Potential Risk and Challenges on Implementation of Blockchain Technology in Accounting
Executive Summary & Empirical Findings
Blockchain technology is regarded as another pioneering technology after cloud computing, internet of things and big data. Blockchain’s unique characteristics which are immutability, transparency, and reliability were found to be useful not only in cryptocurrencies but also in accounting. However, blockchain in accounting is still in its early stages and has many challenges and potential risks to make it more reliable. In order to explore the challenges and potential risks of implementation of blockchain technology in the field of accounting, an opinion survey of professionals has been made in this study.
Major Findings: Major challenge of concern by respondents is lack of skilled manpower followed by low data performance. Transformational risk (moving the existing framework to the blockchain based methodology) is the major potential risk identified by the respondents followed by system risk. Results also reveal that opinion of the respondents of different profession-groups are not significantly different for various statements. Factor analysis was also applied to 14 items of risk and extracts 5 principal risk dimensions: operational risk, system related risk, legal risk, security risk and processing risk.
1. Introduction: The Promise & Disruptive Mechanics of Blockchain
Technological advancements and their adoption in the accounting profession have been more effective to date than in other professions. Blockchain is an emerging technology introduced in 2008. Blockchain technology (BT) is regarded as another pioneering technology after cloud computing, internet of things and big data, which has garnered concern from financial institutions, governments and technology enterprises (Yang, Li, Wu & Zhao, 2017). It is regarded as one of the most disruptive technologies since the internet (Yermack, 2017) or even “a game changer” (Andersen, 2016).
It was first used as a peer-to-peer ledger for registering the transactions of Bitcoin cryptocurrency. As it is being used in a decentralised manner, it removes the need for “trusted third parties” (Cachin, 2016). None of the participating entities can change an approved and registered activity without involving the other participating entities. Its content and all transactions are secure and cannot be altered after being added. Since no one can individually alter any of the recorded transactions, it is nearly impossible to fake records or repudiates an agreement. This feature is well suited for conducting different business activities like accounting.
Blockchain technology may represent the next step for accounting. Blockchain is very useful for accounting as the technology is based on transparency, decentralisation and immutability (Tapscott & Tapscott, 2017). Blockchain technology has the potential to impact all recordkeeping processes, including the way transactions are initiated, processed, authorised, recorded and reported. Blockchain technology may provide new opportunities to reduce transaction costs dramatically and decrease transaction settlement time. It also brings changes in business models and business processes that may impact back-office activities such as financial reporting, tax preparation and could bring new challenges and opportunities to the audit and assurance profession. The function of accounting has been enhanced by blockchain (Ducas & Wilner 2017) as this technology helps to eliminate reconciliations and ensures transaction history.
The importance of blockchain technology in business and accounting is increasing day by day, as blockchain is a highly secure and calculable system which provides peer-to-peer transactions without third party involvement. Besides, once the information of the transaction is recorded, the system stores multiple copies of it, so there is a rare probability to change or delete it from the system; which means the blockchain ledger would remain unaffected by unexpected events (Coyne and McMickle, 2017). Furthermore, the quality of data is exhaustive, reliable and widely available (Kiviat, 2015). Moreover, important advantages of blockchain technology are immutability, decentralisation, transparency visibility, traceability and verification.
These are considerable advantages that cannot be ignored, but blockchain still has many challenges and the potential risk to making it more reliable. It is a complex and new technology as non-technical persons or people from earlier generations are not familiar with it. Size and storage are also challenges for accounting with blockchain. Blockchain provides remarkable savings in transaction costs and time, but the high initial capital cost could be the limitation (Golosova & Romanovs, 2018). On the other hand, the most important challenges of BT (blockchain technology) are related to scalability, energy consumption, latency and low data performance (Dai and Vasarhelyi, 2017). Once the information is coded in BT, it is accessible to all of the network participants. Therefore, it could harm users’ privacy (Tan and Low, 2019) but also becomes attractive to hackers (Moll and Yigitbasioglu, 2019). That is, only adding new blocks of data into a blockchain does not guarantee that the transaction actually took place in real life (Schmitz and Leoni, 2019). Another challenge for BT is the auditing, accounting and corporate reporting regulatory framework, which is extremely strict. This technology also might expose firms to risks that they have not encountered before like transformational risk (moving the existing framework to the blockchain based methodology), cyber security risk, legal risk, value transfer risk, privacy risk and policy and regulatory risk. This new business model also exposes the interacting parties to new risks which were previously managed by central intermediaries.
2. Literature Review, Research Gap, Questions & Hypotheses
Review of Previous Research Literature:
- Zheng et al. (2021): Comprehensive overview highlighting scalability constraints, privacy leakage, and selfish mining. As transaction volume surges, servers become bulky; public key visibility fails to guarantee transactional privacy and exposes networks to colluding selfish miners.
- Zhang et al. (2021): Feasibility of combining blockchain with AI, identifying challenges across scalability, security, privacy, and data collaboration between on-chain and off-chain storage.
- Tiron-Tudor et al. (2021): SWOT analysis for accounting/auditing firms implementing BT. Highlighted weaknesses: scalability, complexity, low performance, large energy consumption, cyber vulnerability, absence of intermediaries in credential loss, lack of standards, and corporate governance gaps.
- Atanasovski, Trpeska & Lazarevska (2020): Assessed disruptive impact on accounting information systems; identified scalability, interoperability, confidentiality, and security hurdles.
- Todorova (2020): Emphasized regulatory uncertainties, smart contract enforceability, territoriality, liability, and the urgent need for globally approved standards covering terminology, privacy, and security.
- Weered (2019): Information risk management; demonstrated that internal IT control environments are no longer sufficient and organizations must oversee the entire blockchain network ecosystem.
- Bansal, Batra, & Jain (2018): Explored blockchain as a new platform reshaping business transactions and transforming accounting mechanisms.
- Yu, Lin and Tang (2018): Investigated impacts on independent auditors and accountants; noted constraints due to data processing capacity, confidentiality, and regulatory hurdles.
- Iuon-Chang & Tzu-Chun (2017): Investigated components of blockchain advancements for robust administration and addressing inventive security issues.
Research Gap & Questions
No previous comprehensive survey explored stakeholder opinions on both challenges and potential risks of blockchain accounting.
RQ1: What are the challenges that emerged on the implementation of blockchain technology in accounting?
RQ2: What are the potential risks related to the implementation of blockchain technology in accounting?
Formulated Hypotheses
H01: There is no significant difference among the opinions of various professionals regarding challenges on implementation of blockchain technology in accounting.
H02: There is no significant difference among the opinions of various professionals about potential risk on implementation of blockchain technology in accounting.
3. Research Methodology, Statistical Tests & Sample Demographics
Sampling & Instrument: Data was collected via judgmental sampling using a structured Google Forms questionnaire circulated nationwide across e-mail, WhatsApp, Facebook, LinkedIn, Instagram, and WhatsApp Status Stories. A total of 56 responses were received from CA/CS/ICWA practitioners, academicians, and IT experts. The questionnaire used a 5-point Likert scale (5 = Strongly Agree to 1 = Strongly Disagree) evaluating 8 challenges and 14 potential risks.
• Cronbach’s Alpha: Demonstrated high internal consistency: 0.770 for the 8 challenge statements and 0.850 for the 14 risk statements.
• Kolmogorov-Smirnov (K-S) Normality Test: Yielded significant values across all items (p < 0.05), rejecting data normality and confirming the methodological necessity of non-parametric tests (Kruskal-Wallis H Test).
Table 1: Respondents Demographic Profile (N = 56)
| (A) Gender Wise | (B) Profession Wise | (C) Age Wise | (D) Experience Wise | |||||||
|---|---|---|---|---|---|---|---|---|---|---|
| Male | Female | CA/CS/ICWA | Academicians | IT Experts | <25 years | 25–40 years | >40 years | <5 years | 5–10 years | >10 years |
| 25 (44.6%) | 31 (55.4%) | 21 (37.5%) | 12 (21.4%) | 23 (41.1%) | 8 (19.6%) | 30 (53.6%) | 18 (26.8%) | 18 (32.1%) | 29 (51.8%) | 9 (16.1%) |
4. Empirical Analysis of Challenges (Tables 2 & 3)
Table 2: Descriptive Statistics of Opinion Regarding Challenges
| Challenges | Mean Score | Coeff. of Variation (C.V.) | Rank |
|---|---|---|---|
| Lack of skilled manpower | 3.87 | 30.39% | I |
| Low data performance | 3.80 | 32.29% | II |
| Lack of government regulations | 3.71 | 31.56% | III |
| Lack of standardisation | 3.54 | 37.32% | IV |
| High initial capital cost | 3.50 | 35.31% | V |
| High energy consumption | 3.43 | 39.65% | VI |
| Still an underdeveloped technology | 3.21 | 41.46% | VII |
| Data privacy and security | 2.57 | 49.69% | VIII |
Table 3: Hypothesis Testing of Challenges (Kruskal-Wallis H Test Across Professions)
| Challenges | Chi-Square | P Value | Hypothesis Decision |
|---|---|---|---|
| High initial capital cost | .695 | .706 | Accepted |
| Lack of skilled manpower | .880 | .644 | Accepted |
| Lack of Government regulations | 4.413 | .110 | Accepted |
| Still an Underdeveloped technology | .402 | .818 | Accepted |
| Lack of Standardisation | .923 | .630 | Accepted |
| High energy consumption | 6.851 | .033* | Rejected |
| Data privacy and security | 3.703 | .157 | Accepted |
| Lack of Awareness | 6.487 | .039* | Rejected |
*Significant at 5% level. Results show that profession groups differ significantly only on 2 of 8 statements (“High energy consumption” and “Lack of Awareness”). Thus, professional discipline does not broadly bias perceptions of technological challenges.
5. Potential Risk Ranking (Table 4)
Blockchain in accounting transforms business models from human-based trust to algorithm-based trust. Respondents evaluated 14 distinct risk items:
| Potential Risk Item | Mean Score | C.V. (%) | Rank |
|---|---|---|---|
| Transformational risk (moving the existing framework to the blockchain based methodology) | 3.86 | 29.40% | I |
| System risk (continuously updating the system) | 3.73 | 28.23% | II |
| Legal risk (laws vary from country to country) | 3.57 | 36.55% | III |
| Volatility risk (related to crypto currency) | 3.55 | 35.18% | IV |
| Key management risk (in case of accidental loss or private key theft) | 3.43 | 34.66% | V |
| Divergence risk (inconsistency of transactions) | 3.34 | 35.78% | VI |
| Operational and IT risk (lower transaction processing rate during congestion) | 3.34 | 35.78% | VII |
| Policy & regulatory risk (lack of governance) | 3.29 | 38.75% | VIII |
| Privacy risk (if using public blockchain) | 3.09 | 40.13% | IX |
| Smart contract risk (error in creation and operation of smart contracts) | 2.96 | 39.70% | X |
| Value transfer risk (due to the absence of intermediary) | 2.87 | 43.10% | XI |
| Authentication risk (related to public and private key combination) | 2.86 | 42.78% | XII |
| Standard risk (of doing business) | 2.82 | 43.87% | XIII |
| Information security risk | 2.73 | 45.42% | XIV |
6. Exploratory Factor Analysis: KMO, Bartlett’s & Rotated Matrix
Table 5: KMO and Bartlett’s Test of Sphericity
Principal Component Analysis using Varimax rotation extracted 5 factors with eigenvalues > 1, explaining a robust 72.69% cumulative variance.
Table 6: Factor and Factor Loading (Rotated Component Matrix)
| Risk Items | F1: Operational | F2: System | F3: Legal | F4: Security | F5: Processing |
|---|---|---|---|---|---|
| Divergence risk (inconsistency of transactions) | .797 | – | – | – | – |
| Volatility risk (related to crypto currency) | .796 | – | – | – | – |
| Smart contract risk (error in creation and operation) | .738 | – | – | – | – |
| Value transfer risk (due to absence of intermediary) | .700 | – | – | – | – |
| Transformational risk (moving to blockchain methodology) | – | .868 | – | – | – |
| System risk (continuously updating the system) | – | .678 | – | – | – |
| Standard risk (of doing business) | – | .609 | – | – | – |
| Legal risk (laws vary from country to country) | – | – | .854 | – | – |
| Policy & regulatory risk (lack of governance) | – | – | .821 | – | – |
| Information security risk | – | – | – | .832 | – |
| Privacy risk (if using public blockchain) | – | – | – | .629 | – |
| Operational and IT risk (lower processing rate) | – | – | – | – | .872 |
| Key management risk (accidental loss or private key theft) | – | – | – | – | .719 |
Aggregates Divergence risk, Volatility risk, Smart contract risk, and Value transfer risk. Consistency of transactions and monetary measurement are inherent accounting pillars; without standardized stabilization across these risks, successful blockchain accounting remains untenable.
Encompasses Transformational risk, System updating risk, and Standard business risk. Continuous system upgrading is paramount but significantly escalates operational costs for adopting enterprises.
Captures cross-border legal variance and policy/governance absence. Example: In India, RBI banned cryptocurrency transactions but the Supreme Court subsequently set aside the ban, creating regulatory volatility.
Covers information security and public ledger privacy risks. Shows the highest C.V. (45.42%), indicating substantial volatility and diversity of opinion regarding public key encryption and consensus security.
Combines network congestion latency and private key management theft. Every transaction consumes significant processing time and heavy electricity, making computational throughput a primary operational concern.
7. Hypothesis Testing of Risks (Table 7: Kruskal-Wallis H Test)
Testing H02 across CA/CS/ICWA, Academicians, and IT experts:
| Potential Risks | Chi-Square | P Value | Decision |
|---|---|---|---|
| Key management risk (in case of accidental loss or private key theft) | .984 | .611 | Accepted |
| Operational and IT risk (lower transaction processing rate during congestion) | 1.737 | .419 | Accepted |
| Transformational risk (moving the existing framework to blockchain) | .390 | .823 | Accepted |
| System risk (continuously updating the system) | .903 | .637 | Accepted |
| Information security risk | 3.346 | .188 | Accepted |
| Standard Risk (of doing business) | 3.221 | .200 | Accepted |
| Smart contract risk (error in creation and operation of smart contracts) | 3.806 | .149 | Accepted |
| Value transfer risk (due to absence of intermediary) | 2.003 | .367 | Accepted |
| Privacy risk (if using public blockchain) | .503 | .778 | Accepted |
| Policy & regulatory risk (lack of governance) | 9.263 | .010* | Rejected |
| Divergence risk (inconsistency of transactions) | 1.331 | .514 | Accepted |
| Legal Risk (Laws vary from country to country) | 6.190 | .045* | Rejected |
| Volatility Risk (related to cryptocurrency) | .975 | .614 | Accepted |
| Authentication risk (related to public/private key combination) | 1.923 | .382 | Accepted |
*Significant at 5% level. Table 7 reveals that professional affiliations cause significant divergence on only 2 out of 14 risk variables: Policy & regulatory risk (p = .010) and Legal risk (p = .045). For the remaining 12 risk variables, consensus is uniform across professions.
8. Conclusion & Future Research Agenda
Blockchain guarantees trust, assures immutability, transparency, decentralisation, visibility, traceability and verification, and supports disintermediation in addition to providing extra security for transactions executed over the internet. These are considerable advantages that cannot be ignored, but the application of blockchain to accounting is still in its early stages.
The study proves that lack of skilled manpower, low data performance, regulatory voids, and lack of standardisation constitute the prime barriers. Overcoming these barriers requires establishing a comprehensive risk management strategy, corporate governance protocols, and internal controls framework.
Just as the internet evolved through rapid continuous upgradation, blockchain technology will mature, solving scalability bottlenecks and drastically reducing transactional overhead. Future work will focus on operationalizing standardized governance and internal control mechanisms to make blockchain-based triple-entry accounting a corporate reality. ■■■