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Section Finance Management

Role of Financial Technology and Electronic Auditing in Developing Accounting Measurement Methods for Digital Assets and Cryptocurrencies

Vol. 21 No. 3 (2026): Agustus:

Ridha Mohanad Al-Salman (1), Hashim Haydar Al-Sarraf (2), Ilham Abdul Hussein (3), Karrar Saleem Hameedi (4)

(1) Al-Furat Al-Awsat Technical University , Iraq
(2) University of Kufa, Najaf, Iraq
(3) Al-Qasim Green University, Iraq
(4) University of Kufa, Najaf, Iraq

Abstract:

General Background: The rapid expansion of digital assets and financial technology has created new challenges for accounting measurement, auditing practices, and financial reporting systems. Specific Background: Traditional accounting approaches often face difficulties in recognizing, measuring, and disclosing digital assets due to their unique technological and economic characteristics. Knowledge Gap: Despite growing interest in digital assets, limited empirical evidence exists regarding the combined role of financial technology and electronic auditing in developing accounting measurement practices. Aims: This study examines the role of financial technology and electronic auditing in developing accounting measurement for digital assets. Results: The findings indicate strong positive relationships among financial technology, electronic auditing, and accounting measurement development. Regression analysis shows that financial technology and electronic auditing significantly contribute to accounting measurement development, with financial technology demonstrating the stronger contribution. The model explains 70.5% of the variation in accounting measurement development. Novelty: The study integrates financial technology and electronic auditing within a single framework to explain improvements in accounting measurement for digital assets. Implications: The findings support the development of specialized accounting standards, advanced electronic auditing systems, digital infrastructure, and professional training programs to improve the measurement, disclosure, and auditing of digital assets.


Keywords: Financial Technology, Electronic Auditing, Digital Assets, Accounting Measurement, Blockchain Accounting


Key Findings Highlights


Financial technology showed the strongest contribution to measurement development.


Audit digitalization supported greater data verification and transparency.


The proposed model explained a substantial proportion of variance in reporting practices.

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I. Overview

The contemporary corporate environment has experienced a fundamental upheaval in recent years owing to the rapid advancement of digitalization.. This is because the value of an item is no longer solely determined by its physical capital, such as land and traditional assets, but rather by the increasing junctures between value creation (The creation of innovative products and services through digital technology).

and corporate valorization, or establishing competitive advantage using businesses to create people. New types of intangible assets (such cryptocurrencies, digital platforms, electronic wallets, and big data) have emerged in the current era of the digital economy, posing fundamental challenges to traditional accounting concepts regarding recognition, measurement, and disclosure.

Therefore, even this reality serves as a significant motivator for a methodological review of the accounting measurement pillars in order to thematize their alignment with the digital paradigm. It also facilitates the discussion of whether FinTech tools and E-Audit mechanisms could enhance comparability, transparency, and reliability. The significance of this change has increased in light of recent advancements in standard-setting. With the release of Accounting Standards Update (ASU) No. 2023-08 in December 2023, the Financial Accounting Standards Board (FASB) established a distinct accounting subtopic for cryptocurrency assets (ASC 350-60) and required that organizations assess these assets at fair value and acknowledge the fluctuations in fair value in net income, including either no assistance or limited valuation-rights-based measures, effective for fiscal years commencing after December 15, 2024(FASB, 2023). In contrast, the 2019 IFRIC Agenda Decision, which instructed organizations to apply IAS 38 or IAS 2 based on intent with regard to holding of intangible assets, continues to be the foundation of IFRS Standards.

Second. Methods of Research

1. Research Issue

The research issue is the absence of a specific standard-setting regime for digital assets, which has resulted in notable measurement inconsistencies among businesses, as well as disparate measurement approaches and implications for understanding entity market cap stakeholders. Classifying these digital assets under the umbrella of current international norms presents another unique challenge because highly volatile, decentralized, and openly tradable assets are usually not accommodated by traditional measurement model bases like historical cost and fair value. The study seeks to address the following question in this context:

2. Research Importance

This study is significant because it highlights the irrelevance of conventional measurement methods and shows that finding an accounting solution for digital assets is not only related to their identification but also represents a more serious dilemma. This is significant from a practical standpoint since more advanced techniques like FinTech and E-Audit could be used to enhance the qualitative aspects of financial reporting's dependability and verifiability. In view of recent advances in the standard-setting industry, especially after ASU 2023-08, which represents a shift from the (cost less impairment) model to changes being accounted for fair value through profit or loss, that research becomes even more crucial.

3. Research Goals

4. Research Theories

Hypotheses 0 H₀: The development of accounting measurement techniques for digital assets is statistically significantly influenced by financial technology and electronic auditing. It generates two sub-hypotheses:

• Hypothesis 1 (H₁): Financial technology has a statistically significant impact on the development of accounting measurement techniques for digital assets.

• H₂: Electronic auditing has a statistically significant impact on the development of accounting measurement techniques for digital assets.

5. Model of Research

Financial Technology (FinTech) H₁ ←──── Effect ────→ Developing Accounting Measurement Methods for Digital Assets
Electronic Auditing (E-Audit) H₂ ←──── Effect ────→
Table 1.

6. The population, sample, and methodology used in the research

Descriptive-analytical research methodology was employed. There are 1,583 responders, including accountants, internal and external auditors, accounting scholars, and employees of financial and regulatory organizations. Due to their backgrounds in oversight and accounting, this study used a purposeful sample of these pertinent individuals. The research tool, a five-point Likert scale questionnaire, was divided into four components. Expert reviewers were used to demonstrate the validity, while Cronbach's alpha coefficient was used to assess the retest reliability. Analyses Descriptive statistics, reliability testing, and hypothesis tests (Pearson coefficient, linear regression, F-test, and t-test) were used to analyze the data using the Statistical Package for the Social Sciences (SPSS).

Third. Previous Research

In recent accounting and financial literature, digital assets and cryptocurrencies have sparked scholarly discussions on a number of topics, including fair value applications, accounting measurement concerns, the role of blockchain and financial technology in forward-looking auditing, and financial disclosure. An outline of the most significant earlier studies, arranged by date, is provided below:

The current study's contribution and its position in relation to earlier research

Upon examination of the aforementioned, it is clear that most prior research has focused either on the technical dimension (blockchain and continuous auditing) or the standard-setting aspect (i.e., accounting treatment of cryptocurrencies under IFRS/GAAP) without synthesizing the two perspectives. The present study seeks to address this deficiency by:

IV. The Foundations of FinTech, Auditing, and Measurement Development Knowledge

1. Theoretical and Accounting Issues with Digital Asset Measurement

There is a great deal of variation in practices due to the absence of a specific framework for standard-setting. According to the literature, some businesses categorize cryptocurrencies as either inventory in accordance with IAS 2 or an intangible asset pursuant to IAS 38 because they lack a separate standard under IFRS (Shaheen et al., 2025: 103). The IFRS Interpretations Committee Agenda Decision from June 2019 addressed recent questions about how cryptocurrencies should be treated in financial statements It indicated that cryptocurrencies holdings do not qualify as cash or a financial asset, and default is governed by IAS 38; if held for sale in normal operation of business, IAS 2 is applicable.

.

This recognition directly affects judgment, especially in light of the comparatively lax rules currently in place regarding ownership and physical presence of the digital asset, which would undermine one of the qualitative features, namely verification (Hijazi, 2023: 561; Mohamed, 2023: 650). Furthermore, despite price fluctuations in sharp edges caused by speculation, demand exceeding supply (Grant Thornton, 2025), or the application of fair valuation under IAS 38, the historical cost model fails to replicate the true value, making it impossible to create an active market for every cryptocurrency.

Treatment of Crypto Assets under US GAAP and IFRS

Based on technical publications published by major international audit firms (KPMG, 2024; Deloitte, 2023) and an official FASB pronouncement (FASB, 2023), the researcher provided a well-collated table outlining some of the key standard-setting differences between these two international frameworks post-issuance of ASU 2023-08 to enhance this section:

Table (A): IFRS vs US GAAP Readiness in Handling Crypto Assets (Scholarly Contribution)

Comparison Item IFRS (IFRS IC 2019 + IAS 38/IAS 2) US GAAP (ASU 2023-08 / ASC 350-60)
Classification Intangible asset (IAS 38) or inventory (IAS 2) if maintained for sale in the regular course of business. Intangible asset within an independent subtopic (ASC 350-60)
Subsequent Measurement Cost model or revaluation model (requires an active market) Mandatory fair value measurement under ASC 820 at each reporting date
Treatment of Changes Impairment → profit or loss; Revaluation → typically Other Comprehensive Income All fair value changes → directly to net income
Impairment Annual test under IAS 36; impairment loss cannot be reversed for intangible assets with an indefinite useful life Abolished — replaced by remeasurement at fair value
Disclosure General requirements under IAS 1, IAS 38, and IFRS 13 Detailed disclosures by name, quantity, fair value, cost basis, and contractual restrictions
Effective Date Effective since 2019 (non-binding Agenda Decision without issuance of an independent standard) Fiscal years commencing subsequent to December 15, 2024, with early adoption allowed
Table 2.

2. Developing Accounting Measurement Techniques with Financial Technology

It serves as a roadmap for addressing the gaps in current paradigms. The umbrella term Financial Technology (FinTech) can be used to address conventional questions and problems. Transaction recording and real-time revaluation have been transformed by blockchain and big data technology (Bonsu, 2025: 15). Transparent and instantaneous ownership monitoring is made possible by blockchain technology, a distributed ledger recognized in almost every other field (Tufael, 2025: 140). It closes this information gap and increases the verifiability of goods produced by transforming the industry to move through Continuous Measurement and offering platforms for trading that serve a price discovery function (Ojha et al., 2023: 114).

Classification of FinTech Tools and Their Impact on Accounting Information's Qualitative Features

According to the “Conceptual Framework for Financial Reporting” (IASB Conceptual Framework, 2018), the researcher offers the following classification, connecting each FinTech instrument (i.e., its categories) with its direct impact on the qualitative aspects of accounting information.

Table (B): Classification of FinTech Tools and Their Effect on Information Characteristics (Scholarly Contribution)

Tool Measurement Function Increased Qualitative Attribute
Blockchain A distributed ledger designed to track ownership and maintain an immutable history of records Verifiability + Reliability + Faithful Representation
Artificial Intelligence (AI/ML) Modeling volatility and estimating fair value in inactive markets (events or absence of them) Relevance + Predictive Value
Big Data Market data to be collected and analyzed in real time from a wide range of sources Relevance + Completeness of Information
Smart Contracts Automating the performance of obligations and better recognition of accounting changes Timeliness + Neutrality + Reduction of Human Discretion
Internet of Things (IoT) Connection of digital assets to real data sources for instant value refresh Relevance + Reliability
Table 3.

3. Enhancing the Accuracy of Accounting Measurement via Electronic Auditing

Because digital assets are unique, the auditing framework will need to change. Since the traditional examination is no longer being conducted, the emphasis on the concept of Electronic Auditing (E-Audit) and consistent auditing has become a spontaneous response to advanced development (Farras et al., 2025: 506). Instead of utilizing a sample, big data analytics enables auditors to examine every transaction, increasing the possibility of finding anomalous patterns (Huang et al., 2022: 138). This shows that the oversight and audit quality are directly tied to the measurement. Therefore, integrating electronic auditing into the measuring framework is thought to be one of the pertinent approximations to professional best practices in accounting to improve its qualitative features like faithful representation and verifiability.

4. Creating Measurement Techniques through FinTech and Electronic Auditing Integration

Financial technology functions as an information system that effectively incorporates technological advancements to improve financial operations, and electronic auditing is an integrative relationship that ultimately focuses on the unmet need of accounting in digital asset measurement techniques. Eight axes can be used to visualize this integration:

1: FinTech's Contribution to the Transition to Real-time Measurement

By converting the periodic measurement model based on historical cost into a continuous measurement model, the scope of financial technology aids in reshaping the accounting cycle for digital assets. Second, because the fair value model is based on actual, verifiable pricing, it may be applied in its purest form thanks to blockchain technology's connection to trading platforms that provide real-time market data (Ojha et al., 2023: 114).

2: the use of electronic auditing can improve measurement models' dependability.

No technique for accounting measurement can be created without a digital regulatory system intended to verify and enforce the integrity of data supplied into valuation models. This is where Electronic Auditing comes in, using big data analytics to examine electronic wallets to verify true ownership and evaluate each transaction related to those digital assets. The risk of overstating reported fair values is reduced by switching from traditional auditing to real-time auditing (Huang et al., 2022: 138).

3: Linking Technology, Audit, and Quality

There is a high correlation between measurement quality and oversight quality, according to the applied literature. The capacity to apply precise accounting standards supported by reliable electronic auditing techniques clearly demonstrates an increase in the organization's market value. Therefore, it is more or less professional to include electronic auditing in the measuring framework in order to provide qualitative aspects of accounting data, particularly verifiability (Chen, 2023: 35–36).

Fourth: Improving Measurement and Associated Problems with All-Inclusive Digital Solutions

In order to obtain more accurate estimates of economic value, a FinTech system must borrow artificial intelligence and the Internet of Things due to the credibility crisis of traditional measurement models for digital assets, which is demonstrated by the various ways to classify these assets (inventory or intangible asset). The absence of practical guidelines for proof of existence and ownership led to the development of electronic auditing (Hijazi, 2023: 561).

Fifth: Using FinTech and Electronic Auditing to Manage Measurement Risk

Due to their intrinsic volatility, digital assets and cryptocurrencies carry a significant risk of material misstatement when measured using conventional methods. Financial technology uses artificial intelligence algorithms to forecast volatility and provide more objective and prudent fair value valuations (Shehata, 2023: 383), while electronic auditing allows for ongoing security monitoring of distributed ledgers to reduce the risk of breaches or manipulation (Chen, 2023: 35).

Sixth: Automating smart contract measurement and verification processes

The adoption of smart contracts is seen as a turning point in the convergence of auditing and accounting. As soon as predetermined criteria are satisfied, these contracts automatically initiate accounting transactions and alter the values of digital assets, minimizing human intervention and subjective assessments in measurement (Appelbaum et al., 2017: 23). In order to ensure that measures are hitting into financial statement policies, Auditing Online Research examines the regulatory programming code and algorithms (Algorithm Audits) either before or during operation (Turki, 2024: 376).

Seventh: Encouraging Financial Disclosure and Reducing Information Asymmetry

The knowledge gap between investors and management due to technical complexity is one of the main issues with accounting for digital assets. FinTech platforms are used to reduce information asymmetry (Ojha et al., 2023: 114). Electronic and continuous auditing systems help extract risk indicators (Red Flags) based on big data, which improves the comprehensibility and comparability of accounting measurement outputs (Yousef et al., 2025: 381).

Eighth: Integrating Intelligence to Address Standard Setting and Regulatory Compliance

Electronic auditing should be used as a prerequisite to assist assurance professionals in evaluating management's adherence to applied accounting policies in light of this disparity in the accounting treatments of digital assets (Abdo, 2022: 478). Financial technology creates the infrastructure necessary for the accurate implementation of these policies, which eventually results in the issuance of uniform specialized accounting standards (Farras et al., 2025: 506).

V. The work's practical component and analysis of the findings

1. Job-specific and Demographic Features of the Sample

Table (1): Demographic and Profession Description of Study Sample

Item Condition N (Number) Percentage
Educational Qualification Diploma 42 32.56%
Bachelors 30 23.26%
Master's 42 32.56%
Doctorate 15 11.63%
Your area of expertise Accounts 84 64.62%
Management 38 29.23%
Economics 7 6.15%
Nature of Work Accountant 54 41.86%
Academic 49 37.98%
Internal Audit 20 15.50%
External Auditor 3 2.33%
Regulatory Agency 3 2.33%
Years of Experience Less than 5 years 76 58.91%
From 5 to 10 years 29 22.48%
From 10 to 15 years 11 8.53%
More than 15 years 13 10.08%
Table 4.

Analysis: Table (1) shows the study sample's diversity in terms of science and profession. The accounting specialty is very prevalent at 64.62%, with diploma and master's degrees accounting for 32.56% and 32.56%, respectively. Regarding the type of work, academics and accountants were also the most referenced (a total of >79%), giving the answers scientific and practical credibility. The majority of experience (58.91%) fell into the young category (less than 5 years), indicating that the sample was sufficiently capable of adopting and using the cutting-edge digital approaches under investigation.

2. Testing the Tool's Validity and Reliability

To evaluate the internal consistency in determining the validity of the questionnaire as a measurement tool, a Cronbach's Alpha test was combined with a Split-Half test:

Table (2): Reliability Coefficients (Cronbach's Alpha & Split-Half)

Axis Cronbach's Alpha Split-Half Spearman-Brown
First Axis: FinTech 0.890 0.817 0.899
Second Axis: E-Audit 0.901 0.850 0.919
Third Axis: Accounting Measurement 0.907 0.845 0.916
Table 5.

Analysis: Cronbach's Alpha values ranged from 0.890 to 0.907, and all predicted reliability coefficients were over the statistically accepted cut-off of 0.70. Split-Half and Spearman-Brown coefficient results, which supported the study instrument's stability—that is, its high degree of reliability and internal consistency—confirmed these.

3. Impact of homogeneity and response variability on item variability

Table (3): Variance Analysis of the Study Axes Items

Item First Axis Variance Second Axis Variance Third Axis Variance
1 0.585 0.726 0.636
2 0.652 0.632 0.676
3 0.669 0.625 0.562
4 0.753 0.566 0.715
5 0.872 0.478 0.665
6 0.591 0.757 0.817
7 0.516 0.722 0.699
8 0.754 0.670 0.656
9 0.706 0.643 0.581
10 0.491 0.587 0.405
Table 6.

Analysis: The variance values were often modest, as Table (3) illustrates. The tenth item on the third axis had the lowest dispersion value (0.405), indicating a high degree of consensus. The top values were found to be within acceptable bounds, finalizing the homogeneity of the sample responses.

4. Description of the Data and Correlation Matrix

Table (4): Descriptive Statistics and Correlation Matrix of the Axes

Axis Arithmetic Mean Standard Deviation Correlation (1) Correlation (2) Correlation (3)
(1) Financial Technology 3.936 0.576 1
(2) Electronic Auditing 4.050 0.581 0.838 1
(3) Accounting Measurement 4.030 0.591 0.811 0.797 1
Table 7.

Analysis: Despite having a positive slope, all axes scored higher than 3.9 on a scale of 5, indicating agreement. Almost all variables have a strong and significant positive relationship with one another, according to the correlation matrix. The strongest relationship is found between Financial Technology and Electronic Auditing (0.838), followed by Financial Technology and Accounting Measurement (0.811).

5. Testing Hypotheses (Multiple Linear Regression Analysis)

To determine how Financial Technology and Electronic Auditing (Independent Variable) affect Accounting Measurement Development (Dependent Variable), use the best suitable method:

Table (5): Multiple Linear Regression Analysis Results

Independent Variable Regression Coefficient (B) Standard Error (t) Value Significance Level (P)
(Constant) 0.466 0.207 2.244 0.026
Financial Technology 0.494 0.091 5.424 0.000
Electronic Auditing 0.398 0.090 4.416 0.000
Model Indicators R = 0.839 R² = 0.705 F = 150.37 Sig F = 0.000
Table 8.

VI. Outcomes

First. Findings from the Measurement Instrument's Validity and Reliability Tests

Two. Descriptive Findings

Third. Results of Correlation

Four. Results of Hypothesis Testing

Fifth. Overall Conclusion

The model's overall importance and predictive performance are indicated by its value of 150.37 and significance level of 0.000. Financial technology and electronic auditing can account for 70.5% of changes in accounting measurement developing digital assets, according to the coefficient of determination (R2 = 0.705). Compared to the immediate impact of electronic auditing (Beta = 0.398), the association of financial technology (Beta = 0.494) was comparatively higher. The central hypothesis of this study, which asserts that financial technology and electronic auditing have a major influence on the development of accounting measurement techniques, can be accepted based on the prior conception.

VII. Research Suggestions

The following recommendations could be made in light of the study's findings:

Suggested Contributions to Research

To bolster the aforementioned, a researcher suggests four research fields that would be an extension of this work and are probably composed of academic contributions:

  • The impact of electronic auditing and financial technology on new accounting measurement techniques for digital assets is the research question.
  • Does financial technology aid in the development of accounting measuring methods for digital assets?
  • I can't help but wonder if electronic auditing contributes to the development of accounting measuring methods for digital assets.
  • Digital asset measurement: Accounting and theoretical challenges.
  • looking at the identification of financial technology as a way to gauge the advancement of accounting techniques.
  • demonstrating how electronic auditing has improved the accuracy of accounting measurement for cryptocurrency and digital assets.
  • Data extraction for research and practice.
  • Electronic auditing (E-audit) and financial technology (FinTech) are independent factors.
  • The creation of measurement techniques to account for digital assets is a dependent variable.
  • Figure (1): Research Model
  • The new real-time auditing framework was created over a decentralized blockchain ledger, as demonstrated by Dai & Vasarhelyi (2017) It demonstrated that continuous auditing of financial transactions could be carried out in nearly real-time during the period the transaction occurs, rather than only at discrete intervals, marking at end-of-period audits.
  • According to Appelbaum et al. (2017), there is a need for more research on the application of big data and analytics in modern audit practices. To stay ahead of this shift, auditors should acquire new technical skills and knowledge.
  • Permissionless blockchain is better for independent external oversight operations, while permissioned blockchain is better for internal corporate auditing, according to Liu et al. (2019) The researchers used the comparative analytical method.
  • The paper by Fuller & Markelevich (2020) supported the idea that blockchain will revolutionize accounting and auditing and that educational and training programs need to be created to prepare professionals for the new digital environment.
  • The authors used a quantitative empirical approach in Liu, Zhang, and Zhang's 2021 paper, The findings show that increased price volatility reduces the mean comparability of financial statements, necessitating the detailed disclosure of the impact of this rumble in the financial notes.
  • The analytical theoretical study was observed in Beigman et al. (2021) The conclusion highlighted the significance of implementing a dynamic mechanism for periodically determining the chief market in light of their multiplicity in order to determine an accurate accounting measurement.
  • Zhao (2021) Specifically, cryptocurrencies support our global economy of digital public goods and lessen our reliance on centralized agents, necessitating changes to accounting procedures and financial control frameworks.
  • According to Lombardi et al. (2022), The systematic literature review confirmed that blockchain technology transforms the audit environment by enhancing transparency and enabling real-time financial transaction verification.
  • Huang, No, and Vasarhelyi (2022) also show that the probability of identifying deviations from the typical pattern is increased when data analytics and machine learning are able to test the entire population of transactions instead of just sampling them.
  • Luo & Yu (2022) The study called for an international harmonization of the accounting treatment of digital assets due to the notable discrepancies in classification, measurement, and disclosure between the two systems.
  • Hubbard (2023) :This study highlights the need to update international standards and found that the revaluation model of intangible assets is better for accounting treatment for cryptocurrency.
  • FASB (ASU 2023-08) :This standard-setting update mandated that, absent contractual limitations on the (substantial) ownership of digital assets, businesses measure crypto assets at fair value and report changes in net income.
  • Bibliometric Review (2024) The bibliometric analysis using VOSviewer and Biblioshiny also reveals a notable increase in the number of studies concerning this developing field, with a focus on three primary axes: digital taxation, financial reporting, and auditing.
  • combining accounting measuring techniques, electronic auditing, and financial technology into a single theoretical framework.
  • providing statistical observations that quantify the extent of this phenomena in a work environment that includes academics, auditors, accountants, and oversight staff.
  • incorporating the ASU 2023-08 and IFRS IC (2019) Agenda Decision's updated standard-setting reference base into the theoretical framework.
  • In order to address the possible shortcomings of its cost model and fair value model, the integrative mechanism of FinTech tools and electronic auditing is proposed in the context of the excessive volatility of digital assets.
  • Through Cronbach's Alpha and Split-Half tests, reliability testing revealed excellent reliability in some axes of perception (α > 90%), which validates assumptions about the outcomes based on scientific dependency.
  • A reasonably self-evident vision among the respondents proportionate to technology and auditing affect measurement is approved by the variance statistics, which demonstrate strong harmony and agreement in the sample members' viewpoints on the notion.
  • Overall trend: on every study axis, a high arithmetic mean (greater than 3.9 out of 5) was attained, indicating that experts are fully prepared to handle the shift to digital technology.
  • The "Electronic Auditing" axis had the highest performance research area in terms of agreement sample, followed by "Accounting Measurement for Digital Assets." This is in line with the necessity for professional settings to create instruments for measuring, monitoring, and managing digital technologies.
  • Financial technology and auditing activities had a strong positive link of more than 80%, according to the correlation matrix.
  • This implies that every development in FinTech tools, such as blockchain and artificial intelligence, automatically improves the auditors' ability to verify the accuracy of data.
  • Testing the Hypothesis: The development of accounting measurement is statistically significantly impacted by both financial technology and electronic auditing.
  • Explanatory Power: 70.5% of the differences in accounting quality were explained by the model, which is a very high ratio in the administrative sciences.
  • The development of the measuring process was determined to be most influenced by "Financial Technology" (Beta = 0.494). This value is higher than that of Electronic Auditing (Beta = 0.398), which directly contributes by offering precise and up-to-date data for digital assets.
  • International professional and standard-setting organizations must create a specialized accounting standard for digital assets and cryptocurrencies that establishes the foundation for recognition, measurement, and disclosure in a way that is acceptable for their technological and economic characteristics.
  • improving the use of FinTech tools in accounting measurement procedures for digital asset information, particularly revenue-producing tools and artificial intelligence technology, since data is obtained promptly, publicly, and verifiable.
  • Extension of Electronic audits Systems and ongoing financial (and monitoring) audits to address the dangers of manipulation and misrepresentation associated with digital assets.
  • Building the digital infrastructure of accounting and oversight organizations to enable the integration of contemporary FinTech solutions with accounting information systems.
  • establishment of professional training and certification courses in digital assets, blockchain technology, big data analytics, and electronic auditing for accountants and auditors.
  • In order to meet the demands of the digital economy, we urge academic institutions and research centers to include the subjects of digital accounting and financial technology in graduate programs and academic curriculum.
  • To increase the reliability of assessing highly volatile digital assets, one approach is to use more adaptable and contemporary measurement models that go beyond the conventional historical cost measurement.
  • In order to provide transparency and close the information asymmetry gap between entities and investors, regulatory authorities will be asked and required to develop regulatory and supervision frameworks for digital assets.
  • suggesting future studies that concentrate on the effects of IoT, smart contracts, and artificial intelligence in measuring, disclosing, and auditing the price of digital assets at the extraction level.
  • Increase the scope of applied comparative study between domestic and foreign settings to ascertain the extent of variations in digital asset accounting and the effects of market value on entities.
  • empirical research to determine how implementing ASU 2023-08 affects the quality and volatility of earnings in publicly traded cryptocurrency companies.
  • Hybrid measuring models powered by artificial intelligence that integrate risk-adjusted value and fair value.
  • Electronic auditing's cybersecurity and governance in permanent versus permissionless blockchain environments.
  • Difference-in-difference regulation analysis: How measurement and disclosure procedures are affected by virtual asset regulatory frameworks (UAE's VARA, EU's MiCA, US SEC).
  • The degree to which investors and consumers accept financial statements created using continuous measurement models as opposed to traditional methods is determined by behavioral studies.

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