result in higher reported emissions. Moreover, assumptions are made when the external data is unavailable, based on object characteristics.

Category 15 - Investments (Insurance-associated Emissions)

a.s.r. has taken into account the "PCAF Global GHG accounting and reporting standard for the financial industry – part c – insurance associated emissions" in order to report on insurance associated emissions for Health and P&C. Emissions associated with healthcare providers are reported under Category 15 Investments, specifically as Insurance-associated emissions. A discrepancy exists between the upstream placement of healthcare providers in the value chain and their downstream reporting under Category 15. Sector discussions concluded that emissions from healthcare providers should not be placed under Category 1 Purchased Goods and Services, due to the lack of direct operational need, nor under Category 15 Investments, due to value chain orientation discrepancies. Given the anticipated review of the PCAF standard in 2025 and Health's affiliation with a larger insurance group, it is deemed appropriate to report healthcare provider emissions under Category 15 Investments, accepting the value chain orientation discrepancy for the first year of reporting. A similar conclusion applies to the reported emissions of repair companies, but a.s.r. chooses to utilise the transitional provision of value chain information and/or the lack of a generally accepted methodology to calculate emissions of repair companies in particular.

Some insurance product lines are not reported. The emission output for Disability and Individual life and Funeral is not recognised as material, Funeral does not yet have a standard methodology, and Pensions has no insurance-related GHG emissions other than those arising from their investment portfolio.

Methodology

For the calculations of P&C, a.s.r. differentiates between its commercial and private car insurance lines. For private car insurance, emissions are calculated by multiplying the average kilometres driven in the Netherlands by the average emissions per kilometre and the PCAF industry attribution factor. The total insurance-associated emissions for the private car insurance portfolio are then determined by accumulating these insured emissions. For commercial lines, emissions are calculated by multiplying the average sector emissions in tCO₂e per euro by the premium in the reporting year. The total insurance-associated emissions for commercial lines are determined by accumulating these insured emissions.

For the funeral sector, the PCAF standard does not contain a methodology and other sources are dated. Therefore, a.s.r. committed to a joint industry initiative as a.s.r. wants to contribute within the sector to obtain an industry-wide calculation methodology and definition. At this moment, the lack of reliable data and methodology results in an exclusion of quantitative explanation. The emissions of claims related to in-kind funeral policies are disclosed in scope 3 Category 1 Products and services. Health calculates its insurance associated emissions by multiplying the emission factor per healthcare type with the euros spend on the healthcare type. The emission factors per healthcare type are retrieved from a report by Stichting Stimular.

Efforts to obtain value chain information

Estimating emissions associated with insurance activities presents challenges due to the diverse nature of insured assets and the limited availability of methodologies for estimating emissions. a.s.r. has utilized sector-average data and industry benchmarks to provide initial estimates, reflecting a reasonable effort given current data limitations. Efforts to improve data accuracy include collaborating with distribution and services entities to develop standardized reporting frameworks to enhance data collection from insured entities. a.s.r. is committed to progressively refining these estimates as more precise data becomes available.

Assumptions and limitations

Within Individual life and Funeral's policies, the funeral payment of a capital insurance policy is freely available for the beneficiaries to spend in accordance with their preferences. Consequently, a.s.r. has no influence on the funeral and little or no reliable data on the insurance associated emissions available.

Due to data unavailability, several assumptions have been made within P&C's policies for the insurance associated emissions for commercial and private lines. For the calculation of the private cars, a.s.r. cannot take mutations into account and due to the publication timeline of the CBS, there is a delay of one year. For the calculations, a.s.r. assumes that all insured cars have an average emission factor and drive the Dutch average amount of kilometres per year. Moreover, the ownership costs in relation to the cost of insurance are unknown to a.s.r. For the commercial line, a.s.r. assumes that customers have an emission based on their industry sector. As not all the client’s activities are known to a.s.r. the SBI codes are applied. a.s.r. only has access to premiums booked on a product level, sector and client level is unavailable at the moment. Therefore, certain parts will be estimated. Lastly, the method used for Health is considered the most appropriate methodology due to the diversity in the sector and limited availability of data. As a result of the measurement uncertainty, the reported scope 3 emissions related to Health should be considered as a guiding value.

Reconciliation of AuM with financial statements

Due to the use of different standards for emissions calculation (ESRS) and financial statements (IFRS), differences arise, necessitating a reconciliation table. These differences include scope and valuation.

For instance, in the sustainability statements, the mortgage portfolio is valued at residual debt, whereas in the financial statements, it is primarily valued at fair value. Additionally, mortgages on behalf of third parties are off-balance in the financial statements but included in the emissions calculation. For investment property, the emissions calculation includes AuM allocated in real estate funds, which are categorised as own investments in the financial statements

GHG Emissions intensity

For the calculation of the emissions intensity, a.s.r. defines net revenue as the insurance contract revenue (ICR) + direct investment income, fee income and other income related to renewables. a.s.r. complies to the ESRS by dividing the market-based, location-based and total GHG emissions by the net revenue in scope of the GHG emissions calculations. This includes the emissions intensity for all the a.s.r. product lines and subsidiaries.

The emission intensity with regard to AuM is determined by dividing the total emissions of as asset class by the AuM data coverage value. Due to the sale of Knab, these assets are included for 10 of the 12 months. This leads to a small variance that is visible in the emission intensity presented for government bonds.

There are no direct assumptions for emissions intensity; however, reliance is placed on the related assumptions of the input values as described in the previous sections.

6.5.3.3Climate change mitigation projects financed through carbon credits

Issued carbon credits for emission reductions or removals from climate change mitigation projects outside the value chain, are material for a.s.r. The carbon credits are issued by Trees for All, which only sells carbon credits from projects that are validated by Plan Vivo against the Plan Vivo Carbon Standard. Each one of these credits represents the removal of one tCO₂e by trees.

For 2024, a.s.r. purchased carbon credits to compensate scope 1, 2 and 3 emissions from its locations in Utrecht.

For 2025, a.s.r. will purchase carbon credits to compensate scope 1 and 2 emissions from its locations in Den Haag, Leeuwarden, Enschede, Rotterdam, Heerlen and Utrecht.

6.5.3.4Resource outflows

Waste streams

Waste streams generated from a.s.r.’s own operations are divided into several different categories or waste types. These categories are all related to waste generated by a.s.r.’s own workforce and include waste types such as PCD, paper and organic waste.

Facilities

Methodology

To categorise the resource outflow data, a.s.r. used the European Waste Catalogue. This catalogue enabled a.s.r. to identify different waste streams in its own operations. Moreover, a.s.r. embedded the Waste Framework Directive for defining all waste disposal methods that are used within its own operations. a.s.r. did not take radioactive waste into account, as this is not applicable for its own operations.

Assumptions

Waste from a.s.r.’s own operations is generally reported on the basis of the average weight of waste containers. In cases where only invoices are available, the invoices are based on the number of containers that were emptied. Whenever this is applicable, a.s.r. calculates the weight per waste stream with the help of key figures from the waste recipient. Moreover, where necessary, the weight of waste is calculated based on a ratio using the number of employees at the site, as the Heerlen location is a multi-tenant building.

This excludes waste generated and handled by suppliers and organic waste. Due to data unavailability, a.s.r. made several assumptions. For the waste collected in roll containers, a.s.r. had no exact data but utilised container size and average weight per waste type. For locations where Prezero is not the waste processor, a.s.r. applied Prezero’s key figures to make estimates based on the total weight of the waste. For the Heerlen location, a.s.r.’s estimations were calculated as the number of employees at Heerlen multiplied by the average weight per person as per data from Prezero.  

Limitations of methodology and measurement uncertainty

As only residual waste is specifically weighted, the other waste types that accumulate for approximately 80% of all waste generated in a.s.r.’s own operations, is not specifically weighed. Therefore a.s.r. used averages and ratios in order to calculate the total amount of waste generated and the weight of waste per waste disposal method. Therefore, there is some measurement uncertainty in the data presented.

Moreover, by using ratios to calculate data for the Heerlen location, a.s.r. assumed that all employees produce the same amount of waste in its own operations, which also leads to estimation uncertainty.

IT

All waste generated by a.s.r. IT can be categorised into datacentre hardware and end-user hardware. The datacentre hardware includes all hardware from within the two datacentres of a.s.r., the owned datacentre in Utrecht and the rented space from Switch in Woerden. The end-user hardware includes all laptops, mobile phones and other hardware used by employees of a.s.r. All hardware within these datacentres, as well as end-user hardware is considered property of a.s.r. and will be disposed, re-used or recycled by a.s.r. The weights of the disposed products (as per the waste manifests) are researched through publicly available sources (e.g. product pages on online shops) in order to calculate the kilogrammes of waste divided into metals, plastics and refractory oxides (metallic minerals).

Knab, TKP, Corins, D&S Holding and Robidus

Methodology

The a.s.r.'s distribution and services entities D&S Holding and Robidus made use of an estimation model, which was developed by a.s.r. As actual data was not available for these entities for multiple reasons, these distribution and services entities estimated the amount of their generated waste by using reported values from a.s.r.’s own operations. As Corins and Knab are located in shared buildings, a proportion of the building's total waste is assigned based on these entities office surface. TKP uses actuals but estimates the glass and cartridge waste based on the data of a.s.r.

Limitations to methodology

The estimation model was developed by a.s.r. to generate data for its distribution and services entities. It does not take into account the different waste streams and waste disposal treatments per location. Therefore, the estimation model only provides an indication of the actual data, based on apportioning values from a.s.r.’s head office.

Measurement uncertainty

To calculate all necessary figures for the distribution and services entities regarding the circular economy, an estimation model based on a.s.r.’s key figures was used. As a.s.r.’s key figures only consist of approximately 20% direct measurement, there is a measurement uncertainty in the circular economy data provided for these entities.

6.5.3.5Impact investments

Impact investments

a.s.r. aims to contribute to sustainable development through impact investments in Asset Management, Real Estate and Mortgages. The definition for Impact investments is based on the definition given by the Global Impact Investment Network (GIIN), and is as following:

'Investing with the intention of generating a positive, measurable social and/or environmental impact in addition to a financial return'.

The valuation method for financial amounts, such as totals that are published, is in line with the method applied for the balance sheet in the financial statements, unless specified otherwise.

Asset Management

Impact investing, which a.s.r. defines in line with the Global Impact Investing Network (GIIN) as an investment approach that seeks to generate positive, measurable social and environmental impact alongside financial returns, is a key component the Policy on Responsible Investments. a.s.r. purposefully allocates capital to generate measurable positive changes in the areas of climate, nature, health, and human rights, without compromising financial performance. Asset Management has formulated impact investing targets since 2018, helping its clients contribute to addressing global sustainability challenges. Asset Management focuses on directing capital to areas where it can create the most significant impact, such as sectors where funding is scarce, technologies critical to building a sustainable future, and underserved groups that require additional support.

Asset Management’s impact investing approach is built around five principles, which provide the foundation for all investment decisions.

1. Intentionality: All investments must have a credible Theory of Change (ToC) to ensure intentionality, clearly articulating how the investment will create positive social or environmental outcomes.

2. Measurability: Outcomes and impacts must be tracked through clear Key Performance Indicators (KPIs) to ensure transparency and accountability.

3. Do no significant harm: All investments must avoid causing significant harm to environmental or social objectives.

4. Positive contribution: All investments must make a meaningful and positive contribution to one of more of Asset Management’s impact goals, as defined for each of its focus themes.

5. Market rate financial returns: While impact is the defining feature of our approach, Asset Management also aims to deliver competitive financial returns to meet its fiduciary responsibility to its clients.

Real Estate

a.s.r. real estate is committed creating long-term value from both a financial and social perspective, by responsibly investing in high-quality real estate. As a result, the sectoral real estate Funds are committed to limiting the negative impact upon the environment. Alongside reducing the environmental footprint, a.s.r. real estate is committed to making a positive societal impact.

The Funds, as part of their yearly strategy cycles, critically assess their ability to make an environmental and societal impact. The result of this is that part of the funds’ strategies are clearly defined and accredited as impact investing strategies. These strategies and objectives are in accordance with both the European Association for Investors in Non-Listed Real Estate Vehicles (INREV) and Global Impact Investing Network (GIIN) standards for impact investing.

• Affordable housing

  • a.s.r. Dutch Core Residential Fund developed an impact investment strategy that focuses on the addition of affordable dwellings to its portfolio. Affordable housing refers to residential dwellings with rents that are deemed to be affordable for households with a median income. In 2024, the Fund designates rents up to € 1,350 as affordable. The Fund contributes to affordability by keeping a considerable part of the portfolio in the affordable segment. The Fund extends its portfolio with dwellings in the affordable segment and takes affordability into account in its rental policy.

• Dutch science parks

  • a.s.r. Dutch Science Park Fund makes a positive societal impact by stimulating science parks in the Netherlands, by investing in real estate for the broad range of functions that are needed for science park ecosystems to thrive. To achieve these goals, the Fund partners with (semi) public entities, e.g. universities and local governments, as well-functioning science park ecosystems require both public and private real estate investments.

• Sustainable mobility

  • a.s.r. Dutch Mobility Office Fund makes a positive environmental impact through enabling CO2 emission reductions for tenant employee mobility to the Fund’s office buildings. The Fund does this through investing exclusively in offices located on public transport hubs, adding office stock on these locations, and through specific measures aimed at stimulating sustainable mobility for each of the Fund’s office buildings.

• Renewable energy

  • a.s.r. Dutch Green Energy Fund is an impact investment vehicle investing in renewable energy, such as wind and solar farms and energy storage in the Netherlands. By investing in renewable projects, the Fund reduces carbon emissions, promotes clean energy and the transition towards a low-carbon economy.

• International non-listed real estate

  • a.s.r. real estate investment partners make impact investments through its investments that contribute to the UN SDGs in three ways: affordable housing, green buildings, and health & well-being. Each (potential) investment is screened in order to determine of that investment meets the GIIN requirements for impact investments. If all requirements are met, the investment qualifies and is reported as impact investment.

Mortgages

a.s.r. defines mortgage loans that make a positive contribution to reducing GHG as impact investments. And more specifically, where governments and civil society organisations are not sufficiently able to solve certain (persistent) environmental issues on their own therefore, a.s.r. strives to provide support within our ability on this subject. The main target is to generate a measurable positive impact on a sustainable future for people and the planet. These investments are visible in (parts of) concrete products and services.

Customers can make use of an Energy Saving Budget (Energiebespaar Budget) and/or Energy Savings Facilities (Energiebesparende Voorzieningen) to finance sustainable measures. To do this they can make use of a separate product, the sustainability mortgage (Verduurzamingshypotheek). The funds allocated for this purpose can only be used for housing improvements aimed at sustainability, which is in line with this definition and are included in a.s.r.'s impact investment figures. Examples of sustainable housing improvements financed through this product include insulation solutions, solar panels and heat pumps. It is noted that only the used amount for sustainable housing improvements is reported.