Julia Backman Does sustainable lending influence bank profitability: Evidence from European financial institutions Vaasa 2024 School of Accounting and Finance Master’s thesis in Finance Master’s Degree Programme in Finance 2 UNIVERSITY OF VAASA School of Accounting and Finance Author: Julia Backman Title of the Thesis: Does sustainable lending influence bank profitability: Evidence from European financial institutions Degree: Master of Science in Economics and Business Administration Programme: Master’s Degree Program in Finance Supervisor: Timothy King Year: 2024 Pages: 61 ABSTRACT: The purpose of this study is to investigate whether sustainable lending influences bank profita- bility. Sustainable loans are green financial instruments that banks offer to companies and indi- viduals for their green initiatives with usually a lower interest rate. The distribution of this lend- ing type has only started to increase in the recent years which in its part explains the lack of research on the subject within the EU. To the increase of the sustainable lending may also have contributed recent changes in legislation and sustainable targets set by the EU where the banks chosen for the study locate. Initiatives such as the EU taxonomy, net zero goal and European green deal are such examples. The study approaches the subject with three research questions that examine whether sustainable lending influences bank profitability and if an increasing time or amount of distributed sustainable lending affects bank performance. The study uses panel data method which observes sustainable lending towards the performance measure ROA as in- dicating bank performance. The research doesn’t find statistically significant indications for sus- tainable lending affecting bank performance. A positive correlation to bank performance is ob- served when sustainable lending has been distributed for an increasing amount and when the time-period for the distribution has been shorter. Many aspects influence bank performance and the result can imply that sustainable lending may have a positive impact towards perfor- mance when distributed for a longer time and in a cautious manner. The study observes the trend for green financing and green initiatives to be increasing. This seems to occur along with the increasing demand for sustainability and a changing legislation around sustainable finance reporting. These factors contribute to a more sustainable future and offer more research mate- rial for the next studies to come. It is a positive direction from an environmental perspective, and it also includes a potential link to performance if the “need for green” is aligned with the sustainable strategies of the financial institutions. KEYWORDS: sustainable finance, green finance, sustainable lending, green lending, commer- cial bank, bank profitability 3 VAASAN YLIOPISTO Laskentatoimen ja rahoituksen yksikkö Tekijä: Julia Backman Tutkielman nimi: Does sustainable lending influence bank profitability: Evidence from European financial institutions Tutkinto: Master of Science in Economics and Business Administration Oppiaine: Master’s Degree Program in Finance Työn ohjaaja: Timothy King Vuosi: 2024 Sivumäärä: 61 TIIVISTELMÄ: Tämän tutkimuksen tarkoituksena on selvittää, vaikuttaako vihreä luotonanto pankkien kan- nattavuuteen. Vihreät lainat ovat kestävän kehityksen rahoitusinstrumentteja, joita pankit tar- joavat yrityksille ja yksityishenkilöille ympäristöystävällisiin kohteisiin, yleensä alhaisemmalla korolla. Tämä lainatyyppi on alkanut yleistyä vasta viime vuosina, mikä osaltaan selittää aihetta koskevan tutkimuksen puutteen EU:n alueella. Vihreän luotonannon lisääntymiseen on voinut vaikuttaa myös viimeaikainen lainsäädännön kehitys ja EU:n asettamat kestävät tavoitteet. Nämä tavoitteet vaikuttavat tutkimukseen valittuihin pankkeihin, sillä ne sijaitsevat EU:n lain- säädäntöalueen sisällä. Lainsäädännön sekä aloitteiden esimerkkejä ovat esimerkiksi EU ta- xonomia, nettonollatavoite ja Euroopan green deal - ohjelma. Tämä tutkimus lähestyy aihetta kolmella tutkimuskysymyksellä. Niiden avulla pyritään selvittämään, vaikuttaako vihreä luoton- anto, pidempi vihreä luotonantoaika tai vihreän luotonannon määrä pankkien kannattavuu- teen. Tutkimuksessa käytetään paneelianalyysiä, joka havainnoi vihreää luotonantoa ROA kan- nattavuusmittariin, joka tutkimuksessa havainnollistaa pankin kannattavuutta. Tuloksissa ei ha- vaittu tilastollisesti merkittäviä viitteitä vihreän luotonannon vaikutuksesta pankkien kannatta- vuuteen. Positiivinen korrelaatio pankkien kannattavuuteen havaittiin, kun vihreää luotonan- toa oli lainattu pidemmällä aikavälillä ja maltillisemmalla rahoitetulla määrällä. Monet seikat vaikuttavat pankkien kannattavuuteen ja tutkimuksen tulos voi viitata siihen, että vihreällä luo- tonannolla voi olla myönteinen vaikutus kannattavuuteen mikäli lainoja lainataan pitkäaikai- sesti maltillisella määrällä. Tutkimuksessa havaitaan, että vihreä rahoitus ja vihreät aloitteet ovat lisääntymässä. Tämä näyttää tapahtuvan samanaikaisesti kestävän kehityksen liittyvän ky- synnän lisääntyessä ja kestävän rahoituksen raportointia koskevan lainsäädännön muuttuessa. Nämä tekijät edistävät kestävämpää tulevaisuutta ja tarjoavat lisää tutkimusaineistoa tuleviin tutkimuksiin. Se on myönteinen suunta ympäristön näkökulmasta ja sisältää myös mahdollisen yhteyden kannattavuuteen mikäli kasvavaan vihreän kysyntään voidaan vastata yhdistämällä kysyntä pankkien omaan kestävään strategiaan. AVAINSANAT: kestävä rahoitus, vihreä rahoitus, vihreä luotonanto, vihreät lainat, liike- pankki, pankkien tuottavuus 4 Contents 1 Introduction 8 1.1 Purpose of the study 9 1.2 Structure of the thesis 10 2 Background 12 2.1 Global strategies that guide financial operators 12 2.1.1 European Green Deal 12 2.1.2 EU taxonomy for sustainable finance 13 2.1.3 Corporate sustainability reporting 14 2.1.3.1 Mitigation of environmental risk in financial institutions 15 2.1.3.2 Greenwashing 16 2.1.3.3 Legitimacy theory 16 2.2 Sustainable finance 17 2.2.1 Green finance 19 2.2.2 Transition finance 19 2.2.2.1 Sustainable loans 20 2.2.2.2 Green loans 20 2.3 Sustainable lending on bank profitability 22 2.3.1 Bank profitability 22 3 Literature review 24 3.1 Current state of research 24 3.2 Sustainable lending and bank performance 27 3.3 Hypotheses development 27 4 Theoretical framework 28 4.1 Performance ratios 28 4.2 ROA, return on assets 28 4.3 ROE, return on equity 28 5 4.4 Sustainable loan ratios 29 4.5 Control variable, leverage 30 5 Data and research methodology 31 5.1 Data sources and description of data 31 5.2 Methodologies 35 5.3 Panel data method 36 5.4 Descriptive statistics 39 6 Empirical results 46 6.1 Regression analysis 46 6.2 Discussion 49 6.3 Limitations 50 7 Conclusions 52 References 54 Appendices 61 Appendix 1. Sustainable lending data (added upon recommendation) 61 6 Figures Figure 1. The average sustainable lending distribution, in thousands € ........................ 34 Tables Table 1. Bank distribution regionally in the study .......................................................... 33 Table 2. Variable listing an definitions ............................................................................ 35 Table 3. Descriptive statistics of all banks ...................................................................... 40 Table 4. Descriptive statistics of northern region, Finland and Sweden ........................ 42 Table 5. Descriptive statistics of central and eastern region, Poland, Hungary and Austria ........................................................................................................................................ 43 Table 6. Descriptive statistics of western region, France, Germany, Denmark, Netherlands, Belgium, Ireland .............................................................................................................. 43 Table 7. Descriptive statistics of southern region: Italy, Spain, Portugal and Greece .... 44 Table 8. Correlation of variables ..................................................................................... 45 Table 10. The result of regression 1 ................................................................................ 47 Table 11. The results of regression 2 .............................................................................. 48 Table 13. The results of regression 3 .............................................................................. 49 7 Abbreviations CIR Cost to income ratio CSRD Corporate Sustainability Reporting Directive EBA European Banking Authority ECB European Central Bank EEA European Economic Area ESRS European Sustainability Reporting Standards ESRB European Systemic Risk Board EU European Union LEV Leverage LIQ Liquidity NPL Non-performing loans ROA Return on Assets ROE Return on Equity UN United Nations 8 1 Introduction Rising environmental issues have been identified as one of the biggest challenges of our time. The changing climate is a shared concern and cross-national measures and agree- ments have been made to affect change to the situation for the better. Companies such as nations have been subject to participate to the endeavors for hindering climate change and many report the measures taken towards sustainable development. Banks and other financial institutions play an important role in sustainable development as their direct and indirect activities impact the environment. The responsibility for bat- tling climate change that these kind of financial institutions have has two sides. As one consequence of climate change are financial problems caused to customers whose is- sues are then reflected on financial institutions. This implies that bank performance is connected to the financial health of their customers. For battling climate change banks can offer products and services that contribute to sustainable development (Stanghellini et al. 2008). The beforementioned also refers to that climate change isn’t only a threat for the environment but also to the economy. Initially the initiatives for the battling cli- mate change have come from the policymakers, central banks and other supervisors. Now both the public and the private sector are finding ways of taking action against the undesired development of the climate. Many banks such as commercial banks have started to include additional green financial products as their financial instruments of- fered to customers that support sustainable development (Park and Kim 2020). Com- mercial banks often act as the primary financier for green projects and green invest- ments for corporate and private customers. Sustainable and green loans as a form of financing that specifically have an environmental objective have started to generalize beside the more common green instruments, green bonds. Sustainable and green loans are similar to green bonds in their green objective and that they should solely be used for green projects. These types of loans are offered to individual corporate and private customers. This enables funding for green projects that have smaller financing needs than what a green bond debt issuing would be used at (The World Bank, 2021). 9 1.1 Purpose of the study The purpose of this study is to provide research-based information to the area of sus- tainable and green lending. The financial instrument in question, sustainable or green loan is chosen specifically since it is directed to private and corporate customers and differs from other lending instruments by its objective, size and the receiver of the loan. This study will from now on coherently refer to sustainable and green lending with the term sustainable lending. This is because in practice the term doesn’t yet seem to have established as much that this study could alone concentrate to only one type of lending. This decision is later argued more thoroughly in this study. The aim in this study is to examine whether a positive correlation between sustainable lending and bank profita- bility exists amongst European financial institutions in different EU countries. Since much previous research hasn’t been conducted within this area with this focus, this study will try to fill this research gap by providing information gathered from those financial insti- tutions that operate and locate in this area. The focus is on big banking organizations within the EU in different countries that offer sustainable lending or that would be ex- pected to offer sustainable lending based on the size of the organization. This study will later also argue why especially the size of the organization seems to suggest a potential existence of sustainable lending in a specific financial institution. This study examines whether a positive correlation between sustainable lending and bank profitability exists and whether the amount or time of the lending offered has an effect in it. In Europe it is geographically visible that many financial institutions that hold the most assets compared to other financial institutions in the area have focused on certain central areas. It is though not self-evident whether the size of the financial insti- tution contributes to the potentially existing correlation between bank profitability and sustainable lending. This is one aspect that this study will also observe. For reaching this goal this study has formed the following three hypotheses that will be viewed in the light of the analysis of the research results: 10 H0: Sustainable lending has no positive correlation to bank profitability This null hypothesis states that no correlation exists between the financial institutions chosen for this study and measured bank profitability. The hypothesis assumes that no statistical significance exists amongst the observations gathered. The three next hypoth- eses assume the opposite and account also for other potentially influential factors. 1: Sustainable lending is correlated to positive bank profitability 2: An increased number of years that sustainable lending has been distributed is posi- tively correlated with bank profitability 3: An increasing amount of sustainable lending distributed is positively correlated with bank profitability These research hypotheses have been created based on the suggestions of previous re- search and literature that would indicate that such correlation could exist. Research con- ducted in the EU area with a data sample of financial institutions such as in this study has yet not been previously conducted. The data is gathered for a time period of 5 years between 2018 and 2022. This five year time frame was chosen because most if the fi- nancial institutions included in this study didn’t report or offer sustainable and green lending before this time period. Observations from this five year period include 337 from 69 different organizations. The year 2023 is at this point excluded from the study since the reporting concerning sustainability measures differs amongst organizations and not all organizations had reported 2023 figures at the time that this study was conducted. This was visible especially in organizations located in France, Greece, Ireland and Italy. More detailed sustainability measures are sometimes reported only in ESG reports. The date for publishing ESG reports seem to vary amongst different organizations. 1.2 Structure of the thesis The structure of this thesis is divided into a theoretical part and an empirical part. The background prior to literature aims in introducing the policies and initiatives that 11 sustainable finance is linked to. Then the study continues into defining and introducing the financial lending instruments, the loan type in question and the type of institutions that offer them as tools to reach the goals of the set initiatives for sustainability. The literature then can offer insight to the current state of research related to the subject and provide the tools for researching the hypothesis. The theoretical framework pro- vides the ratio that is used for measuring profitability within the institutions examined. Examining whether a positive correlation exists between bank profitability and the spe- cific type of loans will be located in the empirical part of this study. The results and con- clusions are presented in the final part of the thesis along with suggestions for future research. 12 2 Background The background for the study will introduce the policies and strategies that relate to the green financial instruments and the underlying framework. The changing legislation re- lated to ESG and sustainability reporting along with general demand are contributing factors for the increase of sustainable products. 2.1 Global strategies that guide financial operators Global operators such as the UN and the EU has set strategies for guiding the transition towards a more sustainable economy. The UN has set a global strategy called sustainable development goals launched in 2015 which are directed to governments. The govern- ments have the responsibility to reach these goals. There are 17 goals which alongside sustainability aim in peace and prosperity in the world. The goals give direction to a global future development. The strategy is called the 2023 agenda for sustainable devel- opment. For reaching its goals, this strategy includes directions for creating policies re- lated to regulation and a taxonomy that addresses environmental and social challenges (Schoenmaker & Schramade, 2019, p.11-12). The UN has a global influence since 193 out of 197 countries recognized by the UN are members (WorldAtlas, 2024). The UN and the EU cooperate to reach the UN determined goals where the EU works continuously to advance these goals with different measures taken (European Commission, 2024b). 2.1.1 European Green Deal The European Green Deal is a group of policy initiatives launched by the European Com- mission in 2019. The Green Deal has been created as a strategy to reach the UN set 2050 goal. The 2050 strategy is aiming for guiding the EU to a green transition and to a climate neutral continent by 2050. In 2030 the greenhouse gas emissions are targeted to have been decreased by 55%. A climate neutral economy in 2050 aims in not creating net emissions of greenhouse gases. This goal is also known as the net-zero goal. The climate neutral economy also strives in detaching resource usage from economic growth. These 13 goals are sought to be met while simultaneously building and maintaining a modern, resource efficient and competitive economy. The set of initiatives include climate, envi- ronment, energy, transport, industry, agriculture, and sustainable finance. The Green Deal also operates as an initiative to sustainably recover from the COVID 19 pandemic. It has received one third of a 1.8 trillion investment from the NextGenerationEU Recov- ery Plan and a part from EU’s seven-year budget (European Commission (2024c). 2.1.2 EU taxonomy for sustainable finance The EU has created a sustainable finance framework that aims in increasing transparency in the market. Within that framework is the EU taxonomy, launched in 2020 that classi- fies or gives the criteria for such activities that can be considered environmentally sus- tainable or that align with the agreed climate goals. The goals of the EU are formatted into the 2050 plan which extends the objectives to concern all countries within the EU. The taxonomy itself includes six environmental objectives along with the criteria for sus- tainability. The objectives include mitigating climate change and adapting to it, using ma- rine resources sustainably, green transition, preventing further pollution and protecting the biodiversity of the planet (Doyle, 2021). For achieving the set objectives regarding increased transparency in the sustainable finance sector the EU identified a need for a precise classification for environmentally sustainable activities. This classification system would make it easier for companies, investors and individuals to have a shared under- standing of what is considered as sustainable activities. Financial and non-financial or- ganizations need to report their activities that align with the taxonomy. Sustainability reporting increases comparability amongst institutions and increases transparency. The taxonomy also has a security aspect to it. Greenwashing, which is later defined and ad- dressed in this study, is a problem that has occurred with the increase of needed and demanded sustainable activities amongst companies and organizations. Shared common definitions will identify the actual sustainable activities for operators (European Com- mission, 2023). 14 The green asset ratio (GAR) quantifies EU taxonomy aligned assets as a percentage in relation to total covered assets. The GAR ratio is designed to increase transparency on sustainable measures taken by a financial institution as financial undertakings. Its aim is to make sure that financial institutions within the EU align with the set environmental goals. The GAR hasn’t been chosen as the best indicator for bank sustainability or an indicator for measuring the progress of the green transition regardless of its aim. This is because not all banks report GAR and the metric itself can’t take into account all activi- ties that can be considered sustainable. A financial institution can support environmen- tally unfriendly customers to reduce their negative impact to the environment but this activity might not necessarily be reflected in the GAR caused by the unsustainable profile of the customer. This would be an example of a sustainable activity that isn’t measured in overall sustainability and reported. There are also a lot of customer companies receiv- ing loans from banks, which are not required to report their operations under similar legislation as companies that need to comply with EU regulation are. The abovemen- tioned issues create information asymmetries around the GAR ratio. They however don’t reduce the fact that the ratio may be helpful for investors and other parties to be more informed about the financial institution’s operations and increased transparency (EBF, 2024). 2.1.3 Corporate sustainability reporting Corporate sustainability reporting has been required from the beginning of the year 2024. The European Commission has made a new corporate sustainability directive (CSRD) that complies large companies and listed SMEs that locate in the EU to disclose information about their social and environmental impact. The directive itself has been effective from the year 2023. The aim of the directive is to increase transparency of sus- tainability towards investors, different organizations, consumers and stakeholders. The CSRD is linked to the European sustainability reporting standards (ESRS) and it expands the information that has previously been obligated to report. The ESRS are the standards and requirements that guide the sustainability reporting. They are created by the 15 European financial reporting advisory group (EFRAG) and align with international sus- tainability standards (European Commission, 2024). 2.1.3.1 Mitigation of environmental risk in financial institutions Climate change and the consequences of it represent an environmental risk to the whole economy. When it comes to the responsibility of environmental protection related to business it is more common to link it to companies whose actions directly affect the environment. It is important to view banks and other financial institutions as intermedi- aries that finance businesses that either are environmentally friendly or not. For this reason, environmental issues concern financial institutions greatly since their effect to the businesses that operate in the market is significant. With offering finance for sustain- able and green activities the financial institutions can steer the overall development into a more sustainable direction. Even if the financial institutions aren’t directly affecting the climate with the nature of their operations it is important for them to consider sustain- ability and the environment with risk mitigation. The risks that emerge in connection with financing polluting businesses or in general environmentally unfriendly businesses are concrete for the financial institutions. The risks reflected on banks can be for example related to credit, legal, reputation, market, interest rate, liquidity, operational and stra- tegic. It is not self-evident how these risks are to be identified, measured, monitored or controlled within financial institutions. If the risks would be presented as to their likeli- hood and impact then credit, legal and reputational risks would emphasize. Credit risk for a bank in a sustainability related lending activity can be a result of a situation where the customer of a bank has been affected by costs related to environmental issues. This can lead to bankruptcy in the worst-case scenario and the loan will be defaulted. Banks can encounter credit risk also in a situation of property impairment caused by environ- mental issues. In the environmental point of view, legal risk arises when compliance in relation to legal environmental obligations is neglected. Legal risk may also be connected to credit risk by banks being legally obligated to pay for environmental problems caused by a contaminated property the bank acted as a lender to. Reputational damages are as severe as the beforementioned risks. They may occur even if the bank isn’t legally 16 obligated to cover for specific environmental damages but if the bank is associated with a project that is environmentally damaging. Reputational risks may have huge implica- tions on the banks business because information travels fast in the modern society. Environmental issues don’t only carry risk but also opportunity. When risk mitigation and recognition is in place it is possible for the financial institutions to try to seize the oppor- tunities that the more sustainable business projects hold in society striving for a greener future (Carse, 2000). 2.1.3.2 Greenwashing The issue of green washing is a relevant subject to mention when dealing with environ- mental topics in relation to company environmental reporting. Greenwashing as a term refers to misleading information directed to the public about climate and environmental actions taken by a company or other organization. In a greenwashing case, the company doesn’t actually do as much for the environment as they claim to do. This reflects nega- tively to the environment since as many actions for tackling climate change hasn’t been initiated as is led to believe. Common example of greenwashing is when a company claims to work towards decreasing polluting emissions but lack a concrete plan to reach this goal. The EU taxonomy with a specified classification system for sustainable activities and increased transparency through ESG reporting are concrete actions against green- washing (United Nations, 2024). 2.1.3.3 Legitimacy theory The policies and laws set by global policymakers and officials are not the only drivers for company social and environmental disclosures in corporate communication. Legitimacy theory discusses the voluntary social and environmental disclosing of companies. These environmental disclosures are typically expressed through annual and sustainability re- ports composed by companies. The legitimacy theory is formed through a number of studies dating back to 1992. According to the theory, there are many factors that influ- ence company disclosures. One factor is environmental laws assigned by policymakers. 17 Stakeholders to the companies also have increasing expectations towards companies to take part in environmental activities and report them. It is not sufficient anymore that the companies only reports to take part in these activities. It is also expected that these activities have a positive and meaningful impact to the environment that could be meas- ured. The aim in disclosing environmental actions are to justify and legitimize the oper- ations carried out by the company within the society. It also has an affect on company’s image that can be appealing to the general public when addressing environmental issues or vice versa. A negative public image may restrict a company’s access to resources cru- cial to the operations and is linked to one of the risks identified in connection to envi- ronment in the banking business. A good image can be utilized as a competitive ad- vantage and limit company environmental liabilities (Mousa & Hassan, 2015). The legit- imacy theory explains why many companies have disclosed reports and communicated their sustainable activities from a time when such disclosures weren’t enforced by poli- cies and regulations. 2.2 Sustainable finance This study is concentrated on topics such as sustainable finance, green finance, sustain- able lending and green lending. These types of lending instruments are related to sus- tainable and green finance which this background section will introduce. The reason why this research uses the term sustainable lending as an umbrella term when referring to the above-mentioned sustainable lending types is because the individual terms don’t seem to have been established yet amongst the European financial institutions. The em- pirical research into the types of sustainable lending instruments that European financial institutions offer showed that these terms are very broadly used to refer to similar types of lending even though the terms have their own definitions. In the future when similar research is being conducted it is highly likely that the terms have become more estab- lished. This allows the study to focus on a specific lending type that is more precise and defined than this study at this point can with this exact set of observations. It is also possible that the EU taxonomy has an impact in the term establishment since it includes 18 clear definitions of the types of instruments that qualify to the reporting of environmen- tal activities. Sustainable finance is a broad term that refers to processes where ESG criteria is taken into consideration when making investing decisions in the financial sector. The aim is to direct capital to such projects that are long term investments favorable to the environ- ment (The European Commission, 2024b). ESG is connected to the concept of sustaina- ble development that aims in securing enough resources for future generations without burdening the planets capacity to supply these resources. ESG stands for three aspects that are environmental, social and governance. For example the environmental aspect is aiming for preventing climate change and further pollution of the environment. It can also aim in preserving biodiversity and enhance circular economy. Social and governance aspect account for issues related to social matters and business related issues. (The Eu- ropean Commission, 2024a). The reason why sustainable development and ESG con- cerns finance is diverse. The main function of the financial system is to allocate funding to productive usage. This gives the financial institutions a significant role in directing fi- nance to companies and projects that support sustainable development. Funding allo- cated to ESG aligning initiatives advance the transition to a more low-carbon and circular economy. Investors also have a role in guiding the direction for the demand. A demand for more sustainable targets to invest in have increased with the awareness of the cli- mate related matters. When it comes to long term investors aligning with ESG, they can demand companies to include and grow the proportion of sustainable business in their operations based on risk mitigation. The objective for sustainable finance has developed from the initial pursuit for short term profit into a long-term value creation which is a good basis for positive long-term environmental effects (Schoenmaker & Schramade, 2019, p.3-4). Sustainable finance is the framework for policy goals included in the European Green Deal and the EU taxonomy. The EU has many sustainability linked global commitments that sustainable finance as the framework is contributing to. The EU channels private investment into the transition along with public investment. In short, the EU is striving 19 to build a financial system that supports sustainability and sustainable growth (European Commission, 2023). 2.2.1 Green finance The function for green finance is to increase and direct financial flows from public and private sources to targets that contribute to sustainable development. Green financing has many channels through which it can be promoted. One of them is policy and regula- tory framework changes that would be directed to achieve similar goals as the UN set sustainable development goals are. Also an overall increase in green financing from dif- ferent sectors to clean and green technologies are approaches that aim towards sustain- ability. A division of the UN has been working towards uniting financial systems by coun- tries, financial regulators and the finance sector. An increased unity between these par- ties contribute to the 2030 and 2050 goals. The main contributions by green finance to these goals currently is the support towards the public sector, promotion of public-pri- vate partnerships on financing mechanisms or instruments and support community en- terprises that utilize micro-credit (UN environment programme, 2024). 2.2.2 Transition finance Transition finance is such finance that has been raised or harnessed to the use of com- panies for their net-zero transition. A transition takes resources both time and money consuming for reaching goals set by global operators such as the UN. Besides the com- mon goal of the net-zero transition, it is up to the nation or the organization to determine how the transition will be carried out. The aspects that affect the net-zero transition vary greatly amongst those that have or will adopt the transition in their operations. As a result of the need for transition, “transition investments” have gained attention from public authorities, industry associations, investors and from the civil society. In general, transition finance is defined as an intention to decarbonize entities or economic activi- ties that are negatively affecting the environment. These entities and economic activities are however important for future development but currently aren’t that 20 environmentally friendly. This is where transition finance supports the transition of an essential entity or economic activity to meet the demands for a sustainable future (OECDiLibrary, 2024). 2.2.2.1 Sustainable loans Sustainable lending can be defined as a decision done by financial institutions to lend to corporate or private borrowers who consider environmental and societal impact in their operations. The overall focus of financial institutions towards the risks related to the en- vironment and social risks has lead to sustainable lending. The awareness that lead to sustainable lending through considering sustainable issues is increasing in the banking industry. The banks hold a key role in financing customers that have an interest toward sustainable issues. The banks evaluate their customers operations to find out whether they fulfill the set sustainability criteria. Avoidance of financing unsustainable customers is a risk related issue. The customers are assessed besides their financial strength but also in their commitment for sustainability throughout the loan period. This creates a requirement for the loan receivers to be able to report how the sustainable loan has been used for the project it was received for. It also creates a demand for being able to measure the sustainable impact of the project (Calderon, 2022). 2.2.2.2 Green loans Green loans are financial loan instruments that finance or re-finance green projects. The aim of the green loan market as a whole is to support those projects that further sus- tainable development. Green projects should give such environmental benefits that they can be defined and in some cases even quantified as environmentally sustainable. The party that provides the green loan has definitions to what they consider to be projects categorized as “green” (Asia Pacific Market Association et al. 2023). Banks and other fi- nancial institutions are the providers of green loans to companies and other parties that direct the funds for example to green innovations. Green loans are generally promoted by having lower interest rates. Lower interest in the loan is an attractive aspect for a 21 company or individual that is planning on launching a sustainability linked project or other operation within the business such as a green purchase with long term benefit for the environment (Li et al. 2018). The green loan principles are as the name suggests principles that characterize green loans. The characteristics established for green loans are use of proceeds, process for project evaluation and selection, management of pro- ceeds and reporting. The use of proceeds stands for utilizing the loan to a green and sustainable project. In the loan documents it should be clearly stated to what the loan is being used for. The environmental benefits should be measurable and able to be re- ported. In the case of refinancing a project it should be stated which part of the project is already financed and which part is being re-financed. The green project’s main goal is to address an environmental concern such as climate change, the decrease of natural resources, loss of biodiversity and so on. It is acknowledged that the definitions of green initiatives or green projects vary in different areas and sectors and that an all-encom- passing definition for a green project can’t be determined. The process for project eval- uation and selection refers to the loan borrowers’ task to disclose to the lender their sustainable objectives. It also includes defining the fitness of the project for the loan and the eligibility criteria. Also, if possible, the briefing includes acknowledgement of poten- tial existing environmental risk. This information is encouraged to be disclosed in the company sustainable reporting. The principle of management of proceeds of a green loan aims in maintaining transparency and the promotion of the integrity of a product. This is achieved by either crediting the loan to a dedicated account or tracking the loan in some other appropriate way. By establishing internal governance for tracking the al- location of the funds for the green projects is a mechanism that contributes to transpar- ency and integrity. The last principle of green loans includes the reporting of the green loans and projects. The reporting is done on an annual basis and a thorough reporting includes a brief de- scription of the green project reported. The expected impact of the project estimated contributes to the transparency aspect (Asia Pacific Market Association et al. 2023). 22 Green loans are also distributed through syndicated green loans. Syndication refers to a group of lenders providing the loan. The group can consist of institutions and investors and the syndicated loan value is much higher when compared to a single loan offered by a single financial institution to a loan receiver. In loan syndication the risk is diversified which aligns with the increased loan amount and the related risk being tolerable for the lenders (Liu, 2023). This study doesn’t take into account syndicated green lending since the focus of this study is individual financial institutions instead of groups and their sus- tainable lending offerings which potentially correlates with profitability. 2.3 Sustainable lending on bank profitability 2.3.1 Bank profitability Bank performance is a combination of internal and external factors. The banking perfor- mance is an outcome of main activities which the business of the banks consists of. These activities are collecting funds as savings from the public and channeling funds to the public as credit or in other forms. In short banking performance reflects the efficiency of bank operating and achieving its financial goals that are measured with different KPIs. The internal factors that affect the activities carried out by a bank are such that the banks have an influence into. The internal factors are influenced by the banks management, and internal governance. The external factors are such that the bank has no control over. These are higher in risk and occur in the macroeconomic sector as inflation, interest rate or GDP growth for example (Indriastuti & Muharam, 2020). The European Central Bank has determined different determinants that affect bank performance. These are the banks earnings or profitability, competitive strategy chosen by the bank, efficiency of the bank, diversification and adequate management. The competitive strategy is referring to the methods that the bank uses to differentiate from its competitors or for finding a competitive advantage in comparison to them. Efficiency is explained as the variation between a set of prices and quantities of inputs and outputs that align with the chosen strategy and has an effect on profitability. In this connection the ECB emphasizes the increased efficiency of larger banks such as commercial banks in comparison to smaller 23 local savings banks for example. Diversification is brought up as sources that the institu- tions have for income that contributes to profitability. Last an appropriate management of bank capital has an effect on bank performance by affecting future availability on funding for lending decisions. Capitalization is found to have an impact in profitability and it also affects banks credit rating. Credit rating has an significant influence on the cost of funding for banks. All these factors are related to the internal factors that the banks can affect (European Central Bank, 2005). The macroeconomic factors or the ex- ternal factors impact the bank profitability through effects of net income and the ability of borrowers to pay back. Repayment issues affect the credit risk of banks and are pre- sented also as defaulted loans on annual basis. Negative effects on bank profitability caused by external factors may result in banks reducing lending and in a bigger perspec- tive lead to a large scale financial instability (von Peter, 2009). The most essential aspect in measuring bank performance is to measure the ability of a bank to create profit or profits from multiple conducted activities (European Central Bank, 2005). 24 3 Literature review This literature review will present the previous research conducted that is related to the subject of sustainable lending and bank performance. It also includes the theories and methodologies that were used in previous research to study the subject that could be utilized for the needs of this study. 3.1 Current state of research When it comes to green financing instruments, green bonds were first issued in 2007 and have since represented a green investment in Europe and around the world (Euro- pean Parliament, 2022). Several studies that focus on green bonds are available and the subject has been studied from many angles. Green lending however as a green financial instrument has been studied mostly in Asia in relation to regulative sustainability enforc- ing policies and their effects on financial institutions. A study that would investigate sus- tainable lending and its effect on bank profitability in European banks that are either commercial banks or offer commercial banking services hasn’t yet been made with this exact focus. This would be the research gap that this study is primarily aiming to fill. A study has been conducted that focused on syndicated green lending affecting bank per- formance and risk. This study included 217 institutions providing syndicated green lend- ing during the years 2010-2020. The majority of the banks chosen to the study were located in Asia (81%) and others around the world. The findings for the study were that a higher concentration of green lending of a financial institution has a connection to lower profitability. The study also concluded that green lending accompanies a moderate default risk and a lower credit risk. In the case of more collateralization and a longer duration for green lending the performance measure ROA was increased. The study used a panel data method with bank related variables such as green lending propensity, size, efficiency, liquidity, performance, default risk, nonperforming loan ratio and credit pro- visioning. The study results indicate that the relationship between green lending and bank performance isn’t unambiguous (Del Gaudio et al. 2022). This study contributed to 25 the current one by implying that banking performance could potentially be linked to sus- tainable lending if the time period for the lending was longer. A second study with the focus of the impact of green lending on bank performance in relation to small and medium size company financing was conducted including the time frame of 2011 to 2021. The study examined this bank performance in the BRIC countries which includes Brazil, Russia, India and China. The method used was panel data method that included 115 banks in the year 2011 and 137 in the year 2021. This means that the study had an unbalanced panel and the entities in the study were observed a different number of times. The results of the study were that a positive relationship between green small and medium enterprise lending and net interest margin exist (Mirza et al. 2023). Green lending has mostly been studied in relation to sustainable policies and potential credit risk caused by the policy’s aim of increasing green lending. The launch of China’s green Credit Policy in 2007 did interest a lot of researchers to find out how the launch of a new greener policy would reflect on bank credit risk. The initiative behind Green Credit Policy was to instruct banks to favor sustainable businesses when issuing credit instead of businesses that weren’t sustainable. China has been a forerunner in distributing green finance and the government set policies have been contributors for the advancement (Zhou et al. 2022). The green credit policy launch has been in the background in the studies conducted about Chinese banks and credit risk in relation to green lending. One of such studies also focused in investigating how the regulations affected bank solvency of individual finan- cial institutions and the resilience of the financial system. The financial crisis during 2007-2008 is also considered in many of the studies by reflecting the distrust of the pub- lic towards the financial sector. The sample in the study consisted of 41 Chinese banks and the time period for the observed green lending was during 2007-2018. The study found that the proportion of green lending offered by a bank depends highly on the size 26 and structure of state ownership. The study did consider all the different banking sys- tems in China. These include the central bank, supervisory authority, commercial banks and policy banks. The conclusion was that the policy reduced credit risk for such institu- tions that were majorly state owned. This implied of an existing information and exper- tise asymmetry that was preventing city and regional banks from accessing these re- sources to evaluate credit risk of green lending more properly (Zhou et al. 2022). This study was very beneficial for the current one. The future research propositions included an identified research gap that was the implementation of green lending and its effect on bank performance across regions. This current study agreed on the existing research gap and focused especially on sustainable lending and bank performance in an area where such research hadn’t been conducted. Another study on a similar subject focused on the stock price crash risk where the un- derlying phenomena is a green credit reform in China (Chen et al. 2023). Studies related to green lending haven’t only been focused on Asia. The relationship of green lending to credit risk in banks has also been studied regionally in the United Arab Emirates (Al- Qudah et al. 2023). A study has also been conducted to examine if European bank’s efforts to build a repu- tation for CSR benefits performance. The study concludes that CSR focused banks had experienced an improvement in their economic performance compared to their peers that didn’t concentrate in sustainable CSR strategies (Forcadell & Aracil, 2017). Another study related to green lending was conducted to find out what kind of an impact a green credit policy set by Chinese officials had on 62 commercial banks during the time period of 2013 to the year 2020. The green credit policy means a policy that encourages banking institutions to create green credit and to include more environmental and social risk management to their operations. The study concluded that policies for green credit do benefit commercial banks’ profits and thus performance (Gao & Guo, 2022). 27 3.2 Sustainable lending and bank performance 3.3 Hypotheses development The previous studies did indicate that there would exist a research gap which would in- vestigate sustainable lending and bank performance. As most of the previous research was concentrated in Asia it was suitable to find an area where much previous research hadn’t been conducted. This was a starting point for the current research. The area of the European Union was chosen since empirical research showed that mostly big sized organizations are as diversified in relation to their services that they would in- clude and report sustainable finance. A brief research in the Nordic area implied that the sample of sustainable lending wouldn’t be sufficient for the needs of the current re- search. All the banks in the sample consist of well-resourced financial institutions that locate in the EU. All the bank types in the sample are commercial, or they offer commercial bank- ing services which strives them for making profit for their shareholders. This is an im- portant aspect in the study since it investigates bank profitability. The previous research can be interpreted to have implied that a correlation between sustainable lending and bank performance could exist but the nature of this correlation varies depending on the variables considered in the study. Three hypotheses were formed based on the previous research. The first hypotheses investigates whether a positive correlation exists between sustainable lending and bank performance. The second hypotheses investigates if an in- creasing time period of sustainable lending distribution correlates with performance and the last analyzes if an increased amount of sustainable lending distributed correlates with performance. 28 4 Theoretical framework This theoretical framework introduces the key performance measure and other measures that can have an affect to bank performance. The dependent variable is ROA, the independent variables SLTL and SLTA. The measures for the control variable are also defined in this chapter. ROA as a performance measure was introduced in previous re- search conducted of sustainable lending in the study conducted by Del Gaudio et al. (2022). The control variables were chosen based on the studies conducted by Del Gaudio et al. (2022) and Zhou et al. (2022). 4.1 Performance ratios 4.2 ROA, return on assets The focus of this study is on finding out if sustainable lending affects bank profitability. As a performance ratio, this study chose the return on assets (ROA). The ratio shows the connection between organizations net income and its total assets. The ratio is expressed as a percentage. The ratio presents an organizations efficiency in utilizing its total assets into generating profit (Petersen & Schoeman, 2008). The formula for return on assets is following: 𝑅𝑂𝐴 = 𝑁𝑒𝑡 𝑖𝑛𝑐𝑜𝑚𝑒 𝑇𝑜𝑡𝑎𝑙 𝐴𝑠𝑠𝑒𝑡𝑠 4.3 ROE, return on equity Return on equity can be defined as after-tax net income which is divided with average shareholder equity. The ratio is expressed as a percentage. The ratio is a metric for the evaluation of investment returns. When this ratio is compared amongst peers in the in- dustry it is possible to evaluate the competitive advantage that might exist. It also 29 possibly indicates how the management of the company is investing its equity to accom- plish company growth (Petersen & Schoeman, 2008). 𝑅𝑂𝐸 = 𝑁𝑒𝑡 𝑖𝑛𝑐𝑜𝑚𝑒 𝑆ℎ𝑎𝑟𝑒ℎ𝑜𝑙𝑑𝑒𝑟𝑠′𝐸𝑞𝑢𝑖𝑡𝑦 4.4 Sustainable loan ratios The banks chosen for this study vary a lot by their characteristics. The banks differ in size, the amount of sustainable lending offered and other financial ratios calculated based on annual financial information. For making the sustainable lending data more comparable amongst the banks in this study, two ratios were formatted. The study of Zhou et al. (2022) introduced a green loan variable type which was now utilized in this current study. The first ratio includes the bank specific annual sustainable lending amount in terms of the overall offered lending (SLTL). This way the observed sustainable lending is demon- strated as a proportion in the context of the overall lending. 𝑆𝑢𝑠𝑡𝑎𝑖𝑛𝑎𝑏𝑙𝑒 𝐿𝑜𝑎𝑛 = 𝑆𝑢𝑠𝑡𝑎𝑖𝑛𝑎𝑏𝑙𝑒 𝑙𝑜𝑎𝑛 𝑇𝑜𝑡𝑎𝑙 𝑙𝑜𝑎𝑛 The other ratio presenting the amount of sustainable lending annually within a specific financial institution is divided with its overall assets (SLTA). This ratio also puts the sus- tainable lending within proportion of a specific financial institution and makes the value more comparable with other financial institutions the study considers. 𝑆𝑢𝑠𝑡𝑎𝑖𝑛𝑎𝑏𝑙𝑒 𝐿𝑜𝑎𝑛 = 𝑆𝑢𝑠𝑡𝑎𝑖𝑛𝑎𝑏𝑙𝑒 𝑙𝑜𝑎𝑛 𝑇𝑜𝑡𝑎𝑙 𝑎𝑠𝑠𝑒𝑡𝑠 30 4.5 Control variable, leverage The bank leverage ratio used in the study of Zhou et al. (2022) assess the extent that a bank funds its assets with equity compared to its debt. This metric indicates financial stability and risk. In general, a higher ratio implies a lower financial risk since the bank isn’t relying strongly on debt, which would be riskier. A higher ratio suggests that the bank is less reliant on debt, which generally implies lower financial risk (Chen, 2022). The leverage ratio was retrieved from Orbis database to this study. The formula used is the following: 𝐿𝑒𝑣𝑒𝑟𝑎𝑔𝑒 = 𝑇𝑜𝑡𝑎𝑙 𝑒𝑞𝑢𝑖𝑡𝑦 𝑇𝑜𝑡𝑎𝑙 𝑙𝑖𝑎𝑏𝑖𝑙𝑖𝑡𝑖𝑒𝑠 31 5 Data and research methodology This chapter will introduce the data used in this study and the methodology that the data was analyzed with. This chapter also includes the expected results along with the con- ducted correlation analyses. 5.1 Data sources and description of data For this study a data pool of 69 financial institutions located in 15 European countries was chosen. The data consists of 337 annual observations. The data aligns with the cho- sen institutions to the stress test conducted by the European Banking Authority in 2023 (EBA, 2023). The EBA conducted the bank stress test in cooperation with the European Systemic Risk Board (ESRB), European Central Bank (ECB) and the European Commission. The reason why an identical financial institution set was chosen for this study is because the EBA surveys banks whose assets represent 75% of EU banks’ total assets. For this study it was crucial to find institutions that have a big impact on the economy and that would have enough resources to also include sustainable lending products amongst their other services. Investigating smaller financial institutions in the EU area indicated that it isn’t common for very small financial institutions to offer sustainable lending. Most of the banks chosen for this study are commercial banks or offer commercial banking ser- vices. The ECB stated in their financial stability review that the euro area includes a wide range of financial institutions that differ by size and ownership structure. The big varia- tion amongst the banks is an aspect that potentially complicates an analysis measuring profitability in the European banking sector when such explanatory factors such as size and ownership is used for measurement (ECB, 2005). Prior research conducted that re- lates to sustainable lending lacks further research in the EU area. When searching for sustainable loan data from different financial institutions around Europe it came appar- ent that sustainable lending information can be difficult to find. As stated previously in this study, loans that qualify as sustainable lending according to a general definition isn’t a financial instrument that all banking institutions include in their loan portfolios. It is partly a matter of to what kind of financial institutions banks want to profile themselves 32 as when serving their customers. Choosing the EBAs set of financial institutions raised the probability of finding reported sustainable lending information in their financial and sustainable reports. A summarization report of sustainable lending data from European institutions wasn’t available when this study was conducted. This led to a data search by examining publicly published annual and sustainability reports for each institution sepa- rately covering the whole five year time period. The data used was end year data. The method for the study was a panel data analysis. Since the data gathering method is by nature time consuming, a pool of 70 institutions was chosen to provide an overview to the subject. From the initial data pool the country Norway was excluded since Norway isn’t part of the EU, though it is of EEA, so the same legislation doesn’t similarly apply to the country as it does to all EU countries. The time period for the data gathered was between 2018-2022. The year 2023 was excluded since during the time of conducting this study, not all the banks had published their annual statements or ESG reports. ESG reports might be published late after the reporting period, some in the end of the new reporting period and it varies greatly amongst financial institutions. The nature of the panel data set was unbalanced that was caused by many reasons. The unbalanced data set here refers to missing values from the data set as a whole. Reasons for missing values were for example that the financial institution didn’t report sustainable lending during one observation year. There were also cases where some financial institutions didn’t in- clude sustainable lending at all in their annual reports and financial statements. In the different regression analyses the missing value observations were left out of the analysis, which led to less observations accounted for. Because the regulation regarding the re- porting on sustainable activities is now mandatory to large companies within the EU, it is likely that the institutions with missing information will start reporting such data in the near future. In some cases the data referring to sustainable lending was too inconsistent or difficult to determine for the study and was therefore excluded. In these situations, the data referring to sustainable lending could include another kind of financial data which causes discrepancies amongst the whole data set if included. All values are in Eu- ros since most annual reports that this study utilized are reported in Euros. 33 The specific time period was chosen since the number of banks reporting sustainable lending is more common during the time period than before the year 2018 which the gathered data also indicates. Table 1. Bank distribution regionally in the study Region in Europe Country Number of banks Bank type Central and Eastern Austria 2 commercial, investment Western Belgium 2 commercial, insurance Western Germany 14 commercial, cooperative, investment, savings Western Denmark 4 commercial Southern Spain 8 commercial Northern Finland 2 commercial, retail Western France 7 commercial, mutual, retail, postal Southern Greece 4 commercial, retail Central and Eastern Hungary 1 commercial Western Ireland 4 commercial, investment Southern Italy 8 commercial, retail Western Netherlands 4 commercial, cooperative Central and Eastern Poland 2 commercial Southern Portugal 2 commercial Northern Sweden 5 commercial, retail The sustainable lending data is analyzed in relation to banking profitability. The perfor- mance ratio chosen for the study is return on assets (ROA) which represents the depend- ent variable. The ratios concerning the financial institutions in the study were provided by the Bureau van Dijks Orbis database. A universal global format was used when 34 accessing the data. In this way any reporting differences were avoided. Access to this database was granted by the University of Vaasa. Figure 1. The average sustainable lending distribution, in thousands € Figure 1 demonstrates the yearly sustainable lending distribution. It indicates that on average the lending has grown during the study period. A decline can be observed during 2020 assumingly as a consequence of the COVID19 pandemic. The last two years of the study represent values very close to one another. The recent changes in legislation might contribute in the future to the trend of increasing sustainable lending. Sustainable lending data represents independent variables in this study. The sustainable lending data was formed as two different ratios the first being sustainable loans to total loans (SLTL) and the second sustainable loans to total assets (SLTA). This enabled to look into the proportion of sustainable lending from two different points of view. As the con- trol variables this study used total assets (TA), cost to income ratio (CIR), liquid assets on deposits and short term funding (LIQ), non-performing loans on gross loans (NPL%) and leverage (LEV). The control variables are used for controlling for factors that could impact the outcome of the study. 35 The annual observations concerning all banks don’t align. This means that not all varia- bles presenting SLTL or SLTA are available resulting to fewer observations in some anal- yses. 5.2 Methodologies This study uses panel data analysis for studying the research questions. The Breusch- Pagan-Godfrey test was conducted to all regression analyses to reveal if heteroscedas- ticity was present. The p-values indicated a value above the 0.05 significance level and heteroscedasticity wasn’t detected. This resulted in continuing with OLS regression anal- ysis with all regression analyses. The empirical part of this study begins with a summary statistics of all data gathered and also including all main regions in Europe. This approach was chosen for two reasons. Displaying summary statistics from all 15 countries separate wasn’t from a data analysis point of view reasonable since some countries only included one or two banks which was insufficient for statistical analysis of the observations. Second, uniting observations regionally combines information that possibly simplifies the analysis of the results when including for major descriptive statistics regionally instead of displaying all countries sep- arately. Table 2. Variable listing an definitions Variable Definition ROA Return on assets SL/TL Sustainable loans / Total loans SL/TA Sustainable loans / Total assets TA Total assets LEV Leverage (Total equity / Total liabilities) LIQ Liquid assets on deposits and short-term funding CIR Cost to income ratio 36 NPL% Non-performing loans on gross loans (Impaired loans / Gross customer loans & advances) 5.3 Panel data method This study uses a panel data model as a method for analyzing time series data. The tra- ditional panel data method is chosen because this study’s interest is in observing the effects of a certain time period which doesn’t take into account dynamic effects of time lags. The panel data model connects both a cross-section element and a time element to the estimation since there are several bank observations from a five-year time period. In this study the cross-section data consists of bank specific factors. Since the data in- cludes different banks in different regions the variation between the banks can be visible. The time element includes those occurrences in the macroeconomic environment that might be reflected on bank profitability. OLS regressions are run for estimating the first hypotheses which analyses whether sus- tainable lending is correlated to bank profitability. The regression equation for assessing the first hypothesis is of the following form: 𝑃𝑟𝑜𝑓𝑖𝑡𝑡+1 = 𝛽0 + 𝛽1𝑆𝐿𝑇𝐿_𝐴𝐿𝐿𝑡 + 𝛽2𝑆𝐼𝑍𝐸𝑡 + 𝛽3𝐿𝐸𝑉𝑡 + 𝛽4𝐿𝐼𝑄𝑡 + 𝛽5𝐶𝐼𝑅𝑡 + 𝛽6𝑁𝑃𝐿𝑡 + 𝑒𝑡+1 Profit it represents the dependent variable ROA in period t +1. 𝛽0 represents the null hypotheses. The independent variable SLTL represents a ratio formed by sustainable lending in relation to total loans or gross loans. Size, leverage, liquidity, cost to income ratio and non-performing loans ratio are all control variables for controlling other factors. The first regression model also includes another regression equation of the following form: 37 𝑃𝑟𝑜𝑓𝑖𝑡𝑡+1 = 𝛽0 + 𝛽1𝑆𝐿𝑇𝐴_𝐴𝐿𝐿𝑡 + 𝛽2𝑆𝐼𝑍𝐸𝑡 + 𝛽3𝐿𝐸𝑉𝑡 + 𝛽4𝐿𝐼𝑄𝑡 + 𝛽5𝐶𝐼𝑅𝑡 + 𝛽6𝑁𝑃𝐿𝑡 + 𝑒𝑡+1 This regression equation also includes the second dependent variable that is also a ratio for sustainable lending in relation to total assets. Including both ratios in the study was done for receiving more information about sustainable lending. The second regression equation was formed to analyze if an increasing number of years that sustainable lending was distributed has an effect on bank profitability. The regres- sion equation for assessing the second hypothesis is of the following forms: 𝑃𝑟𝑜𝑓𝑖𝑡𝑡+1 = 𝛽0 + 𝛽1𝑆𝐿𝑇𝐿_𝐿𝑂𝑁𝐺𝑡 + 𝛽2𝑆𝐼𝑍𝐸𝑡 + 𝛽3𝐿𝐸𝑉𝑡 + 𝛽4𝐿𝐼𝑄𝑡 + 𝛽5𝐶𝐼𝑅𝑡 + 𝛽6𝑁𝑃𝐿𝑡 + 𝑒𝑡+1 and 𝑃𝑟𝑜𝑓𝑖𝑡𝑡+1 = 𝛽0 + 𝛽1𝑆𝐿𝑇𝐴_𝐿𝑂𝑁𝐺𝑡 + 𝛽2𝑆𝐼𝑍𝐸𝑡 + 𝛽3𝐿𝐸𝑉𝑡 + 𝛽4𝐿𝐼𝑄𝑡 + 𝛽5𝐶𝐼𝑅𝑡 + 𝛽6𝑁𝑃𝐿𝑡 + 𝑒𝑡+1 The regression equation includes a new variable controlling for the time that sustainable lending has been distributed. For the variable being able to present this information as different time periods that the data sample includes, the data was divided into three different categories representing the time of SL distribution. Caused by the small amount of SL observations in this study, it wasn’t possible to include all five years as separate analyses. Because of this reason, years one or two, three or four and five years of SL distribution was divided as three different categories. The variable representing five years is SLLONG that the first regression equation for H2 includes. Again the regression equation was run for both sustainable lending variables SLTL and SLTA separately. The second regression including the variable for three or four years SL distribution is of the following forms: 𝑃𝑟𝑜𝑓𝑖𝑡𝑡+1 = 𝛽0 + 𝛽1𝑆𝐿𝑇𝐿_𝑀𝐼𝐷𝑡 + 𝛽2𝑆𝐼𝑍𝐸𝑡 + 𝛽3𝐿𝐸𝑉𝑡 + 𝛽4𝐿𝐼𝑄𝑡 + 𝛽5𝐶𝐼𝑅𝑡 + 𝛽6𝑁𝑃𝐿𝑡 + 𝑒𝑡+1 38 and 𝑃𝑟𝑜𝑓𝑖𝑡𝑡+1 = 𝛽0 + 𝛽1𝑆𝐿𝑇𝐴_𝑀𝐼𝐷𝑡 + 𝛽2𝑆𝐼𝑍𝐸𝑡 + 𝛽3𝐿𝐸𝑉𝑡 + 𝛽4𝐿𝐼𝑄𝑡 + 𝛽5𝐶𝐼𝑅𝑡 + 𝛽6𝑁𝑃𝐿𝑡 + 𝑒𝑡+1 Here the variable SLMID represents bank observations that are placed in the middle of distribution year categories which accounts for three or four years. The regression equa- tion was run for both profit variables and both SL variables. The regression equation that studies the observations with the shortest SL distribution is of the following forms: 𝑃𝑟𝑜𝑓𝑖𝑡𝑡+1 = 𝛽0 + 𝛽1𝑆𝐿𝑇𝐿_𝑆𝐻𝑂𝑅𝑇𝑡 + 𝛽2𝑆𝐼𝑍𝐸𝑡 + 𝛽3𝐿𝐸𝑉𝑡 + 𝛽4𝐿𝐼𝑄𝑡 + 𝛽5𝐶𝐼𝑅𝑡 + 𝛽6𝑁𝑃𝐿𝑡 + 𝑒𝑡+1 and 𝑃𝑟𝑜𝑓𝑖𝑡𝑡+1 = 𝛽0 + 𝛽1𝑆𝐿𝑇𝐴_𝑆𝐻𝑂𝑅𝑇𝑡 + 𝛽2𝑆𝐼𝑍𝐸𝑡 + 𝛽3𝐿𝐸𝑉𝑡 + 𝛽4𝐿𝐼𝑄𝑡 + 𝛽5𝐶𝐼𝑅𝑡 + 𝛽6𝑁𝑃𝐿𝑡 + 𝑒𝑡+1 Here the variable SLSHORT represents bank observations for the shortest SL year distri- bution category of one or two years. The regression equation was run for both SL varia- bles. For the last hypothesis to analyze if an increasing amount of sustainable lending distrib- uted is correlated with bank profitability the following equations were formed: 𝑃𝑟𝑜𝑓𝑖𝑡𝑡+1 = 𝛽0 + 𝛽1𝑆𝐿𝑇𝐿_𝐻𝐼𝐺𝐻𝑡 + 𝛽2𝑆𝐼𝑍𝐸𝑡 + 𝛽3𝐿𝐸𝑉𝑡 + 𝛽4𝐿𝐼𝑄𝑡 + 𝛽5𝐶𝐼𝑅𝑡 + 𝛽6𝑁𝑃𝐿𝑡 + 𝑒𝑡+1 and 𝑃𝑟𝑜𝑓𝑖𝑡𝑡+1 = 𝛽0 + 𝛽1𝑆𝐿𝑇𝐴_𝐻𝐼𝐺𝐻𝑡 + 𝛽2𝑆𝐼𝑍𝐸𝑡 + 𝛽3𝐿𝐸𝑉𝑡 + 𝛽4𝐿𝐼𝑄𝑡 + 𝛽5𝐶𝐼𝑅𝑡 + 𝛽6𝑁𝑃𝐿𝑡 + 𝑒𝑡+1 , 𝑃𝑟𝑜𝑓𝑖𝑡𝑡+1 = 𝛽0 + 𝛽1𝑆𝐿𝑇𝐿_𝑀𝐸𝐷𝑡 + 𝛽2𝑆𝐼𝑍𝐸𝑡 + 𝛽3𝐿𝐸𝑉𝑡 + 𝛽4𝐿𝐼𝑄𝑡 + 𝛽5𝐶𝐼𝑅𝑡 + 𝛽6𝑁𝑃𝐿𝑡 + 𝑒𝑡+1 and 39 𝑃𝑟𝑜𝑓𝑖𝑡𝑡+1 = 𝛽0 + 𝛽1𝑆𝐿𝑇𝐴_𝑀𝐸𝐷𝑡 + 𝛽2𝑆𝐼𝑍𝐸𝑡 + 𝛽3𝐿𝐸𝑉𝑡 + 𝛽4𝐿𝐼𝑄𝑡 + 𝛽5𝐶𝐼𝑅𝑡 + 𝛽6𝑁𝑃𝐿𝑡 + 𝑒𝑡+1 , 𝑃𝑟𝑜𝑓𝑖𝑡𝑡+1 = 𝛽0 + 𝛽1𝑆𝐿𝑇𝐿_𝑀𝑂𝐷𝑡 + 𝛽2𝑆𝐼𝑍𝐸𝑡 + 𝛽3𝐿𝐸𝑉𝑡 + 𝛽4𝐿𝐼𝑄𝑡 + 𝛽5𝐶𝐼𝑅𝑡 + 𝛽6𝑁𝑃𝐿𝑡 + 𝑒𝑡+1 and 𝑃𝑟𝑜𝑓𝑖𝑡𝑡+1 = 𝛽0 + 𝛽1𝑆𝐿𝑇𝐴_𝑀𝑂𝐷𝑡 + 𝛽2𝑆𝐼𝑍𝐸𝑡 + 𝛽3𝐿𝐸𝑉𝑡 + 𝛽4𝐿𝐼𝑄𝑡 + 𝛽5𝐶𝐼𝑅𝑡 + 𝛽6𝑁𝑃𝐿𝑡 + 𝑒𝑡+1 Here a new variable was created for representing the amount of sustainable lending. For being able to represent the data, the bank observations were divided into three catego- ries that divided the SL lending in HIGH, MEDIUM and MODERATE amounts. The equa- tions were run for the profit ratio ROA and for three different categories for SL distribu- tion by value from highest to lowest amount. All different categories include almost the same amount of observations and the amount division in € for high distribution was 223000000 - 936893, for medium distributed sustainable lending 6563685 – 506800 and for moderate 2281000-500. The panel data for the study was unbalanced since not all commercial banks have re- ported sustainable lending data in their reports. In the different hypotheses scenarios the missing value observations were left out from the analysis. Voluntary reporting has contributed a lot to this study since sustainable lending data has been made available even if it hasn’t been obligatory to disclose in the earliest years of the study observations. 5.4 Descriptive statistics Descriptive statistics including all data from all bank observations summarizes the entire time period observed in this study. The correlation coefficient does describe the strength and direction of two variables relationship. The range for the represented relationship is from -1 to +1. A positive correlation is indicated by +1 relationship where both variables increase in relation to each other. In a vice versa situation a negative relationship is 40 indicated by a -1 correlation. If no correlation exist between the variables, the correlation in 0 (LaMorte, 2021). Table 3. Descriptive statistics of all banks In table 3 where all bank data is summarized, an overall conclusion can be drawn of the amount that the sustainable lending in relation to total loans (SLTL) and to total assets (SLTA) as a mean represents. Sustainable lending is only a part of a financial institutions lending products or instruments provided for customers of the overall lending portfolio. It doesn’t represent the overall sustainable activities carried out in the organization since banks offer other kinds of different sustainable products such as a green bond for exam- ple. The mean for sustainable lending in relation to all loans is 9.3%. The median of 0.016 indicates that a notable portion of the banks in the study have relatively low ratios of sustainable lending. The maximum value which is 2.891 indicates that some banks in the study, that could also be called as outliers have a significant proportion of loans that can be categorized as sustainable. Including banks with very high proportions of SL in the study can significantly influence the mean value of SL. It is though important for the sake of the overall distribution of the data to also include those financial institutions with a large proportion of SL. The minimum value of 0.000 means that the observations also include banks that offer no sustainable loans at all. The value for standard deviation is 41 0.430. The value indicates that there is some spread in the SL lending data but it is not excessively wide. According to the above mentioned values for SLTL the SL in contrast to all lending isn’t a significant proportion. When gathering the SL data it became apparent that it was unreasonable to include SL data previous the year 2018 because the lending type at that point was very scarce. Sustainable lending in relation to total assets (SLTA) indicates notable differences amongst descriptive statistics. The mean of 0.022 is lower than in SLTL which indicates that the proportion of sustainable lending is much larger in comparison to the loan port- folio than to the total assets of the bank. The median value of 0.010 indicates a similar observation. The max and min value of SLTA indicates a similar observation to what was observed with SLTL. As the standard deviation was a smaller value on SLTA it can be in- terpreted that possibly a greater variability exists amongst incorporating sustainable lending in loan portfolios than in total assets. The summary indicates overall that there’s a great variability on the amount of sustainable lending offered amongst the banks and that the sustainable lending stands out more notably when compared to overall loan portfolio than it is in comparison to total assets. The descriptive statistics concerning the performance measure ROA implies that the banks in the study are profitable and even the least profitable banks are making profit. Since all the banks chosen for the study are observed by the EBA due to their size it isn’t surprising that these institutions that mostly offer commercial banking services are prof- itable. Standard deviation concerning both ratios suggest variability that could be a re- sult of differences amongst the banks operations and strategies for example that gener- ate the profit observed here. The control variables descriptive statistics suggest that many of the banks in the study have quite high levels of debt financing in relation to their equity. The banks seem to have a high level of liquidity but also high level of operating expenses in relation to their income. The last ratio, non-performing loans (NPL) indicate that in general there are many banks that have quite a low level of non-performing loans when compared to total loans. The maximum value does though suggest that amongst some banks the NPL ratio is much higher than in the overall observations. 42 Table 4. Descriptive statistics of northern region, Finland and Sweden The study now briefly observes the differences between different regions where the banks are located. The banks were divided into four main regions in Europe that are eastern Europe, southern Europe, western Europe and northern Europe. This division was done for being able to observe differences amongst the countries. Since the study included initially 70 banks, the observation amount doesn’t allow each country specific interpretation. Combining observations in regional areas does allow summarization of results in a more brief manner. The descriptive statistics for the northern region concern- ing sustainable lending implies that even if the region includes the least countries within a region the mean of SLTL isn’t the smallest in the sample. This is also true with the mean of SLTA. In the Nordic region sustainable lending is offered quite moderately in compar- ison to the all observation mean. The banks in the Nordic region are not amongst the biggest by asset size within the study observation. 43 Table 5. Descriptive statistics of central and eastern region, Poland, Hungary and Austria The central and eastern region holds the least banks and observations for SLTL and SLTA. This resulted in the inability of counting standard deviation amongst the variables in the region. This region includes generally the smallest banks within the study in terms of total assets. Table 6. Descriptive statistics of western region, France, Germany, Denmark, Nether- lands, Belgium, Ireland 44 The western European region is the area where most of the banks in the study locate. It is also the area with the largest concentration of total assets with the strongest individual banks liquidity vice. The region holds a large number of banks that don’t offer sustaina- ble lending at all which the min value for SLTL and SLTA indicate. In contrast the region holds banks that include the largest portion of SL in the whole study when assessed to- wards all loans and total assets. Table 7. Descriptive statistics of southern region: Italy, Spain, Portugal and Greece The last region includes second most banks the study observed with individual banks that hold large amount of total assets. With regarding this the mean for SLTL and SLTA is very moderate within the organizations. 45 Table 8. Correlation of variables The study used a dependent variable ROA. A correlation matrix was created by including the dependent variable, independent variables and the control variables. The correlation matrix suggest that a very weak negative correlation exists between SLTL and ROA. This means that in the case that SLTL is increased slightly then ROA is decreased slightly. However, in the vase of SLTA and ROA the correlation is positive while also being very weak. The descriptive statistics were added for providing an overview to the banks that this study focuses on and to the trend of sustainable lending regionally. This insight provides a starting point for the main study that investigates whether sustainable lending has an effect on bank performance. 46 6 Empirical results 6.1 Regression analysis For determining whether the fixed effects model or the random effects model would be more efficient for this analysis the Hausman test was conducted for both dependent variables. The Hausman test indicated that the random effects model would be more efficient and appropriate for this study. The dependent variable ROA was tested with the Hausman test where the p-value was above the commonly used significance level of 0.05. This led to failing to reject the null hypothesis and using the random effects model in the study for the dependent variable. The results for regression 1 indicate that there is a negative relationship between the sustainable lending variable SLTL and ROA variable and that the value is not statistically significant. The second variable for sustainable lending SLTA in relation to ROA suggests there would be a positive relationship between the variables. However, the value isn’t statistically significant either. Amongst the control variables leverage and cost to income ratio, the correlation is positive and statistically significant. Total assets and non-per- forming loans are negatively correlated to ROA with statistical significance. In terms of H1 the first regression analysis don’t support the hypothesis. The hypothesis is rejected caused by the lack of positive correlation. 47 Table 9. The result of regression 1 The second regression analysis was conducted for analyzing the effect of time during which the sustainable lending has been distributed. The three categories for sustaina- ble lending time period were five years, three or four years and two or one year. For the maximum time period of sustainable lending distribution the results indicate a pos- itive correlation towards ROA with both SL variables. The values lack statistical signifi- cance. Only cost to income ratio is positively correlated to ROA with statistical signifi- cance. In the case of a middle time period distribution of four to three years both SL variables are positively correlated with performance but without statistical significance. Cost to income ratio is negatively correlated with statistical significance. The shortest time period indicates a negative correlation with both SL variables. Cost to income vari- able is only marginally significant with a negative correlation towards ROA. 48 Table 10. The results of regression 2 The last regression analysis was conducted for analyzing the effect of increasing sus- tainable lending amount distributed. The three categories for sustainable lending was high amount, medium amount and moderate amount. Each SL distribution was divided bank wise so that each bank total SL distribution could be compared with the other bank observations. The results for the highest distribution amount indicates a negative correlation with SLTL towards ROA. The value doesn’t have statistical significance. SLTA is positively correlated but lacks statistical significance. Cost to income ratio is nega- tively correlated with high statistical significance. With the MED scenario both SL varia- bles are negatively correlated with ROA including no statistical significance. No varia- bles in the scenario include statistical significance. In the case of moderate SL lending both SL variables are positively correlated but without statistical significance. Only the cost to income variable is positively correlated with statistical significance. In terms of H2 in the second regression analysis is rejected caused by the lack of statistical signifi- cance despite the existence of positive correlation in different scenarios. 49 Table 11. The results of regression 3 6.2 Discussion The results for the different regression analyses in general don’t support the assumption for sustainable lending being correlated with positive bank performance. The first re- gression analysis analyzed whether a positive correlation would exist between sustaina- ble lending and performance. The results for the analysis didn’t support this assumption since statistically significant positive correlation didn’t appear. This led to rejecting the first hypotheses. The second regression analysis analyzed whether an increased time pe- riod that the lending had been offered would have an effect on bank performance. The findings indicate positive correlation when the time period is longer for SL distribution. The results lack statistical significance which resulted in rejecting also the second hy- pothesis. The last regression analysis analyzed whether an increased amount of SL of- fered during the study period affects bank performance. With the two SL variables the results differed. With SLTL the correlation was negative in the HIGH scenario. With the SLTA variable in the HIGH scenario the correlation was positive though without statistical significance. With the most moderate sustainable lending amount the SL variables are both positively correlated with ROA. The values don’t include statsistical significance. All in all also the third hypothesis is rejected since the results don’t include statistical 50 significance. When interpreting the results different aspects need to be accounted for. Sustainable lending at the time of conducting the research in general doesn’t reflect the majority of assets or loans within each bank. Sustainable lending has increased from the volumes of the initial study year 2018 and by the looks of the reported sustainable lend- ing thus far representing 2024 the trend seems to continue. Changing legislation and an increasing interest from the general public towards sustainability is influencing the banks offered services in the area that this study was focused in. Most of the banks chosen for the study are commercial banks or offer commercial banking services which includes an assumption for a business that is aiming for revenue. These banks also hold the most assets in the area that leads to the assumption of resources far greater than a local sav- ings bank. The existence of resources was crucial for finding a study observation pool of banks than would highly likely offer sustainable lending. Since the findings of this study don’t support the assumption of sustainable lending affecting positively towards bank performance its reasons should be considered. The data for the study indicated that the amount of offered sustainable lending varies greatly amongst the banks in the study. This is natural since also the bank sizes vary amongst the banks. A general observation con- cerning sustainable lending based on the data is that sustainable lending is at this point quite a small proportion when compared to the banks overall assets or lending. If this proportion were to grow strongly in the future a study such as the one conducted now could indicate different results and the impact towards performance could be more sig- nificant. 6.3 Limitations This study has limitations that are relevant to mention. Sustainable lending data has not been easily available and reported in a predeterminant way as financials in financial statements that follow accounting and reporting standards. This has resulted in this study in having sustainable lending information that can include different lending instru- ments varied by the company focus. Some companies haven’t disclosed financial sus- tainable lending information at all. Instead they’ve disclosed information on what the company considers as risks and opportunities related to social and environmental issues. 51 The sustainability disclosures that many of the commercial banks in this research report vary by the focus of the organization and differ also in availability. In the future this is expected to change resulted by the ESRS which has been in force from the beginning of 2024. Another limitation is also unestablished terms for different types of sustainable lending offered. The ESRS and the EU taxonomy can potentially contribute to a more precise usage of the terms in future reporting. At the time of the study the sustainable lending amounts don’t account a large quantity of total assets of the banks or gross loans. The trend until this point seems to point for a growing proportion of sustainable lending amongst banks. When sustainable lending only accounts for a smaller part of the total assets or all loans within the financial institution its effect on the bank can be expected to be marginal. The last limitation observed that has a significance for the study is the short time period that sustainable lending data was able to be gathered from. Financial statements and ESG reports published before the year 2018 didn’t in many cases include sustainable lending information. A larger time period for the study with more observa- tions could’ve affected the results of the study. 52 7 Conclusions The study concludes that sustainable lending doesn’t affect bank profitability with sta- tistical significance. This led to rejecting the first hypothesis. This hypothesis was tested with ROA performance measure and by dividing the two SL ratios to their own analyses. SLTA showed positive correlation towards ROA but lacking statistical significance. The sample size and the available time period for observing sustainable lending very likely affects the research result. A positive correlation might imply that sustainable lending can have potential benefits for the financial institutions. It is likely that with the data available at the time the research was conducted the potential benefits can’t be suffi- ciently captured in the analysis which would be indicated by statistical significance. The second regression analysis also had the result of rejecting the hypothesis. The second regression analysis tested both performance measures and divided both SL ratios to their own analyses. The results indicated that a positive correlation exists mostly when sus- tainable lending is distributed for a longer time period. The results weren’t statistically significant. The second regression analysis can be concluded with similar arguments that applied to the first analysis. Since the value isn’t statistically significant it can only be assumed that sustainable lending contributes positively to a bank’s performance over a longer time period. The performance might also be a result of other factors that the sustainable lending with itself might accompany. For example, a reputational benefit, long term lending increasing loyalty amongst loan receivers and lower default rates could be these positive contributors. With the last regression analysis the results in general indicated a positive correlation in scenarios where sustainable lending had been offered a smaller amount. The values weren’t statistically significant which led to rejecting also the final hypothesis. A positive correlation towards a shorter time period of distributed sustainable lending could indicate that a more cautious starting point could correlate positively with performance. Altering the size and time frame of the observed sustaina- ble lending could also have a significant impact on the results. After rejecting all hypothesis the study concludes that during the time of the study in the EU area there isn’t significant evidence for sustainable lending to affect bank perfor- mance. This study offers instead implications that in the future if the sustainable lending 53 continues with an increasing trend in the financial institutions loan offering it might have a more significant effect to the financial institutions. In general the growing demand and lending sustainable loans is a positive aspect for the environment. With the changing regulation aligning closer with environmental initiatives and goals it is expected that the trend indeed is heading for increased demand for sustainable loans and green financial instruments in general. This offers many avenues for future research within the subject. In future research it is possible to include larger datasets that take into account bigger time periods than this study was able to. Also controlling for other factors that this study didn’t take into account could offer more information and a better understanding of the relationship of sustainable lending towards bank performance. Since this study seems to be one of the few ones that investigate the EU area it could be beneficial to continue the research to fill this research gap. Sustainable and green lending has for the most part been studied from the risk perspective in which the changing legislation has made their mark on, especially in Asia. The year 2024 is the first one in the EU that requires large companies to report their sustainable activities more thoroughly annually. 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