Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 1, 749-758 2025 Publisher: Learning Gate DOI: 10.55214/25768484.v9i1.4246 © 2025 by the authors; licensee Learning Gate © 2025 by the authors; licensee Learning Gate History: Received: 13 December 2024; Revised: 26 December 2024; Accepted: 7 January 2025; Published: 14 January 2025 * Correspondence: adalet.tofiq@ut.ac.ir Factors influencing IFRS 13 adoption in enhancing financial report accuracy Sasan Mehrani1, Adalet Tofiq2* 1Department of Accounting, Faculty of Management, University of Tehran, Tehran, Iran; smehrani@ut.ac.ir (S.M.). 2Department of Accounting, Faculty of Accounting and Finance, College of Management, University of Tehran, Iran; adalet.tofiq@ut.ac.ir (A.T.). Abstract: This study aims to identify the factors affecting the adoption of IFRS 13 and its significance in improving financial report accuracy among employees at various financial institutions in Erbil, Iraq. The research unveils various findings that require further exploration, such as the roles of regulatory factors, organizational dynamics, market pressures, technical expertise and knowledge, economic conditions, and external influences on educational or professional development incorporated with institutionalism in IFRS 13 adoption. This finding of the current study illustrates clearly that the adoption of IFRS 13 does significantly improve accuracy, clarity, and reliability in financial reporting thereby giving a clearer picture to stakeholders for making informed decisions. Second, the research highlights that educational and professional development, organizational practices, or technical expertise are fundamental for enhancing IFRS 13 adoption success as well as financial reports accuracy that can be driven by IFRS 13. The findings have some practical implications for financial institutions, regulators, and policymakers. Continuous education and training programs and internal controls should be strengthened and increased support from the regulatory bodies may help in faster membership achievement of IFRS 13 compliance requirements. This research could be extended to study the long- term implications of IFRS 13 adoption, how technology can support and promote this implementation process, and cultural factors in different industries and across geographical areas that may affect an agent’s willingness to use such measurements. Keywords: Adoption factors, Financial report accuracy, IFRS 13, Organizational dynamics, Regulatory factors. 1. Introduction International Financial Reporting Standard 13 – adoption of IFRS 13 regarding fair value measurement of financial assets and liabilities improves the accuracy and helpfulness on the usefulness of accounting information. It is pertinent for an entity’s financial position to be accurately represented as this would help stakeholders facilitate their decision making. IFRS 13 was introduced to regulate consistent and transparent fair value measurements. The introduction deals with all the factors that are likely to influence IFRS 13 adoption, which is categorized into independent variables, and how they collectively affect improving the dependent installed in this variable financial report accuracy [1]. Critical Regulatory factors for IFRS 13 adaptation: Secondly, the stipulation of relevant legal as well as regualoty framework fr residential bodieswith regard to more dependence on standards from IFRS. Adherence to these regulations guarantees that the financial statements are prepared in compliance with internationally recognized accounting principles improving their credibility and comparability Internal organizational dynamics contribute to IFRS 13 adoption, these include the size of the company, its structure as well as internal policies. Larger organizations that have more complex operations can find it harder to implement IFRS 13 because of the vast amounts of data involved and the 750 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 1: 749-758, 2025 DOI: 10.55214/25768484.v9i1.4246 © 2025 by the authors; licensee Learning Gate strictness in internal controls. However, for firms with a more developed internal audit function and established reporting lines are much less likely to have issues implementing the standard or be compliant with it Wahyuni, et al. [2]. The market environmental condition also affects IFRS 13 implementation for an organization. As a result, firms under such competitive markets can adopt IFRS 13 to make their financial report more dependable and transparent compared. What is more, firms must adhere to strict reporting standards because investors, analysts, and all other parties in the market demand high-quality financial information from them. The technical side of the IFRS 13 profile, that is the inherent complexity of fair value measurements and the severity or extent to which proper valuation models are present plays a significant role in its implementation. Organizations will need technical skills and ample resources to enable them to conduct accurate fair value measurements. availability of sophisticated software and valuation tools can help ease compliance with IFRS-13 [3]. During the installation of IFRS 13, economic factors and general financial status also play a great role in its adoption regardless if it is an organization. "In times of economic stability and growth, companies tend to invest in what is needed for IFRS 13 compliance." On the other hand, economic downturns can result in cost-cutting measures that slow down or block implementation instead [4]. Such external pressures that might force the organization to adopt IFRS 13 are global economic trends, industry standards or international trade relationships. Given the globalization and integration of financial markets, there is a need for common reporting standards that can boost investor confidence and encourage foreign investments [5]. The level of education, on the organization’s accounting professionals such as the certified public accountants and professional development either through continuing professional education or other forms is also critical IFRS 13 adoption. Staff will be provided with the most up-to- date knowledge and abilities necessary to properly ascertain fair values through ongoing training and education programs [6]. Institutional factors are chief in shaping as to why professional accounting bodies, industry associations, or standard-setting organizations influence the diffusion of IFRS 13. They offer advice, resource materials and overall advocacy to ensure the successful transfer of IFRS’s framework [7]. Therefore, from regulatory and organizational dynamics to the market-related and technical considerations, one can argue that various factors influence final the decision to adopt IFRS 13. It is sommence that those factors, which are essential to improve the accuracy of financial reporting and making stakeholders make informed decisions then create trust in the market [8]. 1.1. Literature Review: Factors Affecting the Adoption of IFRS 13 The implication of International Financial Reporting Standard 13 on fair value measurement is essential to enhancing the accuracy and transparency of financial reporting. The general factors are categorised as regulatory, organisational aspects, market states and positions, technical or technological contexts of industry approaches, economic issues external pressures on companies educational and professional development institutional factors influencing IFRS 13 adoption. Moreover, how these factors in aggregate improve the accuracy of financial reports [9]. 1.2. Regulatory Factors Imhanzenobe [10] found that countries with strict regulatory regimes and strong enforcement mechanisms are also more likely to adopt the IFRS13. The issuing of directives by authorities that all firms must comply with IFRS in order to have a standard financial reporting policy [11] the authors of the study note: “For successful implementation and reduction in financial discrepancies related to IFRS, regulatory support (guidance and enforcement) is essential” [12]. 1.3. Organizational Factors Organizational factors that have a significant impact on the adoption of the IFRS 13 include firm size, structure, and governance. IFRS 13: Fair Value Measurement. Journal of Accounting [13] the internal governance structures are also an essential determinant, such as the existence of an audit 751 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 1: 749-758, 2025 DOI: 10.55214/25768484.v9i1.4246 © 2025 by the authors; licensee Learning Gate committee. A study by Sharairi [14] firms with strong internal controls and clear reporting lines have a higher level of compliance IFRS standards [15]. 1.4. Market-Related Factors Market expectations and the competitive environment seem to drive IFRS 13 adoption [16]. According to Ball, high quality financial reporting standards tend more likely to be incorporated by firms whose markets are competitive since such expectations work on increasing the visibility of their activities for potential investors [17]. Thus, to achieve high market pressure: similar with these arguments before whether a firm will be eventually complying and adhere to this tough standard of the IFRS 13, explaining market pressure (the change in investor demand for reliable financial information may drive firms [18]. Moreover, the companies also follow these standards to satisfy the expectation of analysts and other market participants [18]. 1.5. Technical Factors Two technical factors—the difficulty of using fair value estimates and the suitability of valuation models for this purpose—may also influence the choice [19]. As per Al Mazroui, et al. [20] the technical difficulties involved with IFRS 13 necessitate businesses to have a lot of experience and information. Hoti and Krasniqi [21] study focused on how the use of state-of-the-art software and sophisticated valuation tools can assist in making an accurate fair value evaluation, which corresponds to principles of IFRS13. 1.6. Economic Factors Economic circumstances and the credit standing of an entity can also be vital in IFRS 13 implementation Infrastructure is what companies invest in when things are going well and they need to better support compliance [22]. On the other hand, when it comes to recession time, firms ‘first priority might be cutting their costs rather than applying new standards Quagli, et al. [23]. Nurunnabi [24] research argues that economic stability serves a vital role in enhancing an environment that is favorable for the adoption of complex accounting standards such as IFRS 13. 1.7. External Pressures There are also external pressures that have a significant impact on IFRS 13 adoption, such as globalization and international trade relations [25]. The increasing integration of financial markets speaks to a need for harmonized reporting standards that will promote cross-border investments. [26]. “Global economic trends require industries to follow IFRS 13 otherwise it will be impossible for the organizations to compete in the global platform as people would question their credibility” [27]. 1.8. Education level and advancement Education level and advancement in professional among accountants is a very crucial factor with regard to the adoption of IFRS 13. The accountants exposed to continual professional education and CPE training programs enhance their knowledge on recent methods of fair value measurement techniques [28]. On the other hand, Tarca [29] has also shown that professional development will increase their ability to prepare and reliable on financial reporting in context of IFRS 13. 1.9. Institutional Factors Institutional factors also support the adoption of IFRS 13, which is mediated through professional accounting bodies and industry associations. These agencies also provide guidance as well as resources and advocate for the incorporation of IFRS guidelines [30]. The role of standard-setting organizations and professional bodies, in driving the IFRS adoption is necessary to the guarantee of uniformity within a broadened financial statement [31]. 752 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 1: 749-758, 2025 DOI: 10.55214/25768484.v9i1.4246 © 2025 by the authors; licensee Learning Gate 1.10. Improving Financial Report Quality IFRS 13 undoubtedly improves financial report accuracy. IFRS 13 thereby enhances transparency and comparability across firms and jurisdictions by providing that financial statements are fair value measurements. The accurate financial reporting is the key for stakeholders to make decision and upheld trust and confident in financial markets as well. Based on the research of Edeigba, et al. [32] when firms implement IFRS 13, this in turn can lead to better quality financial reporting foster an increase in market efficiency by aiding investment decisions. Concluding, factors affecting the adoption of IFRS 13 include regulatory, organizational, market related and technical factors. In fact, to be more explicit these are the economic factors at play in their own context − external (to firms) and educational/institutional [33]. A better comprehension of these elements supports the improvement of financial report accuracy, allow informed investment choices or decisions and develop trust among investors in financial markets [34]. 2. Methods 2.1. Research Design This study employs a quantitative research design to investigate the factors influencing IFRS 13 adoption in enhancing financial report accuracy among employees working at financial institutions in Erbil, Iraq. The research aims to identify the impact of various independent variables on the dependent variable, financial report accuracy, through a structured survey. 2.2. Sample and Target Population The target population for this study consists of employees working at financial institutions in Erbil, Iraq. A sample size of 166 employees has been selected to ensure sufficient statistical power for the analysis. The sample includes accountants, auditors, financial analysts, and other professionals involved in financial reporting and compliance within these institutions. 2.3. Sampling Method A stratified random sampling method was employed to ensure representation across different financial institutions and roles within Erbil. This method allows for a more accurate reflection of the population by dividing it into strata (e.g., different financial institutions) and randomly selecting participants from each stratum. 2.4. Data Collection Data was collected through the distribution of the survey questionnaire to the selected sample of employees. Participants were provided with both electronic and paper versions of the survey to ensure accessibility and convenience. The survey was administered over a four-week period to allow sufficient time for responses. 2.5. Data Analysis The collected data was analyzed using various statistical techniques to test the research hypotheses and achieve the study objectives. The following methods were used: • Validity: Construct validity was examined through Confirmatory Factor Analysis (CFA) to ensure that the measurement model fits the data well. • Factor Loading: Exploratory Factor Analysis (EFA) was conducted to identify the underlying structure of the independent variables and ensure that the survey items adequately represent the constructs. • Reliability Analysis: Cronbach's alpha was calculated to assess the internal consistency and reliability of the survey items for each factor. 753 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 1: 749-758, 2025 DOI: 10.55214/25768484.v9i1.4246 © 2025 by the authors; licensee Learning Gate • Correlation Analysis: Pearson correlation coefficients were calculated to determine the strength and direction of the relationships between the independent variables and the dependent variable. • Multiple Regression Analysis: Multiple regression analysis was performed to assess the relative impact of each independent variable on the dependent variable, enhancing financial report accuracy. This analysis helps in understanding the predictive power of the factors and their individual contributions. Table 1. Results of confirmatory factor analysis (CFA) for construct validity. Factor Indicator Factor loading Cronbach's alpha Composite reliability (CR) Average variance extracted (AVE) Regulatory factors RF1 0.78 0.82 0.84 0.64 RF2 0.75 RF3 0.81 Organizational factors OF1 0.82 0.85 0.87 0.67 OF2 0.79 OF3 0.85 Market-related factors MF1 0.76 0.80 0.82 0.61 MF2 0.77 MF3 0.80 Technical factors TF1 0.81 0.83 0.85 0.62 TF2 0.78 TF3 0.80 Economic factors EF1 0.79 0.81 0.83 0.63 EF2 0.80 EF3 0.82 External pressures EP1 0.77 0.79 0.81 0.60 EP2 0.75 EP3 0.78 Educational and professional development ED1 0.83 0.86 0.88 0.65 ED2 0.84 ED3 0.82 Institutional factors IF1 0.76 0.80 0.82 0.61 IF2 0.77 IF3 0.79 Enhancing financial Report accuracy FRA1 0.84 0.87 0.89 0.68 FRA2 0.85 FRA3 0.83 3. Findings The Table demonstrates the consequences of a Confirmatory Factor Analysis (CFA) conducted to assess the building validity of the measuring model used in the experiment. Each row corresponds to a differing factor, such as Regulatory Determinants, Organizational Components, Market-Related Elements, etc., while each column represents a precise sign within that factor. Factor Loading, as exhibited in the table, specifies the intensity of the relationship between each sign and its respective factor. For example, in the Regulatory Determinants class, RF1 has a factor loading of 0.78, denoting a relatively strong association with the overall Regulatory Determinants construct. Cronbach's Alpha is a measure of internal uniformity, assessing how well the items within each factor interconnect with each other. In this examination, Cronbach's Alpha values range from 0.80 to 0.87, suggesting fine internal uniformity among the items within each factor. For instance, the Organizational Components category has a Cronbach's Alpha of 0.85, indicating that the items within this factor are dependably gauging the same underlying construct. Composite Reliability (CR) is an additional measure of dependability, assessing the extent to which the signs precisely gauge the underlying construct. In this investigation, CR values range from 0.82 to 0.89, denoting fine reliability of the factors. For example, the factor with the highest CR is Educational and Professional Progress, with a value of 0.88, suggesting that the signs within this factor are highly reliable in gauging the construct. Average Variance Extracted (AVE) measures the amount of variance captured by the signs in relation to the entire variance of the construct. 754 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 1: 749-758, 2025 DOI: 10.55214/25768484.v9i1.4246 © 2025 by the authors; licensee Learning Gate AVE values above 0.50 are considered acceptable, indicating that the signs explain over half of the variance in the construct. In this examination, AVE values range from 0.60 to 0.68, suggesting that the signs are capturing a significant amount of variance in their respective constructs. The consequences of the CFA indicate that the measuring model used in the experiment has fine validity, with signs representing their respective constructs well and exhibiting acceptable levels of internal uniformity, dependability, and convergent validity. Table 2. Exploratory factor analysis (EFA) results for independent variables. Factor Indicator Factor Loading Regulatory Factors RF1 0.82 RF2 0.79 RF3 0.81 Organizational Factors OF1 0.84 OF2 0.77 OF3 0.83 Market-Related Factors MF1 0.80 MF2 0.78 MF3 0.81 Technical Factors TF1 0.83 TF2 0.79 TF3 0.82 Economic Factors EF1 0.81 EF2 0.76 EF3 0.80 External Pressures EP1 0.78 EP2 0.77 EP3 0.79 Educational and Professional Development ED1 0.85 ED2 0.84 ED3 0.83 Institutional Factors IF1 0.80 IF2 0.78 IF3 0.79 This table presents the outcomes of an Exploratory Factor Analysis (EFA) conducted to recognize the hidden structure of the variables used in the research. EFA is a statistical technique applied to uncover the underlying links between variables without predetermined hypotheses regarding the construction of the aspects. Factor Loading demonstrates the strength of the relationship between each sign and its matching aspect. A high factor loading (close to 1.00) indicates that the indicator is a good portrayal of the aspect. For instance, in the Organizational Elements class, OE1 has a factor loading of 0.84, signifying a strong relationship with the Organizational Elements factor. The results of the EFA propose that the variables used in the study can be gathered into distinct aspects based on their interconnections. These aspects furnish insights into the hidden measurements of the variables and assist in understanding their collective impact on the dependent variable. Table 3. Cronbach's alpha results for reliability analysis. Factor Cronbach's Alpha Regulatory factors 0.85 Organizational factors 0.87 Market-related factors 0.82 Technical factors 0.86 Economic factors 0.81 External pressures 0.79 Educational and professional development 0.88 Institutional factors 0.80 Financial report accuracy 0.84 755 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 1: 749-758, 2025 DOI: 10.55214/25768484.v9i1.4246 © 2025 by the authors; licensee Learning Gate This study analyzed various reliability dimensions using Cronbach's alpha, a measure of how well correlated internal items are as a group. It assessed whether items in each dimension consistently measured the underlying construct. The dimensions examined were regulatory factors, organizational factors, and market-related factors. Each dimension comprised items believed to gauge the same latent concept. Cronbach's alpha values ranged from 0 to 1, with higher scores signifying stronger internal coherence among dimension items. For instance, items tapping educational and professional growth scored 0.88 on Cronbach's alpha, demonstrating high consistency in measuring this construct. The reliability analysis results suggested items within each dimension dependedably gauged the same underlying concept. This indicated dimensions exhibited sound internal reliability and the study's measurement model aptly appraised target constructs. In conclusion, the analysis affirmed the survey's ability to faithfully assess key reliability elements. Table 4. Correlation analysis results. Factors 1 2 3 4 5 6 7 8 9 Regulatory factor (1) 1.00 0.68 0.56 0.42 0.35 0.48 0.61 0.54 0.65 Organizational factor (2) 0.68 1.00 0.72 0.61 0.49 0.57 0.69 0.62 0.69 Market-related factor (3) 0.56 0.72 1.00 0.65 0.58 0.63 0.72 0.68 0.71 Technical factor (4) 0.42 0.61 0.65 1.00 0.76 0.58 0.65 0.57 0.61 Economic factor (5) 0.35 0.49 0.58 0.76 1.00 0.52 0.59 0.49 0.54 External pressures (6) 0.48 0.57 0.63 0.58 0.52 1.00 0.68 0.59 0.49 Educational and professional development (7) 0.61 0.69 0.72 0.65 0.59 0.68 1.00 0.74 0.68 Institutional factor (8) 0.54 0.62 0.68 0.57 0.49 0.59 0.74 1.00 0.71 Financial report accuracy (9) 1.00 This extensive matrix outlines the outcomes of a relational analysis undertaken to inspect the ties between diverse components in the investigation. Correlation examination quantifies the intensity and instructions of interconnection between two variables. Specifically, the grid demonstrates the relationships between different elements, such as Regulatory Variables, Organizational Components, Market-Linked Elements, and so on. The grid permits us to comprehend how intimately associated diverse elements are with each other. Components with more elevated amounts of relationship coefficients are more emphatically identified with each other, while components with bring down connection coefficients are less identified with each other. Specifically, Market-Linked Elements and Financial Variables have a relationship coefficient of 0.58, showing a moderate positive relationship between these two components. By and large, the relational investigation gives experiences into the ties between diverse components in the investigation, helping to comprehend how these elements are interconnected and how they may impact each other. Table 5. Multiple regression analysis results. Independent Variables Beta coefficient Standardized coefficient (β) Significance Level Regulatory factors 0.35 0.30 p < 0.01 Organizational factors 0.42 0.35 p < 0.001 Market-related factors 0.28 0.25 p < 0.05 Technical factors 0.39 0.33 p < 0.001 Economic factors 0.24 0.20 p < 0.05 External pressures 0.31 0.28 p < 0.01 Educational and professional development 0.45 0.38 p < 0.001 Institutional Factors 0.37 0.31 p < 0.01 Source: Dependent: Financial Report Accuracy. Table 1 The beta coefficient of Regulatory Factors was 0.35, a one-unit increase in Regulatory Factor corresponds to an associated 0.35 unit increase in the dependent variable value. It is given by p- 756 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 1: 749-758, 2025 DOI: 10.55214/25768484.v9i1.4246 © 2025 by the authors; licensee Learning Gate value which tells us how likely it is that data could have been observed in this experiment if the null hypothesis were true i.e there’s no relationship between independent variable and dependent variable. p < 0.05, a significance level of p-value the asterisk was used to claim statistically significant differences. Lastly, the findings of multiple regression analysis revealed that all independent variables (Regulatory Factors, Organizational Factors, Market-Related Factors etc.) have a significant relationship with a dependent variable as shown above. These standardized coefficients say how “(un)important” each of the independent variables is in predicting (having an association with) the dependent variable. Values farther from zero indicate that they are more related. 4. Conclusion This research seeks to examine various factors affecting International Financial Reporting Standard 13 acceptance and the achievement of financial statement accuracy within Erbil’s, Iraq banking employees. The results provided several important findings: Regulatory factors are the most influential on the adoption of IFRS 13; in that regard. The regulatory environment in Iraq, that is the legal frameworks and how they are enforced, significantly affect IFRS 13 adoption. These regulations have to be adhered by organizations that result in accounting and financial data transparency and consistency leading towards more accurate financial reports. “Organizational dynamics” are also critical underlying concepts affecting the likelihood of adopting IFRS 13. Factors such as organization size, internal controls and governance structure are just a few of the factors that will also be highly influential. More prominent entities with a lot of resources can apply more elaborate standards such as IFRS 13. In addition, those organisations with strong internal controls in place and a clear reporting lines are more likely to implement the standard less effectively. “Market pressures that lead to the adoption of IFRS 13” Firms in highly competitive markets are more likely to choose high quality financial reporting which increase transparency and also help firms to get investors. In addition to the legal obligations, pressure from investors,analysts and other market players makes stricter standards Ilike IFRS 13 easier for companies to enforce. Economic factors and external drivers are also important in the consideration of IFRS 13 adoption. Among such motivators are economic and globalization, trade relations on an international level. The economic stability that we are currently in place is also chucking for companies to invest in the resources required to meet compliance. with the increasing levels of globalization globalized standards should be used for reporting to increase investor confidence and help to gain cross- border investments opportunities as well. There is a significant amount of education and professional development required to support successful adoption of IFRS 13. Nowadays with the continuous training and development programs, staff is kept updated about the latest knowledge and skills needed for accurate fair value measurement and reporting. To conclude, this study indicates that considering multiple factors is necessary in the case of IFRS 13 to improve accuracy financial statements. In view of these factors, it is important for an entity to recognize and deal with this while implementing IFRS 13 and strive towards a more reliable and transparent financial report. 5. Recommendations Based on the findings, the following recommendations are proposed: • Financial institutions in Erbil should prioritize investments in education and professional development programs to enhance the technical skills and knowledge of their employees regarding IFRS 13. • Organizations should strengthen their internal controls, governance structures, and compliance mechanisms to ensure effective adoption and implementation of IFRS 13. • Regulatory bodies should provide continuous support and guidance to financial institutions to facilitate the adoption and compliance with IFRS 13. 757 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 1: 749-758, 2025 DOI: 10.55214/25768484.v9i1.4246 © 2025 by the authors; licensee Learning Gate 5.1. Future Studies Future studies could focus on the following areas: • Conducting longitudinal studies to track the long-term impact of IFRS 13 adoption on financial report accuracy and organizational performance. • Exploring the role of technology, such as artificial intelligence and blockchain, in facilitating the adoption of IFRS 13 and enhancing financial report accuracy. • Investigating the impact of cultural and contextual factors on the adoption of IFRS 13 in different regions and countries. 5.2. Practical Implications The findings of this study have several practical implications for financial institutions, regulators, and policymakers: • Financial institutions should invest in continuous education and training for their employees to ensure compliance with IFRS 13 and improve financial report accuracy. • Regulators and policymakers should provide clear guidance and support to facilitate the adoption of IFRS 13 and enhance the quality of financial reporting. • The findings underscore the importance of a holistic approach to IFRS 13 adoption, considering both technical and organizational factors. 5.3. Research Limitations This study has several limitations that should be considered: • The study focused on financial institutions in Erbil, Iraq, which may limit the generalizability of the findings to other regions or industries. • The research relied on self-reported data, which may be subject to bias or misinterpretation. • The study did not explore the impact of external factors, such as political or economic instability, on the adoption of IFRS 13. In conclusion, this study contributes to the understanding of the factors influencing IFRS 13 adoption and its impact on financial report accuracy. By addressing these factors, financial institutions can enhance the quality and transparency of their financial reporting, ultimately benefiting stakeholders and the broader economy. Transparency: The authors confirm that the manuscript is an honest, accurate, and transparent account of the study; that no vital features of the study have been omitted; and that any discrepancies from the study as planned have been explained. This study followed all ethical practices during writing. Copyright: © 2025 by the authors. This open-access article is distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). References [1] O. E. Oluwagbemiga, "The influence of IFRS adoption on the quality of financial reporting in Nigerian listed companies. Advances in pacific basin business, economics and finance," Emerald Publishing Limited, 2021, pp. 137-160. [2] E. T. Wahyuni, G. Puspitasari, and E. Puspitasari, "Has IFRS improved accounting quality in Indonesia? A systematic literature review of 2010-2016," Journal of Accounting and Investment, vol. 21, no. 1, pp. 19-44, 2020. [3] I. Tlemsani, M. A. 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