OCDE - Leveraging AI and digital tools for SME sustainable finance

Please cite this paper as: OECD (2026-06-26), “Leveraging AI and digital tools for SME sustainable finance”, OECD SME and Entrepreneurship

Papers, No. 80, OECD Publishing, Paris. http://dx.doi.org/10.1787/e8fb0d10-en OECD SME and Entrepreneurship Papers No. 80 Leveraging AI and digital tools for SME sustainable finance OECD2025 D4SME Survey OECD SME and Entrepreneurship PapersOECD SME and Entrepreneurship Papers Leveraging AI and digital tools for SME sustainable finance 2025 D4SME Survey OECD SME and Entrepreneurship Papers OECD SME and Entrepreneurship Papers Leveraging AI and digital tools for SME sustainable financeOECD SME and Entrepreneurship Papers

Leveraging AI and digital tools for SME sustainable finance

Small and medium-sized enterprises (SMEs) face challenges tapping into sustainable finance. The principal obstacles are informational: sustainability data are costly to generate, difficult to verify and fragmented across reporting frameworks. Furthermore, the administrative burden of originating and monitoring small-ticket sustainable loans constrains the flow of finance to SMEs. This paper examines how artificial intelligence (AI) and digital tools can help address these bottlenecks across the financing lifecycle. It looks at how these tools can contribute to sustainability data generation and reporting on the SME side, and to origination, credit assessment and portfolio monitoring within financial institutions. Drawing on country examples and recent initiatives, it maps practical applications of AI and digital tools across the front, middle and back offices of financial institutions and identifies the governance conditions under which they can be deployed responsibly. It provides a series of policy recommendations for consideration in order to leverage these tools further to enhance SME access to sustainable finance.

JEL codes: G21, G28, O33, Q56

Keywords: SMEs, sustainable finance, artificial intelligence, digital tools

PUBE2 

consideration in order to leverage these tools further to enhance SME access to sustainable finance.

JEL codes: G21, G28, O33, Q56

Keywords: SMEs, sustainable finance, artificial intelligence, digital tools

PUBE2 

LEVERAGING AI AND DIGITAL TOOLS FOR SME SUSTAINABLE FINANCE © OECD 2026

ABOUT THE OECD The OECD is a multi-disciplinary inter-governmental organisation with member countries which engages in its work an increasing number of nonmembers from all regions of the world. The Organisation’s core mission today is to help governments work together towards a stronger, cleaner, fairer global economy. Through its network of specialised committees and working groups, the OECD provides a setting where governments compare policy experiences, seek answers to common problems, identify good practice, and c o-ordinate domestic and international policies. More information available: www.oecd.org. ABOUT THE SMEs AND ENTREPRENEURS PAPERS The series provides comparative evidence and analysis on SME and entrepreneurship performance and trends and on a broad range of policy areas, including SME financin g, innovation, productivity, skills, internationalisation, a nd others. This work is issued under the responsibility of the Secretary-General of the OECD and does not necessarily reflect the official views of OECD Member countries. This document, as well as any statistical data and map included herein, are without prejudice to the status of or sovereignty over any territory, to the delimitation of intern ational frontiers and boundaries and to the name of any territory, city or area.

Photo credits: Cover © Yaroslav Astakhov/Getty Images Plus.

© OECD (2026)

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This work is made available under the Creative Commons Attribution 4.0 International licence. By using this work, you accept to be bound by the terms of this licence ( https://creativecommons.org/licenses/by/4.0/). Attribution – you must cite the work. Translations – you must cite the original work, identify changes to the original and add the following text: In the event of any discrepancy between the original work and the translatio n, only the text of original work should be considered valid. Adaptations – you must cite the original work and add the following text: This is an adaptation of an original work by the OECD. The opinions expressed and arguments employed in this adaptation should not be reported as representing the official views of the OECD or of its Member countries. Third-party material – the licence does not apply to third-party material in th e work. If using such material, you are responsible for obtaining permission from the third party and for any claims of infringement. You must not use the OECD logo, visual identity or cover image without express permission or suggest the OECD endorses your use of the work. Any dispute arising under this licence shall be settled b y arbitration in accordance with the Permanent Court of Arbitration (PCA) Arbitration Rules 2012. The seat of arbitration shal l be Paris (France). The number of arbitrators shall be one. 3

LEVERAGING AI AND DIGITAL TOOLS FOR SME SUSTAINABLE FINANCE © OECD 2026

Acknowledgements This report was produced by the OECD Centre for Entrepreneurship, SMEs, Regions and Cities ( CFE), led by Lamia Kamal-Chaoui, Director, as part of the programme of work of the OECD Committee on SMEs and Entrepreneurship (CSMEE). The development of this report benefited from the val uable input and constructive feedback provided by Delegates of the CSMEE, chaired by Angelina Cannizzaro (Department for Business and Trade, United Kingdom) as well as the members and knowl edge partners of the OECD Platform on Financing SMEs for Sustainability.

constructive feedback provided by Delegates of the CSMEE, chaired by Angelina Cannizzaro (Department for Business and Trade, United Kingdom) as well as the members and knowl edge partners of the OECD Platform on Financing SMEs for Sustainability. This publication was written by So Jeong In (Policy Analyst, CFE) and Miriam Koreen (Senior Counsellor and Head of Unit, CFE) under the supervision of Lucia Cusmano (Head of D ivision, CFE). The authors would like to also thank Marija Kuzmanovic (Policy Analyst, CFE), Giulia Honegger (Policy Analyst, CFE), and Iota Nassr (Senior Policy Analyst, DAF) for their inputs and comments on the report. Bridgette Joyce and Jack Waters provided administrative and editorial assistance during the publication process. The report was developed with the financial support and inputs of the members of the OECD Platform on Financing SMEs for Sustainability – the Industrial Bank of Korea and the Bulgarian Development Bank – and the United Kingdom Departments for Business and Trade (DBT) and for Energy Security and Net Zero

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LEVERAGING AI AND DIGITAL TOOLS FOR SME SUSTAINABLE FINANCE © OECD 2026

Table of contents Acknowledgements 3

Executive summary 6 1 Introduction 8 2 Why SME sustainable finance remains difficult 10 Opacity and information asymmetry problems 10 Fragmented reporting ecosystems 10 Digital capability gaps in SMEs 11 High transaction costs for banks and the challenge of scalability 11 3 How AI and digital tools can intervene 13

SME side: sustainability data generation and pre-financing 14

Financial institution front office: client interaction and origination 16 Financial institution middle office: credit scoring, ESG risk analytics and compliance 19 Financial institution back office: monitoring, reporting and portfolio management 21 4 Policy considerations 23 Building interoperable SME sustainability data infrastructure 23 Developing verification and trust layers around SME sustainability data 24 Incentivising SME adoption of sustainability reporting through financing advantages, nonfinancial support and operational simplification 24

Financial institution back office: monitoring, reporting and portfolio management 21 4 Policy considerations 23 Building interoperable SME sustainability data infrastructure 23 Developing verification and trust layers around SME sustainability data 24 Incentivising SME adoption of sustainability reporting through financing advantages, nonfinancial support and operational simplification 24 Ensuring accountability and appropriate safeguards for the use of AI in SME sustainable finance 25 5 Conclusions 27 References 28 Notes 31

TABLES Table 1. Key barriers to SME sustainable finance 12 Table 2. Practical uses of digital tools and AI for financial institutions 14 5

LEVERAGING AI AND DIGITAL TOOLS FOR SME SUSTAINABLE FINANCE © OECD 2026

BOXES Box 1. Digital tools for SME sustainability data generation 15 Box 2. Front office digitalisation for SME sustainability finance 17 Box 3. An overview of traditional AI, Generative AI and Agentic AI 19 Box 4. Middle office innovations in SME sustainability financing 20 Box 5. Back office automation for SME sustainability financing 226 

LEVERAGING AI AND DIGITAL TOOLS FOR SME SUSTAINABLE FINANCE © OECD 2026

Executive summary Small and medium-sized enterprises (SMEs) are central actors in the transition to a more sustainable and resilient economy. They account for around 50% of economic output and business sector environmental impacts. At the same time, they remain underrepresented in sustainable financ e. Although sustainable finance markets have expanded significantly in recent years, this growth has not translated into broadbased access for smaller firms. The key challenge is how to deploy s ustainable finance at loan size s appropriate for SMEs in a way that is workable for both providers and users of finance. Many countries are promoting sustainable financing instruments, and many financial institu tions are adapting their practices in response to ESG-related disclosure requirements and inv estor demand. For SMEs, engaging with sustainable finance is not only about access to capita l. It can also help firms lower

Many countries are promoting sustainable financing instruments, and many financial institu tions are adapting their practices in response to ESG-related disclosure requirements and inv estor demand. For SMEs, engaging with sustainable finance is not only about access to capita l. It can also help firms lower operating costs through energy-efficiency investments, meet buyer sustainability standards , participate in global value chains and reduce reporting costs through more efficient data management. However, sustainable SME finance is constrained both by traditional SME finance frictions and new sustainability-related information demands. SMEs are more opaque borrowers than large corporates, often due to shorter credit histories, weaker collateral positions and limited standardisation of firm-level data. In the sustainability context, these longstanding constraints are compounded by additiona l information demands related to emissions, environmental performance, transactions and cli mate-related risks. Financial institutions, large buyers and other stakeholders require such informati on in different formats , while the tools intended to support reporting vary widely in methodology, language coverage, data access arrangements and interoperability. As a result, the cost of providing SME sustainable finance is considered to be high, weakening its scalability. These frictions are reinforced by uneven digital capabilities among SME s, many of which lack integrated systems for accounting, data management, sustainability measurement and reporting . Even when firms are willing to invest in more environmentally sustainable business models, the y often do not have the internal capacity to generate the sustainability data needed to access that targeted finance. This challenge is especially acute for micro and small firms, which face greater time, skil l and resource constraints than larger SMEs. Digital capability therefore affects not only reporting quality, but also the practical ability of firms to become visible to lenders and participate in more structured forms of sustainable finance. AI and digital tools can reduce these frictions across the financing lifecycle. On the SME side, digital tools can help firms generate sustainability-related information – in formats that are machine-readable, reusable and aligned with lender requirements – automate parts of the reporting process and share data more efficiently with counterparties. On the financial institution side, AI can suppor t front-office onboarding and

can help firms generate sustainability-related information – in formats that are machine-readable, reusable and aligned with lender requirements – automate parts of the reporting process and share data more efficiently with counterparties. On the financial institution side, AI can suppor t front-office onboarding and product matching, middle-office risk analysis and evidence checks, and back-offi ce monitoring and reporting. Used responsibly, these technologies can help move sustainable SME fi nance away from labour-intensive handling towards more standardised and automated processes. This is particularly important in the SME segment, where even modest reductions in origination, due dilig ence or monitoring costs can materially improve viability of sustainable financing. 7

LEVERAGING AI AND DIGITAL TOOLS FOR SME SUSTAINABLE FINANCE © OECD 2026

Some digital applications are relatively mature for measurement, onboarding and monitoring, such as digital carbon calculators or e-KYC platforms. On the other hand, more autonomous us es of AI for due diligence and workflow management remain emergent and can serve as tools for faster human-assisted review, rather than as autonomous decision making systems. The contribution of these tools depends on several conditions and carries a number of risks that need to be managed . Such tools can support SME access to sustainable finance provided the surrounding information environment allows data to be trusted, compared and reused. If s ustainability-related information remains fragmented, weakly governed or difficult to validate, automation may reproduce existing inefficiencies. Furthermore, some applications of AI also raise concerns related to bias, explainability, privacy, cybersecurity and the quality of model outputs. To address these challenges and scale the responsible use of these technologies, this paper identifies four broad policy priorities. First, building an interoperable sustainability data infrastructure is essential to enable SMEs to “report once and reuse” information across multiple counterparties and systems. Second, developing robust verification and trust layers can reinforce the credibility of the sustainability data underpinning financing decisions. Third, policymakers and lenders can incentivise SME adoption by explicitly linking reporting efforts to tangible financing advantages and providi ng targeted non-financial

developing robust verification and trust layers can reinforce the credibility of the sustainability data underpinning financing decisions. Third, policymakers and lenders can incentivise SME adoption by explicitly linking reporting efforts to tangible financing advantages and providi ng targeted non-financial capacity building. Finally, ensuring accountability and appropriate safeguards, such as human oversight and explainability, is critical so that AI functions as a decision aid that complements human judgement rather than replacing it.8 

LEVERAGING AI AND DIGITAL TOOLS FOR SME SUSTAINABLE FINANCE © OECD 2026

Sustainable finance1 represents a large pool of finance in countries around the world; yet its reach to small and medium-sized enterprises (SMEs) remains limited and uneven 2. The challenge is to ensure that such capital reaches firms through financing arrangements that work for lenders and are available to SMEs. This remains difficult because sustainability-related information in the SME segment is often costly to generate, difficult to verify and challenging to leverage different financial and commercial relationships. For many smaller firms, the issue is not only whether financing exists, but als o whether they can provide the kind of information that allows financial institutions (FIs) to understand the status of the firm’s sustainability performance, recognise its transition efforts, assess related benefit s and risks and design tailored financing conditions. Furthermore, the cost to FIs of gathering, interpreting and monitoring such information often requires substantial administrative effort relative to transac tion size. The core constraint is therefore less the availability of sustainable financing than the challenges and costs associated with the information and delivery systems through which that capital is expected to flow. Sustainability-related information demands have expanded on both sides of the market, widening the gap between what is being asked of SMEs and what they can reasonably provide. Financ ial institutions increasingly require such information for portfolio reporting, product design, financed-emissions accounting and risk management. Large corporates are placing similar demands on suppliers throughout value chains. Standard-setting initiatives are moving towards more proportionate frameworks for smaller firms, but the surrounding landscape remains fragmented and implementation uneven – a challenge the OECD has

increasingly require such information for portfolio reporting, product design, financed-emissions accounting and risk management. Large corporates are placing similar demands on suppliers throughout value chains. Standard-setting initiatives are moving towards more proportionate frameworks for smaller firms, but the surrounding landscape remains fragmented and implementation uneven – a challenge the OECD has addressed directly through its Guidance Note on fostering convergence in SME sustainabili ty reporting (Koreen, Kuzmanovic and Honegger, 2025 [1]). Many SMEs face growing expectations from several directions at once, often without the internal expertise, digital systems or staff capacity needed to respond efficiently. What emerges is a reporting burden along with a financing constraint : rising information demands increase the fixed costs of originating and managing sustainable SME financ e, making access slower, more expensive and less scalable. These barriers are mutually reinforcing. Information asymmetry leads financial ins titutions and other counterparties to request more sustainability-related data from SMEs in order to re duce uncertainty. Fragmented reporting ecosystems then multiply those requests across institutions , value-chain partners and jurisdictions, often through different templates and methods. At the same time, limited digital capabilities constrain many SMEs’ ability to respond in an automated or reusable way. Time, complexity and cost are consistently identified as major obstacles to sustainability measurement and reporting (SME Climate Hub, 2025[2]). The cumulative effect is a transaction-cost structure in which small-ticket sustainable finance becomes difficult to originate, assess and monitor at scale. These challenges are not uniform across the SME population: micro-enterprises and the smallest firms tend to face the most limited capabilities and resource constraints, while medium-sized firms may be b etter positioned to engage with digital reporting tools and access sustainability-linked financing produc ts. Some of the barriers described apply to SME access to finance more broadly; however, they are more pronounced in the conte xt of sustainable finance, given the additional information requirements of this type of financ e. Against this backdrop, digital tools and artificial intelligence (AI) have attr acted growing attention as practical means of addressing information and process bottlenecks across the financing li fecycle. At the

sustainable finance, given the additional information requirements of this type of financ e. Against this backdrop, digital tools and artificial intelligence (AI) have attr acted growing attention as practical means of addressing information and process bottlenecks across the financing li fecycle. At the same time, their contribution depends on the quality of the surrounding data envir onment. They can 1 Introduction 9

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process and structure information more efficiently, but they cannot generate reliable ou tputs where underlying data do not exist or are of insufficient quality. They can also introduce new risks, including the potential for biased outputs, limited explainability of model decisions and vulne rability to poor-quality or inconsistently governed data. Used within appropriate governance arrangements, these technologi es can help move sustainable SME finance away from labour-intensive handling towards more standardised a nd scalable processes. This paper examines these issues across the financing lifecycle, beginning with the SME side (demand side) and moving through the financial institution’s front, middle and back office3 (supply side). It considers how digital tools and AI can make a significant practical difference to SM E access to sustainable finance, and where their use creates new governance and policy demands. The analysis points to four broad policy priorities: • improving interoperability so that sustainability-related information can move more ea sily across systems and counterparties; • strengthening verification and trust mechanisms so that such information can be leverage d to facilitate financing of small businesses; • creating clearer incentives for SMEs by linking better reporting to visible commercial benefits; • and ensuring that the use of AI in financing decisions is subject to appropriate safeguards from the outset. The broader objective is to enable SMEs to report once and reuse information across counterparties, so that financing terms reflect actual sustainability performance and transition efforts. AI a lso cannot compensate for missing, inconsistent or weakly verified data . Scaling sustainable SME finance will therefore require proportionate reporting, trusted data-sharing arrangements, interoperabl e digital infrastructures and carefully governed AI applications.

that financing terms reflect actual sustainability performance and transition efforts. AI a lso cannot compensate for missing, inconsistent or weakly verified data . Scaling sustainable SME finance will therefore require proportionate reporting, trusted data-sharing arrangements, interoperabl e digital infrastructures and carefully governed AI applications. The paper builds on the work of the OECD Platform on Financing SMEs for Sustainability under the OECD Committee on SMEs and Entrepreneurship (CSMEE). It advances previous work on SME s ustainable finance, including the 2022 policy paper on Financing SMEs for Sustainability : Drivers, Constraints and Policies, the 2023 survey report on financial institution strategies and approaches, the 2025 Guidance Note on fostering convergence in SME sustainability reporting and the 2025 report on Sc aling Up Public Financial and Non-Financial Support for SME Sustainability. It aims to set out the key issues, trends and policy considerations in a concise way, and to contribute to ongoing policy d ialogue on how to unlock sustainable finance for SMEs. The paper also draws on linkages with the OECD Digital for SMEs (D4SME) Global Initiative.10 

LEVERAGING AI AND DIGITAL TOOLS FOR SME SUSTAINABLE FINANCE © OECD 2026

Opacity and information asymmetry problems SMEs are typically more opaque borrowers than larger firms, making them more challeng ing for lenders to assess and finance. Limited financial disclosure, shorter credit histories, weaker collateral positions and less standardised reporting practices all complicate risk assessment, performance monitoring and accurate credit pricing. This raises the cost of finance for SMEs in lending markets and often translates into tighter credit conditions, stricter collateral requirements and lower availability of external financing (OECD, 2022[3]). These challenges are compounded in the context of sustainable finance. Financial institutions are now required to assess not only traditional creditworthiness, but also environmental performance, transition plans, and exposure to climate risks, raising the informational threshold for financing . Given that financed emissions (Scope 3) represent the vast majority of a lender ’s carbon footprint, financial institutions need

required to assess not only traditional creditworthiness, but also environmental performance, transition plans, and exposure to climate risks, raising the informational threshold for financing . Given that financed emissions (Scope 3) represent the vast majority of a lender ’s carbon footprint, financial institutions need consistent, comparable and reliable sustainability data for decision makin g (PCAF, 2025 [4]). While this applies to their entire financed portfolio, the SME segment remains the weakest link in reporting, precisely when information needs are expanding most rapidly. This structural opacity limits SM E participation in sustainable finance, even where demand exists. Fragmented reporting ecosystems Sustainability reporting is becoming increasingly relevant for SMEs in financ ing and value-chain relationships. This is driven not only by regulatory pressure trickling down across jurisdictions, but also by operational demands from financial institutions and supply chain partners (Koree n, Kuzmanovic and Honegger, 2025[1]). Financial institutions are increasingly seeking sustainability data from their SME clients, with 60% doing so either directly or indirectly (OECD, 2023 [5]). To meet their own reporting needs and bridge the existing data gap, many financial institutions and large enterprises have developed their own methodologies and sustainability questionnaires for SME clients. As a result , SMEs face a multitude of uncoordinated data requirements from different institutions, forcing them to navigate multiple complex reporting frameworks across jurisdictions. This fragmented approach places an additional reporting burden on SMEs and can act as a deterrent to accessing sustainable finance even if such financing comes with better terms (OECD, 2023 [5]; Koreen, Kuzmanovic and Honegger, 2025 [1]). Reflecting this friction, only about a third of SMEs investing in sustainability-related improvements use promotional sustainable finance instruments. This suggests that reporting and administrative hurdles may lead some SMEs to rely on standard finance, even though promotional instruments could offer more favourable terms thro ugh public guarantees, subsidies or other support mechanisms (SMEunited and Eurochambres, 2023 [6]). In response to these challenges, a range of initiatives have sought to s treamline reporting and foster

standard finance, even though promotional instruments could offer more favourable terms thro ugh public guarantees, subsidies or other support mechanisms (SMEunited and Eurochambres, 2023 [6]). In response to these challenges, a range of initiatives have sought to s treamline reporting and foster convergence in sustainability data requests to SMEs. These include the EU Voluntary Sustainability Reporting Standard for SMEs (VSME) and national-level programmes, as well as international initiatives 2 Why SME sustainable finance remains difficult 11

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such as the OECD Guidance Note on fostering convergence in SME sustainability reporting. Progress has been made in reducing duplication and aligning frameworks more closely with the capacities of smaller firms. Digital tools and AI offer further potential to close the remaining gaps. On the other hand, while the development of sustainability measurement tools aims t o help SMEs, the proliferation of these digital solutions presents a new challenge for SMEs to navigate. A UK review found that there are more than 270 solutions in the market for carbon reporting alone, most of which still require manual data inputs by businesses (Icebreaker One, 2024[7]). Methodological alignment, pricing structures, language coverage and data-access rules also vary across these tools 4. Consequently, SMEs still face a fragmented market for reporting tools, even as more digital solutions become available (Koreen, Kuzmanovic and Honegger, 2025[1]; Icebreaker One, 2024[7]). Digital capability gaps in SMEs Digital readiness remains uneven across the SME landscape. SMEs are often constrained by limited access to digital skills, a lack of time, and insufficient financial resources to invest in hardware and software solutions (OECD, 2025[8]). Survey evidence highlights that capability constraints are acute in the data and reporting phases. Specifically, SMEs identify a lack of time (42%), tech nical difficulties (41%), and high reporting costs (41%) as the top barriers to sustainability measurement and reporting ( SME Climate Hub,

solutions (OECD, 2025[8]). Survey evidence highlights that capability constraints are acute in the data and reporting phases. Specifically, SMEs identify a lack of time (42%), tech nical difficulties (41%), and high reporting costs (41%) as the top barriers to sustainability measurement and reporting ( SME Climate Hub, 2025[2]). These internal resource deficits hinder their ability to measure their environmental footprint, collect the right data and respond to counterparties’ growing information requests. Additionally, these digital and financial literacy gaps prevent SMEs fr