Assessment of TCFD Voluntary Disclosure Compliance in the Spanish Energy Sector: A Text Mining Approach to Climate Change Financial Disclosures

Abstract

This study investigates voluntary compliance with the Task Force on Climate-Related Financial Disclosures (TCFD) framework in 64 financial, Environmental, Social, and Governance (ESG) reports from six Spanish IBEX-35 energy firms (2020–2023) and explores the implications for intangible assets and corporate reputation, employing empirical quantitative text mining and Natural Language Processing (NLP) in Python. A validated scale-based taxonomy within the TCFD framework applies query-driven rules to extract relevant text. This enables an evaluation of aspects of the reports, facilitating the development of a compliance index measuring each company’s adherence to TCFD recommendations. All companies showed year-on-year improvements (2023 was the most comprehensive), yet none fully adhered due to information gaps. Disparities in the disclosures of Scope 1,2 and 3, persisted, suggesting reputational risks. A replicable methodological model generating a compliance index that assesses the ‘being’ (‘true performance’) versus ‘seeming’ (‘external perception’) dichotomy within sustainability reports and acts as a potential reputational barometer for stakeholders. By providing unprecedented evidence of TCFD reporting in the Spanish energy sector, this study closes a significant academic gap. Future research may analyze ESG reports using AI agents, study the impact of ESG on energy-intensive companies from AI data centers, supporting services like Copilot, ChatGPT, Claude, Gemini, and extend this methodology to other industrial sectors.

1. Introduction

This study explores the significance of voluntary corporate disclosure in the context of global climate emergencies and the increasing demand for transparency in Environmental, Social, and Governance (ESG) reporting. A multitude of frameworks and initiatives have emerged to guide corporate reporting on these complex issues, each with varying scopes and focuses. The Task Force on Climate-Related Financial Disclosures (TCFD), specifically focusing on climate-related financial risks and opportunities, became a prominent voluntary standard within the broader ESG landscape [1]. In particular, the energy sector, which is critical for the transition to a low-carbon economy, requires innovative methodologies to overcome the limitations of traditional approaches [2,3,4,5].

There is a paucity of context-specific studies examining the application of the TCFD framework to the Spanish energy sector, which constitutes a significant gap in the literature. To address this discrepancy, an approach incorporating advanced data science techniques, including text analytics, applied to financial and sustainability reports has been adopted. This methodology facilitates a more profound comprehension of the correlation between reporting transparency and the incorporation of intangible assets, including corporate communication (in both internal and external forms), marketing, and corporate reputation. Furthermore, these techniques facilitate the identification of discrepancies between an organization’s operational reality and its public perception among investors, analysts, academics, and other stakeholders in the face of climate change [6,7,8].

The present study makes a novel contribution by assessing the TCFD compliance in the Spanish energy sector. Specifically, 64 reports from six IBEX-35 companies (Enagás, Endesa, Iberdrola, Naturgy, Redeia, and Repsol) covering the period of 2020–2023 were analyzed, representing the final phase of voluntary TCFD implementation. It is noteworthy that the TCFD mandate concluded and was dissolved in 2023 after establishing an effective global framework for climate disclosure [9]; oversight of these disclosures was subsequently transferred to the International Sustainability Standards Board (ISSB) of the IFRS Foundation, in line with the mandatory application of the Corporate Sustainability Reporting Directive (CSRD) from 2024 [10].

The TCFD employs validated scales from the four areas to extract the relevant indicators of current and future projections in each company’s reports [11]. The voluntary TCFD framework was established in 2015 with the aim of addressing the deficiencies in climate-related financial disclosure. In the same year, Carney [12] issued a warning regarding the ‘tragedy of the climate horizon’, observing that both the physical and transitional opportunities and risks were not reflected in the financial reporting, thus hindering the decision-making processes directed towards the development of a low-carbon economy [13]. From 2017 to 2023, the G20, major companies, and economic sectors played pivotal roles in the promotion of the TCFD model, which was initially proposed by the Financial Stability Board (FSB). The model was designed to emphasize the risks and opportunities associated with climate change, with a particular focus on their impact on financial stability and the global economy [3,14].

It is imperative for policymakers, analysts, investors, stakeholders, and academics to understand Spanish energy companies’ compliance with the TCFD to address gaps in the scientific literature and their relevance in the discourse on climate change [15]. The challenge of formulating a univocal definition of corporate sustainability is attributable to its multidimensional and multifaceted character, and an emerging consensus has been reached among researchers in this field, identifying fundamental pillars such as long-term value creation [16], stakeholder orientation [17], the integrated management of ESG risks, impacts, and opportunities [4], and the promotion of transparency and responsible governance [18,19]. In this context, Pinillos & Castilla [20] describe this phenomenon as a ‘regulatory tsunami,’ while Zhang [21] highlights the transition from a paradigm focused on maximizing shareholder value [22] to one that incorporates all stakeholders, as evidenced by initiatives such as the Business Roundtable Statement [23].

The evolution of ESG reporting, illustrated in Figure 1, represents a continuous evolutionary process over approximately 80 years, driven by three converging strands: (1—blue line) the consolidation of key academic milestones, (2—gray line) progress through increasingly robust international agreements affecting the planet and humanity, and (3—green line) the progressive construction of regulatory frameworks.

At the European level, the Non-Financial Reporting Directive (NFRD) [24] represented a significant milestone in recognizing the importance of both tangible and intangible assets, such as corporate reputation [25]. More recently, the Corporate Sustainability Reporting Directive (CSRD) [26] and European Sustainability Reporting Standards (ESRS) [27] have established new requirements that, as of 1 January 2024, will be mandatory for the listed companies [28,29,30].

The energy sector is of pivotal significance within the discourse on sustainability, and preliminary observations indicate significant variations in compliance with the TCFD framework among Spanish companies [4]. It is important to note that this sector is the primary contributor to Scope 3 emissions in IBEX-35, totaling 268 million t CO₂ e. The majority of these emissions are attributed to Naturgy (≈38.1%), Repsol (≈22.8%), and Iberdrola (≈14.6%), with the remaining emissions distributed approximately equally among Enagás, Endesa, and Redeia (≈8%). These companies have been shown to exert a considerable environmental impact through the end use of their products and extensive value chains [31,32,33], raising concerns regarding their transparency and ability to address climate change in light of impending EU regulations [28,34], and it is imperative to scrutinize their engagement [35,36].

As demonstrated in the existing literature, context-specific studies in strategic sectors, such as the Spanish energy sector, are scarce. This limitation results in the restriction of the generalizability of findings and necessitates an analysis of voluntary compliance in this area [37,38,39,40]. Accordingly, this study employs text mining techniques on 64 ESG reports (2020–2023) to assess TCFD compliance and its relationship with the management of intangible assets [6,41,42].

In response to the aforementioned points, the present research provides a novel contribution by focusing on the Spanish IBEX-35 energy sector and utilizing a methodological approach grounded in data science and advanced text mining to analyze 64 financial and ESG reports between 2020 and 2023. This approach (Data Science) has been demonstrated to enhance the accuracy and completeness of compliance assessments in accordance with TCFD, thereby enabling a detailed analysis of the quality, extent, and relevance of climate-related disclosures and overcoming the limitations of traditional manual methods [2,43]. In addition, empirical evidence has demonstrated a link between the degree of voluntary TCFD compliance and the effective management of intangible assets, such as corporate reputation [44]. The developed model has been shown to be both replicable and adaptable. This suggests that it may offer promising avenues for future research in both sectoral and geographical domains. Furthermore, it can promote transparency and trust in sustainable corporate reporting [45].

The primary research lacunae identified in the domain of ESG reporting analysis and in accordance with the TCFD framework were as follows. First, studies tailored to the context of strategic sectors (e.g., the Spanish energy sector) are scarce, which limits the generalizability of the findings [46]. Second, there is insufficient application and empirical validation of advanced data science techniques, such as specialized language models, to assess the quality, consistency, and depth of the ESG disclosures [47].

In the context of this study, the following three points are identified as areas of concern: The absence of robust quantitative analyses linking TCFD compliance to the management and perception of intangible business assets, particularly corporate reputation, is lacking [6,48]. The absence of longitudinal research comparing voluntary compliance with subsequent phases of mandatory regulation (e.g., the CSRD [29]). The limited transparency and systematization of computational methodologies for textual analysis have been identified as significant factors affecting the replicability and reliability of the existing studies [15].

These gaps present significant opportunities to expand scientific knowledge and enhance reporting and management practices for corporate sustainability.

In the contemporary context of corporate reporting, characterized by the increasing complexity and volume of unstructured data, the adoption of advanced analytical tools such as text mining based on NLP techniques is imperative to transform ESG information analysis [43,49]. These methodologies, which integrate computational linguistics and content analysis, enable systematic and scalable evaluations to overcome the limitations of traditional methods [50,51].

The implementation of Artificial Intelligence (AI) through transformational models, such as FinBERT or ClimaBERT, has demonstrated enhanced performance in both the classification of financial texts and the detection of greenwashing [2,43,52].

Given their potential in the analysis of numerical data and unstructured textual documents, such as financial and sustainability reports, and their increasing prevalence in the field, this study employs data science and text mining techniques [53,54,55]. The results of this study have significant theoretical and practical implications. In principle, the integration of sophisticated text mining methodologies within the framework of TCFD compliance enhances the conceptual underpinnings of ESG reporting, thereby elucidating the interplay between report quality and intangible assets [2]. In practice, the model developed for public access and replication facilitates the systematic identification of disclosure inconsistencies. This, in turn, has been demonstrated to enhance companies’ capacity to formulate sustainable policies and bolster the confidence of investors and regulators [47].

The primary objectives are as follows: (O1) to analyze compliance with the TCFD recommendations in the selected reports; (O2) to evaluate the quality, scope, and relevance of climate disclosure; and (O3) to develop an index that measures compliance with 70 Specific Concepts (SC) of the TCFD.

The research questions formulated are intended to facilitate the identification of key patterns, examine the evolution of disclosed information over time, and derive practical recommendations. Consequently, the following research questions were formulated.

Q1: What key patterns and levels of transparency are evident in reports?

Q2: How has the quality and comprehensiveness of disclosed information evolved over the study period?

Q3: What practical recommendations can be drawn from the analysis of the compliance index?

This study adopted a structured abstract following the NISO Z39.14-1997 R2015 standard [56] to facilitate indexing and retrieval using AI systems. Moreover, this article is structured in accordance with the IMRaD(I) format, thereby facilitating a lucid and methodical exposition of the methodology, results, the discussion of the implications and limitations, and conclusions. It employs an evidence-based approach that integrates citations to substantiate its claims [57].

2. Literature Review

2.1. Text Mining in the TCFD Framework: Approaches and Gaps

Following the publication of the TCFD recommendations, a plethora of methodologies employing NLP and machine learning have been developed for the systematic assessment of compliance with climate risk disclosure standards [38]. In the early years of the TCFD state reports, namely 2018 and 2019, supervised algorithms were employed for the identification of the relevant sections within corporate reports. This illustrates the potential of these techniques in transforming traditional manual and subjective analysis processes [4]. This transformative approach has contributed to the global recognition of the TCFD framework and stimulated research across diverse sectors. This, in turn, has emphasized the strategic value of advanced analytical tools in enhancing transparency and systematizing climate information analysis [18].

Several studies have demonstrated the efficacy of text mining in evaluating the alignment of the disclosed information using the TCFD framework. For instance, research within the aviation sector has demonstrated the efficacy of these methodologies in assessing the quality and comprehensiveness of climate risk disclosures and building on these pioneering efforts. Subsequent investigations have refined the NLP techniques for climate reporting [1].

A notable development in this area is QlimateQA, which was introduced by Luccioni et al. [58]. This model was meticulously designed to identify text passages with significant climatic relevance in financial reports. The study demonstrates that customizing language models for specialized domains yields substantial improvements in analytical precision over general-purpose models. Similarly, ClimateBERT [2] signifies a substantial methodological progression. ClimateBERT is a large language model pre-trained on an extensive corpus of climate-related disclosures associated with the TCFD framework. This offers a deeper and more nuanced understanding of the technical language employed in the TCFD reports. As demonstrated in the literature, comparative analyses have shown that ClimateBERT outperforms generic language models in complex analytical tasks such as document classification and sentiment analysis [15].

Despite the exploration of BERT adaptations for more extensive financial applications, such as FinBERT [43], empirical evidence indicates that climate-specific models, exemplified by ClimateBERT, demonstrate superior efficacy in the analysis of highly specialized technical reports. Moreover, recent research on general-purpose models, such as ChatGPT [59], suggests a potentially fruitful direction for TCFD disclosure analyses. Nonetheless, specialized models remain the preferred option because of their semantic precision, profound contextual understanding, and capacity to discern subtle technical nuances. These factors are critical for the generation of robust and reliable analytical results [2,43].

As demonstrated in

Table 1. Previous studies applied Data Science to the TCFD framework and climate disclosure.

Year	Author(s)	Title	Method/Approach	Brief Description
2020	[58] Luccioni, A., Baylor, E., & Duchene, N.	QlimateQA: Analyzing Sustainability Reports Using Natural Language Processing	Development of a specific NLP model/identifying climatic passages in financial texts	Development of QlimateQA, a domain-specific model to identify climate-relevant passages in financial reports, enhancing the accuracy of analyses.
2022	[2] Bingler, J., Kraus, M., Leippold, M., & Webersinke, N.	ClimateBERT: A Pretrained Language Model for Climate-Related Text	Pre-trained BERT model/extraction of technical information from climate texts	Development of ClimateBERT, a pre-trained language model specifically for climate texts that facilitates the identification of relevant sections in the TCFD reports and improves the extraction of technical information.
2022	[43] Huang, A.H., Wang, H., & Yang, Y.	FinBERT: A Large Language Model for Extracting Information from Financial Text	Adapted BERT model/sentiment classification and analysis of ESG financial texts	Presentation of FinBERT, an adaptation of the BERT model to the financial field, used for the classification and analysis of sentiment in financial texts related to ESG disclosures, showing advantages over traditional techniques.
2023	[53] Velte, P.	Automated text analyses of sustainability & integrated reporting: A literature review of empirical-quantitative research	Systematic review/methodological assessment in text mining and NLP for sustainability reporting	The study presents a systematic review of the literature on the application of text mining and NLP techniques in the analysis of sustainability and integrated reports. It examines the methods used and the research objectives, highlighting both the progress made and the current limitations.

Source: Own elaboration based on the synthesis of the analyzed literature.

, these advancements underscore the necessity of customized NLP models in the critical evaluation of climate disclosures. By leveraging specialized tools instead of generic approaches, researchers can achieve enhanced analytical precision and gain deeper contextual insights [47]. Consequently, this fosters improved transparency and accountability in climate risk reporting across sectors, and the ongoing development of these models has the potential to enhance and standardize assessment methods within the field [60].

2.2. ESG Regulatory Frameworks: Historical Developments and Global Trends

The landscape of ESG reporting is shaped by a variety of frameworks and initiatives that have evolved significantly over time [39]. The seminal period in the evolution of ESG regulatory frameworks spanned from the late 1990s to the early 2000s, culminating in the formal launch of the Equator Principles in 2003 [61]. These principles were developed with the objective of prompting financial institutions to integrate social and environmental criteria into their investment decision-making processes, with a particular emphasis on infrastructure projects. Simultaneously, in 1997, the establishment of the Global Reporting Initiative (GRI) led to the standardization of sustainability reporting, thereby promoting greater transparency in the disclosure of non-financial information [62]. Unlike narrowly focused frameworks, the GRI provides comprehensive standards covering a wide range of Environmental, Social, and Governance topics, making it a widely adopted standard for broad ESG disclosure [45]. At the turn of the millennium, a series of significant developments marked advancements in the realm of corporate social responsibility. The launch of the Global Compact in 1999 [63] and the formulation of the Millennium Development Goals in 2000 [64] signified a broadening of corporate social responsibility, addressing global challenges such as poverty and inequality. Moreover, at the beginning of the 21st century, the Greenhouse Gas Protocol [65] was initiated, establishing a methodological framework for measuring and reporting emissions, thereby enhancing the accuracy of environmental disclosure [28]. GHG Protocol metrics, particularly Scope 1, 2, and 3 emissions, are a critical component, later emphasized by climate-specific frameworks such as TCFD [16].

Normative evolution was further advanced by the publication of the ISO 26000 [66] standard in 2010, which provides comprehensive guidelines on social responsibility and holistically integrates ESG aspects, similar to the GRI. However, as a guidance standard, ISO 26000 covers a broad spectrum of social responsibility themes beyond climate [66,67]. A significant shift in global policy occurred in 2015 with the adoption of the 2030 Agenda for Sustainable Development and the Paris Agreement. These instruments represent a strong international commitment to limiting global warming [5,68]. These global initiatives provided crucial political momentum and context, emphasizing the need for frameworks such as the subsequent prominent TCFD to translate broad climate goals into actionable corporate disclosure [4]. At the European level, the Non-Financial Reporting Directive (NFRD) [24] marked the inception of mandatory sustainability reporting, a concept subsequently reinforced by the EU Taxonomy [69] and the Sustainable Finance Disclosure Regulation (SFDR) [70]. The Corporate Sustainability Reporting Directive (CSRD) [26] and, more recently, the Corporate Sustainability Due Diligence Directive (CSDDD) [71] have been instrumental in extending transparency and accountability obligations throughout the value chain [26,29,30,71].

However, frameworks such as the GRI and the EU’s evolving CSRD/ESRS provide comprehensive approaches covering a wide range of Environmental, Social, and Governance aspects, with varying degrees of materiality considerations (single vs. double materiality) [28]. The distinct contribution of the TCFD rests on its specific focus on the financial implications of climate-related risks and opportunities [4]. This narrower yet deeply material information from an investor perspective focuses on distinguished TCFD and positions it as a crucial precursor and input for more holistic and eventually mandatory ESG reporting standards [38]. For instance, the International Sustainability Standards Board (ISSB), established under the IFRS Foundation, has explicitly incorporated TCFD recommendations into its prominent standards (IFRS S1 and IFRS S2), making TCFD-aligned climate disclosure a cornerstone of global sustainability reporting for investors [10]. Similarly, the European Sustainability Reporting Standards (ESRS), mandated by the CSRD, build upon the TCFD structure for climate-related information while expanding significantly to cover all ESG topics [28].

As shown in Figure 2, this evolutionary trajectory is graphically represented, with a gradual increase in the involvement and standardization of the most relevant ESG frameworks being highlighted.

As demonstrated in the literature, the discourse surrounding ESG frameworks has evolved from a voluntary (soft law) to a mandatory (hard law) approach [72]. Buhmann and Feldb [73] posited that this shift has led to an enhancement in corporate governance and reputation. By contrast, Friske et al. [74] underscore the role of voluntary practices in the initial legitimization of corporate social responsibility, notwithstanding the presence of geographical and enforcement limitations. In this context, Ostrom [75] emphasized the importance of complementing bottom-up initiatives with top-down frameworks to achieve global standards. The evolution of the TCFD, which has been transformed into a de facto global benchmark under pressure from investors and regulators, exemplifies the prevailing trend towards enforceability [76].

2.3. The TCFD Framework, a Global Standard for Enterprise Reporting

This study examines the TCFD framework, originally established in Switzerland by the Financial Stability Board (FSB) in 2015, with the aim of enhancing the understanding, design, and disclosure of information pertinent to a low-carbon economy in line with NetZero commitments [5,10]. In 2017, the TCFD published a “Final Report,” which rapidly became a voluntary global benchmark for companies’ non-financial disclosures. The report provides recommendations for increased transparency in financial reporting, with the aim of informing investors, shareholders, and the public [9,30]. These annual reports, which detail climate-related financial risks and operational impacts, facilitate cross-company and cross-sector comparisons, thereby promoting transparency regarding climate change risks and financial opportunities in relation to the 17 Sustainable Development Goals (SDGs) [77]. The framework developed by TCFD is structured around governance, strategy, risk management, metrics, and targets, thereby addressing the climate-related aspects of both operations and investments [78].

In their 2024 study, Maji and Kalita [3] advanced the notion of the TCFD model as a series of recommendations devised by international experts to enhance the disclosure of climate-related financial information. The objective of these recommendations is to enhance the transparency and quality of such information, thereby empowering investors to make informed decisions [46].

A survey of the extant literature on TCFD frameworks in academic databases revealed a paucity of material. A comparable strategy has also been implemented in other sectors in the context of climate change. In the Indian energy sector, a study of 22 listed companies conducted between 2018 and 2020 revealed moderate climate disclosure, consistent with the recommendations of the TCFD, which correlated positively with financial performance [3].

In the aviation sector, although there was an increase in climate reporting between 2015 and 2018, compliance with the TCFD framework was inadequate, particularly regarding strategic implementation [1]. The building sector, which is responsible for more than 40% of global emissions, is confronted with considerable challenges in integrating climate-related risks due to the intricacy and challenges associated with data collection [79].

The implementation of the TCFD model has been demonstrated to engender a number of advantages, including enhanced planning and identification of climate change risks, the facilitation of stakeholder engagement, and the implementation of competitive strategies [4]. The voluntary disclosure of non-financial information has been demonstrated to provide a comprehensive view of corporate actions and performance. Furthermore, the disclosure of sustainability initiatives has the potential to facilitate the planning of climate change-related measures, which may reduce both internal and borrowing costs [10,30]. Investors have been observed to impose higher costs on entities with a greater exposure to climate risks, a dynamic that rewards proactive companies and penalizes inaction [80]. Moreover, it has been demonstrated that corporate reputation may be enhanced through transparency, as trust is established when companies, investors, and stakeholders voluntarily provide TCFD-based financial information. This has resulted in sustainability certifications and an improved corporate image [25].

A subsequent significant development in Europe is the CSRD, which came into force in January 2024 for companies listed in regulated EU markets. The CSRD report encompasses 12 criteria that are distributed across four domains. First, there are crosscutting considerations that include general principles and content. Second, there are environmental issues such as climate change, pollution, water resources, biodiversity, resource utilization, and the circular economy. Third, social considerations encompass company workers, value chain employees, affected communities, consumers, and users. Finally, governance considerations address the business conduct of the listed companies. CSRD financial reporting necessitates the comprehensive disclosure of environmental impacts, human rights practices, and social initiatives that align with European climate change objectives [28,34].

2.4. Text Mining in Financial Reporting Analysis, Evolution, and the Future of NPL

The intersection of NLP and AI has precipitated a paradigm shift in the analysis of financial reporting and ESG disclosure [60]. Text mining, a fundamental application of NLP, has emerged as an indispensable tool for processing and extracting insights from vast volumes of textual data, thereby overcoming the limitations of traditional methods and opening novel avenues for assessing corporate sustainability [21]. This advancement is particularly significant in a context that demands enhanced transparency and quality in disclosing climate risks and ESG performance [16]. Nonetheless, an analysis of the environmental and ESG information via text mining faces several notable challenges. These include stylistic heterogeneity and a lack of standardization in sustainability reporting, which hinders the effective comparison and evaluation of the data [53]. It has been asserted that these obstacles impede the research. However, the adoption of dynamic approaches, such as zero-shot language models and multimodal analysis integrating textual, visual, and numerical data, has been actively encouraged [59].

Table 2. Historical evolution of NLP in relation to data science and text mining techniques.

Years	ERA	Techniques Employed	Main Features
1950 – 1980	First ERA: Rule-based systems	Heuristic methods. Regular expressions for pattern matching WordNet, Gensim, and fastText.	Rapid implementation. Accuracy guaranteed by human intervention. Requires expert knowledge and is time-consuming.
1990 – 2010	Second ERA: Statistical methods	Machine learning models such as Naïves/Bayes/logical regression/ SV/LDA/HMM.	Less reliance on customized rules. Data-driven approach. Requirement for manual feature selection.
2010 – Today	Third ERA: Machine learning approaches	Deep learning models such as RNN, LSTM, GRU, CNN. Transformers and pre-trained models such as BERT and GPT. Autonomous AI agents.	Automatic feature generation. Better management of unstructured data. Self-learning capability. High-quality and cost-effective results.

Source. Own elaboration based on the synthesis of the analyzed literature.

illustrates the historical evolution of NLP in relation to Data Science, with a particular emphasis on the utilization of Data Science and text mining techniques.

NLP has evolved from heuristic-based systems to advanced deep learning models, thereby facilitating more natural and accurate interactions with human language [81,82]. Notwithstanding the challenges posed by linguistic ambiguity, variability, and data biases, the development of large models such as GPT-4 and SEAMLESS-M4T has transformed our ability to understand and generate content, personalize strategies, and optimize processes, thereby driving unprecedented automation in ESG reporting analytics [60,83].

In the contemporary corporate reporting landscape, characterized by an increase in the complexity of unstructured information, text mining techniques have emerged as essential tools for the analysis of ESG reporting [51]. Textual analysis, as defined by McKee [49], is the process of extracting meaning from written language. This has been enhanced by data science methodologies that integrate computational linguistics, NLP, and content analysis, thereby overcoming traditional limitations [50].

Advancements in machine and deep learning have facilitated the development of models such as FinBERT and ClimateBERT, which improve sentiment classification and enhance the accuracy of pattern identification in climate disclosures [2,43]. The combination of these techniques with emerging AI platforms has the capacity to facilitate the identification of discrepancies between public declarations and actual practices. This capability enables researchers to identify the instances of greenwashing and evaluate the authenticity of sustainability commitments [52,84]. Furthermore, the configuration of these systems facilitates the realization of specific objectives, including the assurance of regulatory compliance, the identification of risks, and the generation of customized reports for various stakeholders [59,85].

The analysis was guided by two hypotheses.

H1. 

The implementation of risk management techniques improves the analysis of financial information by assessing and measuring compliance with the data presented in the reports.

H2. 

Spanish energy companies disclose the quality, scope, and relevance of their climate change actions, with enhanced disclosure positively influencing stakeholders’ and investors’ perceptions.

3. Materials and Methods

This study is divided into three subsections. First, the study design, analytical procedures, and construction of the taxonomy under the validated scale of the TCFD framework, as well as its applications and techniques, are described. Second, a rigorous evaluation of the 64 reports is conducted, with particular attention to the rigor expected for reports within this field. Third, an index is developed from the analysis of 70 SCs applied to the results of previous developments, text mining, and related aspects.

Text mining techniques were chosen based on their ability to extract semantic patterns from large volumes of data and mitigate human bias, as corroborated by previous studies. This approach improves the accuracy of the analysis of TCFDdisclosures [2,53,54].

3.1. Description of the Text Mining Process

The methodology employed was Named Entity Recognition (NER). The model utilized in this study employed a rule-based approach to identify pertinent entities and word sets within sustainability reporting in the context of the TCFD. This approach mirrors the method employed by Moreno & Caminero [54] for their analysis of climate information in the Spanish banking sector. This technique integrates domain-specific knowledge with data-driven models, aligning with broader trends in text mining and NLP to analyze sustainability reporting [53].

3.1.1. Definitions and Objectives

This study evaluated the degree to which the analyzed companies adhered to the recommendations of the TCFD framework. To this end, text mining techniques were employed to analyze the financial information disclosed in companies’ annual and sustainability reports. A total of 64 reports were collected and preprocessed from six IBEX-35-listed companies in the Spanish energy sector: Enagás, Endesa, Iberdrola, Naturgy, Redeia, and Repsol, covering the period of 2020–2023.

3.1.2. Tools and Resources Used

The reports were manually downloaded in Portable Document Format (PDF) and stored in a shared Microsoft OneDrive space. The subsequent process involved sorting and formatting the data using Adobe Pro X, with the final step being the conversion of the data to Microsoft Word format. The document reading process was executed using the Python v.3.11 programming language, in conjunction with the Python docx v.1.1.2 and pdfplumber v.0.11.4 libraries. The tokenization process was enabled using the spaCy v.3.8.4 library. Full-text searches (FTS) were conducted using the Whoosh v.2.7.4 software, and Microsoft Excel was employed to compile and analyze the results. The complete dataset (both pre-processed and post-processed) is available for consultation on the GitHub Webplatform, (accessed on 4 March 2025), along with the relevant code files: https://github.com/MATDOMI/TCFD-Energy-Sector-TM.git.

3.1.3. Document Collection and DATA PREPARATION

The PDF reports under scrutiny were procured from the corporate websites of the companies under study. This study encompasses 64 reports for the years 2020–2023, as they represent the final phase of implementation of the voluntary TCFD framework, just before the mandatory entry of the CSRD came into force in 2024. Each designated “ReportsYear” is defined exclusively as the number of reports published in that particular year (i.e., Reports2021 = ReportsIn2021), excluding data from the preceding years.

The inclusion criteria were as follows. The selection of the six energy companies was based on two key factors: their importance and representativeness in the Spanish energy sector. The selection was made on the basis that the companies constitute the group of main players listed on the IBEX-35 and are subject to a strict regulatory framework and homogeneous reporting standards. However, it must be noted that this selection may not be representative of the Spanish energy sector. The inclusion criteria were as follows: (i) a minimum of 250 employees, (ii) review by an external auditor, (iii) public publication on the corporate website, and (iv) PDF. The reports analyzed included “Annual, consolidated or integrated reports”, “non-financial information and/or sustainability reports”, sustainability or ESG reports, and “Corporate Governance Reports”. A range of other reports incorporating data that may be relevant to the TCFD were also considered

The exclusion criteria were as follows: The following reports were excluded from the study: (i) non-annual reports; (ii) reports not in PDF; (iii) reports not available on official websites; (iv) infographic reports; and (v) reports that did not contribute to the study after manual review.

The exclusion of other companies in the sector, such as Moeve, EDP Spain, and Engie Spain, is justified by the fact that although they are relevant in the industry, they operate under different regulatory conditions or are listed on different stock markets. This phenomenon gives rise to discrepancies in disclosure requirements as well as in the quality and consistency of the ESG information available. Consequently, it becomes challenging to directly compare their reports with those of selected companies.

The files were meticulously organized into three distinct categories: entity, year, and report type. These reports facilitated the development of an initial taxonomy on the validated scale of the TCFD framework through a manual review. Evidently, no individual reports on official websites provide coverage for all sections of the TCFD. The process of text mining involves the extraction of key themes, words and data from TCFD-related reports. The objective is realized through the implementation of data preparation techniques encompassing the analysis of PDF text sourced from corporate websites. The identification of the extracts was achieved by leveraging fundamental concepts from a sustainability taxonomy specially designed for the energy sector, and the Global Reporting Initiative (GRI) and the TCFD were used as a point of reference [4,61].

3.1.4. Text Preparation

The use of Adobe Pro X in the conversion of PDF files to Microsoft Word resulted in a 95.31% success rate, except in cases involving graphics, tables, and text boxes. It was found that approximately ≈ 4.69% of the records were not fully retrieved. This was mainly because of the technical limitations of OCR and formatting (e.g., images and bullet points). The exclusion of these records from further thematic analysis was necessitated by the absence of uniform information, which was required to apply the inclusion criteria. Given that the analyzed sample represents ≈ 95.31% of the total and that the reasons for exclusion were technical or access-related, it can be concluded that this exclusion does not introduce a significant bias in the findings, which in turn validates the analysis performed on the retrieved data. Conversion errors were manually corrected to adjust the success rate and minimize human bias, as indicated in

Table 3. No. of reports and file conversion.

	Enagás	Endesa	Iberdrola	Naturgy	Redeia	Repsol	TOTAL
No. of reports:	9	11	12	11	9	12	64
Successful Conversion:	≈94.80%	≈96.00%	≈95.23%	≈95.90%	≈95.50%	≈95.45%	≈95.31%
Cause of Failure:	Graphs and information tables do not convert properly. Tables not converted properly. Bullets require manual correction.
Resolution:	Manual—minimizations of human bias/improved post-error resolution.

Source. Author’s own elaboration.

.

3.1.5. Structured Text Representation and Extraction

A Python script was employed in conjunction with SpaCy, an efficient NLP library, to segment paragraphs and sentences into manageable extracts. This process enables the identification and analysis of paragraphs, sentences, bullet points, objects, and tables, without compromising the integrity of the original text. The total number of extracts used in this study was 14.503, as outlined in

Table 4. Structured text representation and extraction.

	Enagás	Endesa	Iberdrola	Naturgy	Redeia	Repsol	TOTAL
No. of sentences (key and thematic sentences)	1.264	1.897	3.152	2.837	1.645	2.465	13.260
Number of bullets (elements identified)	57	62	71	68	54	86	398
No. of objects (prioritized list)	89	97	112	75	106	134	613
No. of Tables (structured data)	33	42	40	37	35	45	232
TOTAL (%)	≈13.7%	≈13.1%	≈21.7%	≈19.6%	≈11.3%	≈20.6%	14.503 (100%)

Source. Author’s own elaboration.

.

3.1.6. Analysis and Information Extraction

Python was employed in conjunction with spaCy to define the NER relevant to the reports. The documents were indexed according to their environmental metrics, financial indicators, risk categories, phrases, bag-of-words tokens, and titles. In addition, separate tables were generated for tokenization. SpaCy, a powerful NLP library, facilitates the efficient identification and classification of named entities. The initial framework comprised 11 TCFD-recommended disclosures (RDs), which were subsequently subdivided into 70 SCs based on domain-specific knowledge and TCFD guidelines, as summarized in Table 4 [4]. For each detailed disclosure, a rule was established in order to determine its presence in corporate reports. The rule assigned values from 1 to 3 according to the monitoring frequency associated with the relevant entity, as demonstrated in

Table 5. The examples of these three rules demonstrate the flexibility of their search concepts.

Areas	Recommended Disclosures (RDs)	Specific Concepts (SCs)	Query	Value
A3—Risk Assessment and Management	RD8—Corporate resilience and reputation plan against climate change	Frequency of follow-up in relation to the “reputation”	reputation AND plan AND climate change reputation AND plan AND resilience reputation AND plan AND (strategy OR sustainable)	3 2 1

Source. Author’s own elaboration.

. These values reflect the relevance, monitoring frequency, and industry standards, ensuring a prioritized assessment of key disclosures. Monitoring frequency refers to the frequency with which terms associated with an entity were mentioned in corporate reports. Evidently, an elevated frequency is indicative of enhanced relevance. The values assigned to each query reflected the relative importance of the term to the company.

When multiple query matches were identified, the maximum value was given exclusive consideration, following established rules that stipulated disclosures pertaining to ‘climate change’ should be assigned a higher score than those relating to ‘sustainable’ practices. In the context of information extraction and coding, a set of Boolean queries was utilized to identify the relevant textual fragments within the reports. These queries were composed of specific key terms combined with logical operators, thereby enabling the identification of the desired information. Following extensive consultation, the decision to not include synonyms or more heterogeneous alternative terms was made. The rationale behind this decision was that the taxonomy was constructed and validated exclusively with the terms discussed in the TCFD framework.

This methodological decision was made with the objective of minimizing the occurrence of false positives and ensuring uniformity in the analysis of different companies, which used varied and sometimes inconsistent terminology. The allocation of a relevance value to each query was determined by the weighted frequency of the key terms present within the text. The coding was complemented by a manual review of the samples to calibrate and validate the accuracy of the model, ensuring an appropriate balance between coverage and accuracy.

Following iterations in the process, 103 queries were formulated using 70 SCs to identify 57 detailed disclosures, each associated with one of the 11 DRs reported in

Table 6. Quantification of specific disclosures and inquiries pertaining to each recommended disclosure.

4 Areas	11 Recommended Disclosures (RDs)	Detailed Disclosures	Total Queries
A1— Government	RD1—Structures and processes for monitoring climate risks RD2—Senior management involvement in climate management	3 8	9 18
A2— Strategies and Opportunities	RD3—Impact of climate change on the organization RD4—Development of green products for diversification, adaptation, and resilience RD5—Identification of climate risks and opportunities	7 11 2	10 12 3
A3— Risk Assessment and Management	RD6—Climate risk assessment and management RD7—Adaptation to changes in regulation RD8—Corporate resilience and reputation plan against climate change	2 7 3	4 12 6
A4— Metrics and Targets	RD9—Measuring and quantifying climate impact in the company RD10—GHG Emissions Protocol and Management, Scope 1, 2, and 3 RD11—Objectives and actions for the use of renewable energies and business sustainability	4 6 4	10 12 7

Source. Author’s own elaboration.

. This approach provides a robust and replicable foundation for the quantitative measurement of the TCFD compliance.

3.1.7. Visualization of Results with Tokenization and Indexing

Whoosh implemented an FTS on a set of extracts that were stored for retrieval via a Graphical User Interface (GUI). The FTS, a technique that allows exhaustive searches within document text, enables Whoosh to tokenize and index extracts, thereby facilitating the identification of relevant entities. A total of 14.503 excerpts were obtained from 64 reports across the six entities analyzed. The application of Whoosh streamlined the processing of this substantial data volume, thereby enhancing the accuracy of this study. The search criteria included NER keywords, phrases, expressions, and contexts such as company names, environmental metrics, categorization by section (such as TCFD areas), relevance, and frequency. These FTS results ensured the precise identification of the relevant extracts from the complete dataset of 14.503 samples.

3.1.8. Revision and Validation in Taxonomy Creation

We conducted a manual review and validation based on our subject matter expertise by applying NER to business reports using an FTS. We developed a taxonomy of concepts based on the validated scale of the TCFD recommendations. The 70 SCs were organized by area across the 11 RDs, as presented in

Table 7. Set of concepts for creating the taxonomy according to the TCFD framework [4].

4 Areas	11 Recommended Disclosures (RDs)	70 Specific Concepts (SCs)
A1— Government	RD1—Structures and processes for monitoring climate risks RD2—Senior management involvement in climate management	SC1—management, remuneration, periodicity, monitoring SC2—management, remuneration, periodicity, monitoring, sustainability committee
A2— Strategies and Opportunities	RD3—Impact of climate change on the organization RD4—Development of green products for diversification, adaptation, and resilience RD5—Identification of climate risks and opportunities	SC3—criteria, strategy, effect, reputational risks, reporting standards, technological utilization, sustainable energy SC4—climate scenarios and temperature increase SC5—tangible risks, climate change risks, shift risks, cost reduction opportunities, financing, mortgages, sustainable financing, short-term, medium, long-term, several weather events
A3— Risk Assessment and Management	RD6- Climate risk assessment and management RD7—Adaptation to changes in regulation RD8—Corporate resilience and reputation plan against climate change	SC6—environmental risks, prospects, shift risks, tangible risks, procedures, disclosure guidelines, compliance risk, reputation risk, economic risk, legislative controls, international agreements SC7—risk management strategies, materiality, emission valuation, litigation, severe weather events, renewable energy, transition costs SC8—strategy and crisis response
A4— Metrics and Targets	RD9—Measuring and quantifying climate impact in the company RD10—GHG Emissions Protocol and Management, Scope 1, 2, and 3 RD11—Objectives and actions for the use of renewable energies and business sustainability	SC9—reduction, CO2 emissions, refuse, energy use, water use, fuel use, renewable energies SC10—Scope, CO2 emissions, CO2 units, CO2 intensity, CO2 e SC11—target, reduction, CO2 emissions, refuse, energy use, water use, fuel use, renewable energies, renewable energies

Source. Author’s own elaboration.

.

The objective was to streamline the process by labeling the excerpts. A manual review of the process loop was conducted to ensure taxonomic consistency with the TCFD guidelines, resulting in the verification of 70 SCs. Each word was assigned a single label, and although SCs may recur, the rules prioritized longer textual segments. Explicit rules based on these recommendations were implemented to prevent false positives. The lexicon was lemmatized and converted into lowercase to account for term variations. Lemmatization reduces words to their base forms, thereby facilitating consistent term identification. Extracts were processed using Python and labeled according to the taxonomy.

3.1.9. Evaluation of Results (Model Accuracy)

The accuracy of the model was evaluated using an F1 score of 73%, which indicated satisfactory precision. This is particularly noteworthy given the intricate nature of the corpus of reports analyzed, which suggests a reasonable balance between accuracy and completeness. This approach enabled the efficient extraction of key information for the exploratory scope of this study and its objectives. This performance enabled the identification of relevant patterns in non-standardized data from complex corporate reports. The model demonstrated an accuracy of 0.78 and a recall of 0.68. However, its performance was hindered by the use of a non-exclusive lexicon, as specific terms such as ‘climate’, ‘emissions’, and ‘sustainable’ have the capacity to refer to multiple concepts. Moreover, the absence of a concise TCFD report impedes the unification of the 11 RDs and the subsequent confirmation of the compliance levels. The methodology necessitated a comprehensive understanding of the subject matter to establish the rules, a process that has the potential to introduce extraneous variables into the results. It is imperative to integrate automated techniques with supervised qualitative assessments to validate and enrich the results, thereby optimizing the accuracy and reliability of the analysis of corporate disclosures.

A critical evaluation of the existing methodologies is proposed herein. Although the application of text mining and NLP techniques has facilitated the analysis of large volumes of unstructured data in corporate reports [53,54], these methodologies have significant limitations. First, automated methods frequently lack the capacity to fully capture the semantic context and discursive subtleties present in reports, which can result in the superficial interpretation of key information [43,47].

Moreover, the absence of standardization in taxonomies and classification criteria impedes the comparability and replicability of the studies [55,72,86]. In contrast, the prevailing contemporary methodologies are predominantly oriented towards quantitative analyses, often overlooking qualitative components that are instrumental in elucidating the motivations and strategies underpinning disclosure. These qualitative elements are indispensable for comprehending the genuine intentions of companies [37,74,87].

3.1.10. Implementation and Utilization

Following the completion of a domain-specific training program, the application has been shown to enhance financial reporting analyses by accurately measuring key metrics and facilitating the efficient dissemination of reports to stakeholders, investors, and academics, without requiring extensive economic expertise. Furthermore, the implications of this phenomenon extend to intangible business assets, with notable influences on areas such as marketing, communication, reporting, risk management, and executive leadership.

3.2. Assessment Based on ESG Reporting Aspects Under the TCFD Standard

This study evaluated the disclosure of environmental information in 64 IBEX-35 energy sector reports in accordance with the recommendations of the TCFD. The present assessment employed the content analysis approach for sustainability reports developed by Beck et al. [88] to evaluate the quality, scope, and relevance of the information. A quantitative approach was employed, encompassing criteria such as the completeness of the information provided, the level of detail on climate policies, and transparency in the measurable outcomes. In addition to these quantitative metrics, qualitative scales were utilized to assign high scores to instances that demonstrated specific examples and alignment with recognized standards and low scores to cases that exhibited ambiguity or a paucity of detail on climate policies.

The assessment encompassed all the reports that identified 11 DRs. The allocation of coverage to topics pertaining to the TCFD was informed by a comprehensive review of the extant literature and our accumulated experience. This process involved a meticulous evaluation of the intricacies inherent in climate change actions, the transparency of reporting practices, the extent of TCFD implementation, and the alignment of these practices with the overarching sustainability strategy of each company.

3.3. Development of an Index Based on Compliance with the TCFD in ESG Reports

In accordance with the methodological approach proposed by Halme and Huse [89] regarding the assignment of value to environmental disclosure in companies, a compliance index ranging from 0 to 1 was employed to weigh a quantitative scale. The scale employed in this study evaluates the level of TCFD disclosure in the reports of the six companies analyzed.

The construction of the index is based on the theory of communication performance measurement and intangible asset management, following the recommendations of Parguel et al. [90] regarding the importance of including dimensions such as relevance, extension, quality, and detail to assess the effectiveness of corporate communication and its impact on reputation. The present study found that the proposed framework aligns with contemporary regulatory and analytical frameworks. These frameworks emphasize the importance of standardized measures for the assessment of transparency and completeness in ESG reporting [13,19,21].

The index comprises 70 SCs, which are distributed across the four primary thematic areas of TCFD. The uniform weighting method was applied to each SC in the total score, under the assumption that it holds equivalent importance in the comprehensive assessment of compliance. This approach is supported by previous studies in the field of ESG reporting [91]. For each concept, the presence, relevance, explanation, quality, and detail of the text in each SC in the 64 reports were assessed using text mining techniques. Furthermore, these results were contrasted with expert qualitative analysis, ensuring a rich and contextualized assessment.

The values for each CS were aggregated within their respective areas to obtain a partial score and, subsequently, the total score for each company. The consolidated index under consideration enables an estimation of the level of compliance with the TCFD framework. This is interpreted as a preliminary indicator of the reputational risk associated with climate disclosure in the Spanish energy sector.

The following section presents an analysis of the results and addresses the study’s questions, objectives, and hypotheses.

4. Results

4.1. Results of Text Mining Applied to TCFD Compliance Analysis

A systematic analysis was conducted utilizing text mining techniques, as previously outlined, to evaluate the TCFD compliance in the selected reports from six energy sector companies. This approach fulfilled objective O1 and addressed research question Q1.

This analysis revealed improvements in climate disclosure. As Figure 3 shows, there was a gradual increase in climate disclosure by Spanish energy companies, with 2023 being the most prolific year in terms of productivity. It was evident that no individual report contained all the recommendations; rather, they were disseminated across multiple reports. Iberdrola and Repsol demonstrated the most comprehensive coverage of all the aspects, achieving the highest threshold in 2023.

Other companies have demonstrated a year-on-year progression. None of the 11 DRs achieved compliance with the 70 SC points.

It was determined that two areas, designated A3 and A4, exhibited a discrepancy in the progression of energy companies compared to A1 and A2. This finding suggests an asymmetric evolution, characterized by the disclosure of RD8 in the context of strategy resilience and climate-related objectives, including RD10 and GHG emission management. This study demonstrates that annual ESG, sustainability, and other corporate reports contain significant information on TCFD. No company possessed a solitary report from which comprehensive conclusions could be derived. The generation of multiple reports was imperative for the accurate composition of this report. Enagás and Redeia face substantial challenges in their disclosure of information. Increased board participation (A1) in climate-related issues has been observed over time with the establishment of specific departments and roles. As is evident from the 2023 reports of all companies, this is a matter of universal concern. As demonstrated in A2, there has been an increase in reports on climate change-related risks and opportunities. RD4 and RD5 were present in all the analyzed companies, with Iberdrola and Repsol demonstrating exceptional data quality. IBEX-35 energy companies reported higher quality (RD3) on how climate change affects their organizations (SC6), including technological adaptations (RD9), actions to mitigate reputational risk, creating departments (RD6), and adopting renewable energy infrastructure (SC7). Institutions demonstrated a greater inclination towards reporting climate-related metrics, as opposed to specific objectives (A4). RD10 represented the weakest point due to the non-mandatory nature of reporting greenhouse gas (GHG) emissions on Scopes 1, 2, and 3, resulting in a bias with regard to climate impact. Nevertheless, a significant improvement in the relevant metrics was observed in SC9, SC10, and SC11, indicating an effective adaptation to the CSRD requirements [26], which is mandatory for large public-interest entities in 2025.

To assess variations in compliance with the TCFD framework among the companies analyzed, a statistical analysis was conducted using an analysis of variance (ANOVA) on the compliance index derived from 64 financial and ESG reports. The taxonomy, which is based on 70 SCs, has enabled the quantification of adherence to the recommendations of the TCFD framework. The results of the analysis of variance (ANOVA) indicated statistically significant differences (p < 0.05) between companies, thereby highlighting that Iberdrola and Redeia achieved high levels of compliance (mean value ≈ 10), while Enagás obtained the lowest score (mean value ≈ 4). Furthermore, Tukey’s post hoc analysis was conducted, which confirmed the presence of significant differences between specific groups.

The distribution of pertinent information across numerous reports is indicative of the intricacy of the reporting process. This underscores the necessity of a thorough analysis to ensure an accurate and comprehensive evaluation.

These findings indicate that the observed variability in disclosure is attributable to company-specific internal factors. This observation lends credibility and validity to the proposed model in assessing climate-related disclosure transparency in corporate reports.

4.2. Results of the Aspect-by-Aspect Assessment of Financial and ESG Reporting

In accordance with objective O2 and question Q2, a thorough evaluation of climate disclosure was conducted, employing criteria encompassing quality, comprehensiveness, and relevance. This evaluation was methodically structured according to four TCFD priority areas: governance, strategies and opportunities, risk management, and metrics and targets.

An analysis of the 64 reports revealed significant variations in the quality, extent, and relevance of climate information disclosure, potentially due to human bias. The evaluation considered the aspects listed in

Table 8. Evaluation by aspects based on quality, extent, and relevance criteria.

Assessment Aspects of Climate Disclosure in Businesses	Enagás	Endesa	Iberdrola	Naturgy	Redeia	Repsol
1. Quality of information
•  Accuracy and reliability	Medium	High	High	High	Medium	High
•  Relevance to stakeholders	High	High	High	High	High	High
•  Inclusion of quantitative and     qualitative data	YES	YES	YES	YES	YES	YES
2. Extension of Disclosure
•  TCFD Aspects Coverage     (Governance, Strategy, Risks     Metrics, and Targets)	Partial	Partial	Complete	Partial	Partial	Complete
•  Details of actions to address     climate challenges	Limited	Limited	Detailed	Limited	Limited	Detailed
3. Relevance and Contextualization
•  TClarity of presentation	Unclear	Clear	Clear	Clear	Unclear	Clear
•  Connection with sustainability strategy	Evident	Explicit	Clear	Explicit	Explicit	Explicit

Source. Author’s own elaboration based on TCFD [4].

to reflect the results

In terms of information quality, the evaluation of accuracy and reliability was moderate in Enagás and Redeia, owing to the absence of aspects A1 (SP2), A3 (RD8), and A4 (RD9 and RD10). High ratings were allotted to Endesa, Iberdrola, Naturgy, and Repsol, although none specified RD8 or completed all A4 sections, such as RD10. All companies demonstrated a high level of relevance in terms of the information provided to stakeholders and investors, incorporating both quantitative and qualitative data. The TCFD aspect coverage was partial in Enagás, Endesa, Naturgy, and Redeia, omitting some RDs, whereas it was complete in Iberdrola and Repsol, although RD8 and RD10 were not fully addressed. Available data on climate action were limited to those of Enagás, Endesa, Naturgy, and Redeia. By contrast, Iberdrola and Repsol provided short-term objectives and detailed information on strategic plans and actions. However, both companies lack specifics regarding RD6 and RD7.

The relevance and contextualization of Enagás and Redeia for RD4 and RD5 are unclear, as these entities lack climate scenarios and transition risks. This phenomenon was evident in the case studies by Endesa, Iberdrola, Naturgy, and Repsol. A correlation between sustainability strategy and corporate performance was evident in Enagás and Iberdrola, although these companies provided fewer metrics than Endesa, Naturgy, Redeia, and Repsol. The evolution of the phenomenon under scrutiny until the year 2023 was evident, with the reports from 2023 being the most comprehensive in terms of scope and depth. While Enagás and Redeia produced fewer complete reports, all companies demonstrated improvements. Iberdrola and Repsol have been identified as two companies that have consistently demonstrated leadership in this area, although they did not demonstrate the initiative to evolve into the CSRD in RD7, despite the mandatory compliance requirements.

It was also observed that the incorporation of quantitative and qualitative data is prevalent, and each annual exercise is increasingly comprehensive. However, the coverage of certain key components, such as Scope 3 emissions, remains restricted and lacks transparency.

The findings presented herein serve to reinforce the analysis of disclosure patterns, thereby identifying key areas that require attention to enhance transparency and compliance with regard to climate reporting within the sector.

4.3. Results of Comparative Analysis of TCFD Compliance Using a Quantitative Index

To achieve a quantitative assessment of compliance with the recommendations of the TCFD, an index was developed consisting of 70 SCs, weighted uniformly. The application of this index permitted the allocation of a definitive score to each company during the specified period of analysis, thereby directly addressing the objective O3.

As illustrated in

Table 9. Index to assess mention, relevance, extension, quality, and detail of text in the 70 SCs.

Years: 2020–2021–2022–2023			E1	E2	E3	E4	E5	E6
A1	RD1	SC1—management, remuneration, periodicity, monitoring	1	1	1	1	1	1
	RD2	SC2—management, remuneration, periodicity, monitoring, sustainability committee	1	1	1	1	1	1
A2	RD3	SC3—criteria, strategy, effect, reputational risks, reporting standards, technological utilization, sustainable energy	0	0	1	1	0	1
	RD4	SC4—climate scenarios and temperature increase	0	1	1	1	1	1
	RD5	SC5—tangible risks, climate change risks, shift risks, cost reduction opportunities, financing, mortgages, sustainable financing, short-term, medium, long-term, several weather events	0	0	1	1	0	1
A3	RD6	SC6—environmental risks, prospects, shift risks, tangible risks, procedures, disclosure guidelines, compliance risks, reputation risk, economic risk, legislative controls, international agreements	1	1	1	1	1	1
	RD7	SC7—risk management strategies, materiality, emission valuation, litigation, severe weather events, renewable energy, transition costs	1	1	1	1	1	1
	RD8	SC8—strategy and crisis response	0	0	1	0	0	1
A4	RD9	SC9—reduction, CO2 emissions, refuse, energy use, water use, fuel use, renewable energies,	0	0	1	1	0	1
	RD10	SC10—Scope, CO2 emissions, CO2 units, CO2 intensity, CO2 e.	0	0	0	0	0	0
	RD11	SC11—target, reduction, CO2 emissions, refuse, energy use, water use, fuel use, renewable energies	1	1	1	1	1	1
Result/Index:			5	6	10	9	5	10

Source. The author’s elaboration is based on a company analysis of the TCFD framework [4]. Legend: (E1) Enagás, (E2) Endesa, (E3) Iberdrola, (E4) Naturgy, (E5) Redeia, and (E6) Repsol.

, SCs are delineated in the 64 reports of the six companies, and the final index reflects the total score of each company in the climate disclosure assessment. The index was derived from a comparative analysis of 64 reports. This analysis provided a detailed examination of the TCFD framework, revealing significant variations in the quality and level of detail in climate disclosure between companies. Iberdrola and Repsol attained a score of 10, Naturgy attained a score of 9, and Endesa and Redeia attained average scores of 6 and 5, respectively. Enagás received the lowest score (4), indicating the need for enhancement in the realm of climate disclosure.

A1—Governance: Organizations had specific climate risk committees and senior management was highly involved, as detailed in all reports.

A2—The following section addresses the strategies and opportunities. The TCFD (2017–2023) asserts that companies frequently demonstrate an inability to provide a rationale for climate-related projects, thereby impeding investors’ capacity to comprehend the projects’ relevance to the company’s strategic framework. For instance, a company may state that it has ‘significantly increased its projects’ without specifying which projects this refers to. At most, the company provides the name of the project in the headline. However, the economic costs of environmental actions are sometimes unspecified.

A3—Risk Assessment and Management: The absence of a resilience plan and its associated reputational implications is a pervasive trend. Despite its mention in the preceding two years, the subject has been approached from a biased perspective and lacks a clear definition.

A4—Metrics and Targets: This approach enabled the analysis to be distinguished from the standardized process, as the incorporation of numerical data, including CO₂ values, proved to be a significant factor. Furthermore, none of the six companies under scrutiny were able to cover Scope 1, 2, and 3 in their emission reporting. While Iberdrola and Endesa both demonstrated substantial reductions in their emissions—representing 14% and 4% of the IBEX-35 total, respectively—Repsol accounted for 21% of total emissions in 2023. Despite reductions in Scopes 1 and 2, Naturgy maintained the highest overall footprint, contributing 32% of the total. Despite achieving an overall reduction of 60% since 2017 (equivalent to 14.1 million t CO₂ e; 4% of IBEX-35), Endesa has experienced an increase of 7% between 2020 and 2023. Enagás has achieved a 25% reduction since 2018, while Redeia maintains commitments to improve sustainability, although it does not offer relevant data.

These findings underscore the necessity for the establishment of unified standards. The establishment of such a system has the potential to serve as a foundation for the development of metrics that can be utilized to evaluate the investor and stakeholder perceptions of a company’s sustainability initiatives, as well as its corporate reputation as a valuable intangible business asset.

5. Discussion and Implications

5.1. Discussion

In light of these findings, several discussions have emerged concerning the primary conclusions, their interpretation, comparisons with other studies, the limitations that have been identified, potential future research directions, and the implications of the study. The analysis revealed an imbalance in the four areas and information regarding the 11 RDs. This paucity of data is attributable to the limited availability of information. This aspect has seen annual improvement, with the 2023 reports being the most complete, although no company has yet fully complied with all 11 RDs. The absence of a uniform nomenclature and distribution of data across numerous reports complicates the evaluation and comparison of the TCFD compliance [13,92].

These findings are consistent with those observed in other sectors [1,3,38,79] and emphasize the discrepancy between public and private commitments and corporate actions regarding climate disclosure [80]. In their 2019 publication, Eccles & Krzus [16] proposed that companies employ sustainability reporting as a marketing tool rather than an accurate reflection of their environmental efforts. Tyagi [13] observed that although the energy sector is critical to the transition to a low-carbon economy, its current disclosure practices often fail to reflect this responsibility.

The increasing number of ESG reporting frameworks over the past two decades indicates the necessity for greater standardization in the disclosure of climate-related information, such as the CSRD [40,53]. The vast majority of corporate websites have established departments dedicated to Corporate Social Responsibility (CSR), Risk Management, or Reporting. Within these departments, ESG data are collated and analyzed, which presents a challenge in the weighting of the results and the equitable assessment of the information disclosed to investors and stakeholders [11,14,39].

In response to Q1 regarding the key patterns and levels of transparency, the text analysis revealed that Spanish energy companies have made consistent efforts to enhance their climate disclosure practices. A notable turning point was observed in 2023, the most productive year in this regard. Nevertheless, no company complied fully with all 11 RDs of the TCFD in a single report owing to the dispersion of information, and none fully covered Scope 1, 2, or 3 emissions. This difficulty in achieving full compliance with a climate-specific standard such as the TCFD, particularly regarding comprehensive emissions reporting (Scope 3), highlights the challenges widely recognized across the broader landscape of ESG reporting [76]. The dispersion of information across multiple reports under a voluntary framework also underscores the need for standardization to be pursued by regulators through initiatives such as the CSRD, which aims to consolidate and make data more comparable. Substantial disparities in GHG disclosure were revealed, with Iberdrola and Endesa demonstrating significant reductions compared to Repsol and Naturgy. These findings highlight the growing tendency towards greater standardization in reporting, anticipating European regulations such as the CSRD, although the use of multiple reports complicates a comprehensive assessment. The results indicated substantial disparities in the disclosure of greenhouse gases (GHGs) in the Spanish energy sector. It is evident that Iberdrola and Endesa demonstrated significant reductions in emissions, with respective decreases of 14% and 4% compared to the IBEX 35 average. Conversely, Repsol was identified as a major contributor to emissions, with a total emission footprint of 21%. Despite efforts to reduce its Scope 1 and 2 emissions, Naturgy’s total footprint remains the highest among IBEX-35 companies, representing 32% of the index’s total emissions in 2023. These disparities in a key climate metric emphasized by TCFD reflect the heterogeneity that presents challenges not only for climate-specific assessment but also for evaluating environmental performance within comprehensive ESG analyses [30]. The necessity for consolidated regulations, such as the European Sustainability Reporting Standards (ESRS), emerges clearly from these findings to homogenize disclosure quality and enhance transparency within the energy sector in accordance with the CSRD [28]. As Siew [37] and [80] argue, the use of multiple reports complicates a comprehensive assessment. As evidenced in the international literature, Spanish companies are found to lag in the standardization of reporting in comparison to their European and North American counterparts [16,29,39,40].

In response to Q2, the quality, scope, and relevance of the TCFD information in the Spanish energy sector showed a positive evolution. The quality of climate-related information has shown a marked improvement over time, with 2023 being the most productive year. The accuracy and reliability of the information varied among the companies, with Endesa, Iberdrola, Naturgy, and Repsol demonstrating higher levels of accuracy and reliability, while Enagás and Redeia exhibited lower scores. All the companies demonstrated a high level of relevance for stakeholders and included both quantitative and qualitative data. It is evident that both Iberdrola and Repsol achieved full coverage of the TCFD aspects and provided a greater level of detail than other companies. As time progressed, there was a demonstrable improvement in the clarity of the presentation, particularly regarding Endesa, Iberdrola, Naturgy, and Repsol. Evidently, all companies exhibited an explicit connection to sustainability strategies. Nonetheless, domains such as risk assessment and management, metrics, and targets exhibit deficiencies and inconsistencies, particularly in resilience and emission reporting, signifying the need for enhancement, and these persistent gaps in the key areas of climate disclosure within TCFD also point to potential weaknesses in broader ESG risk management and performance reporting [14,55]. These reports have been accused of “greenwashing,” a term used to describe the practice of using environmental sustainability as a marketing strategy to mislead consumers about a company’s environmental impact [52,85]. These reports have been criticized for their lack of transparency regarding company costs, with researchers calling for more detailed and precise data to be made available [84,92]. The risk of greenwashing is a significant concern across all types of ESG reporting, and findings from voluntary frameworks such as the TCFD can provide valuable insights into corporate reporting practices as mandatory requirements are implemented [90,93].

In response to Q3, practical recommendations include developing a unified report format that incorporates all TCFD recommendations. This format aims to facilitate the assessment and comparison of companies. The disclosure of risk assessment and management information, in addition to metrics and targets, is critical because of the current suboptimal level of compliance. It is incumbent upon companies to provide a quantitative perspective on climate-related financial risks and opportunities and to demonstrate a genuine commitment to the TCFD and future CSRD beyond mere public disclosure. The development of metrics for the assessment of investor and stakeholder opinions, accountability, female representation on the board, and the presence of a climate transition plan on climate governance-related disclosure, in conjunction with capacity building, will facilitate the anticipation of future regulations such as the CSRD, with a view to enhancing transparency [14,18,34]. The creation and disclosure of corporate climate change resilience plans has been demonstrated to reduce reputational risk and enhance the corporate reputation. It is incumbent on energy companies to demonstrate a genuine commitment to the TCFD framework and the future CSRD [30]. Meeting the expectations of climate disclosure under TCFD is a critical step towards achieving robust and credible broader ESG reporting [1].

Following a thorough analysis of data from 64 reports using the text mining technique, Hypothesis H1 was supported. This technique was instrumental in enabling the analysis of a substantial volume of unstructured data, the identification of patterns, and the effective assessment of compliance with the TCFD framework. Moreover, this study measured the degree of voluntary compliance of six Spanish energy companies. Furthermore, Hypothesis H2 was corroborated, as companies within the Spanish energy sector disclosed the quality, Scope, and relevance of their climate change actions, which enhanced stakeholder perceptions. This study provides evidence of gradual improvement in the disclosure of climate-related information. The year 2023 was identified as the most productive in this regard, and there has been a positive evolution in governance and strategy.

5.2. Implications

This study’s findings and methodology have important implications for research, practice, and policy.

This study proposes a pioneering methodology for analyzing unstructured textual datasets, which establishes a foundational framework for future research in the domains of sustainability and financial dynamics. The potential of this technique is manifested in the revelation of patterns that, through advanced models such as sentiment analysis, enable the examination of reviews in social networks [66]. This approach establishes a connection between data scientists and researchers in the social sciences and humanities with the potential to transform literary analysis. Furthermore, it is capable of processing large volumes of unstructured data in financial reporting, sustainability, finance, and academic research [92]. Furthermore, it has been demonstrated to facilitate the analysis of historical documents, books, and articles at a higher rate than traditional methods [93]. This finding indicates the necessity of exploring new areas of research and conducting further studies on the relationship between climate disclosure and financial performance [60].

In practice, organizations can implement an analytical approach to financial reporting, optimize the intangible aspects of corporate communication, and coordinate business actions through marketing with more accessible reports. Thus, the provision of a metric to assess corporate reputation was facilitated. Transparency in climate disclosure has become a crucial element in corporate reputation [16]. The potential of companies, analysts, and academia to utilize data science to enhance disclosure, analysis, and study processes is significant [2,43].

Regarding the policies in question, the empirical findings of the present study reveal significant differences in compliance with the TCFD among IBEX-35 companies. This indicates the heterogeneity in climate disclosure. This discrepancy highlights the need to enhance the existing regulatory framework. Consequently, the adoption of stricter regulatory measures is proposed, including the implementation of the CSRD and the incorporation of mandatory external audits, to standardize and improve transparency in ESG reporting. These recommendations are informed by empirical evidence that reveals distinct patterns of disclosure and aligns with previous studies [16,79]. The integration of these measures could contribute to improving the quality and comparability of information, benefiting investors and stakeholders. Furthermore, the involvement of the scientific community is encouraged to foster public–private collaboration, which indicates greater cooperation between businesses and the government to address climate challenges [8]. This study underscores the pivotal role of the energy sector in facilitating a transition to a low-carbon economy. This suggests that climate disclosure is assuming a crucial role in corporate governance and financial regulation, with significant implications for investment decision-making and public policy.

6. Conclusions

The findings of this study demonstrate a progressive improvement in the disclosure of the TCFD framework in the Spanish energy sector. However, none of the companies achieved full compliance, which is consistent with the findings of previous studies [3,37,39,40]. Nevertheless, in contrast to the uniformity exhibited by certain international studies in reporting consistently low levels of disclosure, this study’s findings demonstrate that companies such as Iberdrola and Repsol exhibit considerably higher levels, thereby indicating a more effective integration of sustainability strategies. Conversely, companies such as Enagás exhibit significant deficiencies, demonstrating pronounced heterogeneity within the sector. These results align with the existing literature [11,92] and underline the need for stricter regulations, such as the CSRD, to homogenize the quality and transparency of climate information [28].

The Spanish energy sector demonstrates notable variations in its adherence to the TCFD recommendations regarding the practices of disclosure and compliance. This has raised concerns regarding the level of transparency exhibited and the degree of preparedness for climate change. This study examines the participation of this sector, given its impact on carbon emissions and future European regulations on climate disclosure. Analyzing TCFD compliance provides valuable insights into the preparedness of companies for more comprehensive and mandatory ESG reporting requirements [72]. The originality of this study lies in its assessment of TCFD in the context of prospective international regulatory obligations concerning financial reporting. This assessment employed a multidisciplinary management report to formulate innovative recommendations. This study underscores the strategic significance of sustainability reporting in the context of corporate transparency, disclosure, and reputation, particularly from the perspectives of investors, non-financial professionals, and stakeholders.

The text mining technique has revealed that the sector has improved its climate disclosure, with 2023 being the most productive year. Taxonomy-based methodologies and semantic analyses were employed to conduct a rigorous review of the TCFD sustainability reports of six IBEX-35 Spanish energy companies. This study demonstrates the efficacy of data science in optimizing the analysis of non-financial metrics and highlights the utility of the TCFD compliance index in identifying discrepancies between the disclosure of six companies and their potential reputational risks. The energy sector has the potential to assume a leadership role in fighting climate change. Nevertheless, this potential is constrained by the current absence of adequate disclosure mechanisms, as pertinent areas have not been subjected to audits or formally established as mandatory disclosure requirements.

This study had several limitations. The text mining methodology is subject to limitations in terms of its capacity to capture textual or contextual nuances. Evidently, algorithmic bias is present in the automated interpretation process. The exclusive emphasis on six energy sector companies from IBEX-35 over a period of four years limits the generalizability of the results. The utilization of the TCFD protocol is not without its drawbacks; the dissemination of public information may be susceptible to scrutiny and legal action, most notably by investors.

It is recommended that future research consider the risk of corporate ‘greenwashing,’ whereby companies may exaggerate their environmental efforts or TCFD compliance in self-assessed documents. The six energy companies examined constitute approximately 75% of the total IBEX-35 Scope 3 emissions in 2023, with the largest share attributed to Repsol, Naturgy, Iberdrola, and Endesa. It is recommended that research be concentrated on sectors, such as construction and logistics. This study examines the TCFD framework in relation to intangible corporate assets, such as communication, sustainability, marketing, and reputation. The initial sustainability reports, subsequent to regulatory standardization, were subjected to text mining analysis and compared with the results of this study. It is imperative that environmental performance be measured in terms of investment results, as opposed to disclosure.

The developed index, both conceptually and methodologically, can be applied to other sectors (aviation, construction, and logistics), provided that the taxonomy is adapted and validated for each sector’s distinct reporting practices and regulatory framework. Broader applicability beyond the Spanish energy sector must be confirmed through further contextual analyses.

The index, in its conceptual and methodological development, demonstrated a high degree of adaptability, suggesting its potential for application in other sectors, including aviation, construction, and logistics. However, for such an adaptation to be successful, it is essential that the taxonomy be adapted and validated for each sector’s distinct reporting practices and regulatory framework. The broader applicability beyond the Spanish energy sector must be confirmed through further contextual analyses.

The Spanish energy sector is presented with a number of strategic opportunities, including the following: (i) the development of technologies for energy efficiency, sustainable mobility, and infrastructure modernization; (ii) the integration of corporate reputation and communication into governance strategies; (iii) the promotion of public–private collaboration to encourage renewable energy investments; (iv) the incentivization of investments in sustainable products, energies, and techniques; and (v) the training of teams in climate risks and reputation to accelerate the adoption of regulatory frameworks.

This study recommends the following: (i) the standardization of metrics and ratios that contrast verified quantitative empirical data with disclosed information and common regulations; (ii) the strengthening of external audits to validate metrics; and (iii) the prevention of greenwashing through the implementation of specific methodologies, including the utilization of advanced social-network analysis techniques, sentiment analysis, and the application of text mining with advanced discrepancy analysis. These methodologies enable the discernment of discrepancies between discourse and actual actions, thereby reinforcing the credibility of ESG reports and facilitating the identification and prevention of environmental overstatements [94]. In addition to the implementation of preventive measures, such as the establishment of sectoral benchmarks with the objective of identifying and preventing the overestimation of environmental efforts, it is essential to develop metrics and ratios. The purpose of these metrics and ratios is to contrast verified quantitative empirical data with disclosed information.

This article proposes a series of recommendations for future research, including the following: First, examining the relationship between the TCFD framework and intangible corporate assets. Second, investigating the impact of the CSRD on sustainability reporting. Third, analyzing the interactions among environmental performance, investment outcomes, and disclosure levels. Fourth, extending research into the construction, transportation, and logistics sectors. Fifth, assessing the risks of corporate reputation and damage to other intangible assets arising from greenwashing. Sixth, improving text mining techniques. Finally, conducting international comparative studies. These areas for future research should aim to enhance the comprehension of climate disclosure and refine the analytical methodologies.

Justo Villafañe’s theory of corporate image distinguishes between an organization’s internal identity “being” its values, culture, and strategic vision and its external projection “appearing” to stakeholders. Corporate credibility, he argues [6], stems from the alignment between these dimensions. Socio-technical transition theories suggest that achieving such alignment requires embedding sustainability principles into the organization’s core strategy, innovation processes, and reputation management frameworks [95]. In this context, integrating sustainability into key intangible assets such as marketing, corporate communication (both internal for employees and external via social media), and stakeholder engagement—along with responsible digital presence and comprehensive ESG reporting, enhances perceived legitimacy and positions the company as an ethical and sustainable leader [7].

Environmental protection against climate change must transcend voluntary or mandatory measures to become embedded in the organizational DNA of companies. As with the incorporation of labor rights following the Industrial Revolutions or the global consensus embodied in the 2030 Agenda (17 SDGs), sustainability today demands a systemic transformation. Only when sustainable principles shape corporate strategy, organizational culture, and action will companies be able to build genuine trust and perceived legitimacy that goes beyond mere disclosure.