Auditing Dissertation Topics for 2026-27 | 40+ PhD-Reviewed Ideas

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Non-Big Four audit firms were responsible for 40% of all UK public interest entity audits in 2024, nearly double their share from the start of the decade (FRC, Audit Market and Competition Update, December 2025). That kind of structural shift opens dissertation territory that generic AI-generated topic lists can't map, because they recycle the same broad categories without connecting them to what's actually changed. Premier Dissertations has built every topic around named sources, verified research gaps, and methods your supervisor can approve on first review. If you need something tailored to your exact specialism, request 3 free custom topics in 24 hours. Below you'll find 30+ auditing dissertation topics for 2026-27, sorted by category, methodology, and academic level.

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The UK audit market is shifting faster than most students realise. According to the FRC's December 2025 Audit Market and Competition Update, non-Big Four firms were responsible for 40% of all public interest entity audits in 2024, up from 22% at the start of the decade. That near-doubling opens genuine dissertation territory: what's driving challenger firms into the PIE space, and is audit quality keeping pace with market redistribution?

A 2026 study by Mugwira and colleagues in the Journal of Accounting Literature surveyed 166 experienced auditors and found that audit firms sit at a moderate level of technology maturity overall. But the distribution is uneven: Big Four firms are transitioning from moderate to advanced stages, while non-Big Four firms are only progressing from early to moderate. For students researching the non-Big Four expansion into PIE audits, this maturity gap raises a pointed question: are challenger firms winning market share with less mature technology infrastructure, and what does that mean for audit quality?

A 2026 systematic review by Abderrahman and Makarem in the Journal of Risk and Financial Management examined emerging technologies across external audit. Their headline finding is that while Big Data analytics and machine learning now have a reasonable empirical base, research on generative AI in auditing is almost non-existent. If you're looking for a topic where your dissertation genuinely fills a gap rather than repeating existing work, generative AI adoption in audit firms is one of the clearest openings in the field right now.

Blockchain's role in auditing is also maturing past theory. Aladeeb and Alaoui's 2026 hybrid bibliometric-systematic review in Cogent Business & Management mapped a full decade of blockchain research in accounting and auditing. They identified six principal themes and argued that blockchain enables a transition from centralised periodic auditing to distributed continuous assurance. But the empirical validation remains thin. Students with access to firms experimenting with blockchain-based audit trails have a real competitive advantage.

On the tax side, Anjarwi's 2026 study in the Journal of Tax Administration found that jurisdictions using AI and advanced analytics achieve measurably better audit precision for tax evasion detection, while developing economies face persistent infrastructure barriers. That cross-jurisdictional contrast is a ready-made comparative research design for any student interested in how technology reshapes regulatory enforcement.

ESG assurance demands are growing faster than audit firms can retool. With mandatory climate-related disclosures tightening under UK sustainability reporting frameworks, auditors are being asked to verify data they were never trained to assess. The gap between what regulators now require and what audit methodologies can actually deliver is where the most practically useful dissertations will sit in 2026-27.

This study investigates how audit professionals are actually using (or refusing to use) generative AI tools in engagement workflows, and whether AI-assisted analysis alters the quality of auditor judgement.

Gap: Abderrahman and Makarem's 2026 systematic review found almost no empirical research examining generative AI in external audit, despite rapid practitioner adoption.

Methodology: Semi-structured interviews with 15-20 audit professionals across Big Four and mid-tier firms, analysed using thematic analysis.

Data source: Primary data collected through purposive sampling of qualified auditors in London and regional offices.

Source: Abderrahman & Makarem, Journal of Risk and Financial Management, Vol. 19(3), 2026.

This study examines why challenger audit firms have nearly doubled their share of UK public interest entity audits and whether audit quality metrics differ between Big Four and non-Big Four PIE engagements.

Gap: The FRC's December 2025 data shows non-Big Four firms at 40% of PIE audits (up from 22%), but no academic study has yet examined the quality implications of this rapid redistribution.

Methodology: Quantitative analysis of audit quality indicators (restatements, going concern accuracy, inspection findings) across a matched sample of 50 Big Four and 50 non-Big Four PIE audits, 2020-2025.

Data source: FRC Audit Quality Review reports, company annual reports from the Companies House database, and Financial Reporting Lab data.

Source: FRC, Audit Market and Competition Update, December 2025.

This study explores why mid-tier UK audit firms have been slow to implement blockchain-based audit trail verification despite growing theoretical support for continuous assurance models.

Gap: Aladeeb and Alaoui's 2026 bibliometric review found the field still characterised by limited empirical validation and regulatory uncertainty around blockchain adoption.

Methodology: Multiple case study design covering 3-4 mid-tier firms, combining document analysis of technology investment plans with semi-structured interviews (10-12 partners and technology leads).

Data source: Primary interviews and internal technology strategy documents obtained through firm partnerships or professional network access.

Source: Aladeeb & Alaoui, Cogent Business & Management, 2026.

This study assesses the preparedness of UK audit firms to provide assurance over non-financial ESG data under evolving mandatory reporting requirements aligned with ISSB standards.

Gap: UK sustainability reporting requirements aligned with ISSB standards are now mandatory for large companies, but no established audit methodology exists for verifying non-financial ESG metrics like Scope 3 emissions or social impact indicators.

Methodology: Mixed-methods: survey of 80-100 audit professionals on ESG assurance competence, followed by 10 in-depth interviews exploring training gaps and methodological challenges.

Data source: Primary survey data distributed through ICAEW and ACCA member networks; interview participants recruited from firms with active ESG assurance practices.

Source: FRC guidance on sustainability assurance standards, 2025-2026.

This study compares the effectiveness of AI-enhanced tax audit techniques in the UK (an advanced jurisdiction) versus a developing economy with limited digital infrastructure.

Gap: Anjarwi's 2026 research found that technologically advanced jurisdictions achieve significant improvements in audit precision, while developing economies face persistent infrastructure constraints, but no direct paired comparison exists.

Methodology: Comparative case study using secondary data from tax authority audit outcomes in both jurisdictions, supplemented by 8-10 expert interviews with tax audit professionals.

Data source: HMRC published compliance data, World Bank governance indicators, and OECD tax administration statistics.

Source: Anjarwi, Journal of Tax Administration, 2026.

This study evaluates whether machine learning algorithms outperform traditional statistical sampling in identifying material misstatements during external audits.

Gap: Abderrahman and Makarem's 2026 review confirmed ML has the strongest empirical base of any emerging audit technology, yet no UK-focused study compares ML anomaly detection directly against ISA 530 sampling.

Methodology: Quasi-experimental design applying ML classification models (random forest, neural network) to a historical dataset of audited financial statements, benchmarked against outcomes from traditional sampling on the same dataset.

Data source: Financial statement data from FAME database; known misstatement cases from FRC enforcement actions.

Source: Abderrahman & Makarem, Journal of Risk and Financial Management, Vol. 19(3), 2026.

This study investigates how the permanent shift to remote and hybrid auditing since 2020 has affected the sufficiency and reliability of audit evidence in small and medium enterprise engagements.

Gap: Post-pandemic remote auditing is now standard practice, but its effect on evidence quality in smaller engagements (where physical verification historically mattered most) remains underexplored in 2025-2026 literature.

Methodology: Survey of 100+ auditors who conduct SME audits, combined with analysis of 30 anonymised engagement files comparing pre-2020 and post-2022 evidence documentation.

Data source: Primary survey data via ACCA/ICAEW networks; anonymised engagement file data through participating firm agreements.

Source: FRC Audit Quality Review thematic findings, 2025.

This study examines whether the FRC's requirement for Big Four firms to operationally separate their audit practices from consulting has measurably improved audit independence and reduced conflicts of interest.

Gap: The operational separation framework has been in place since 2024, but no academic study has yet assessed its effects on independence indicators or audit outcomes.

Methodology: Quantitative analysis of pre- and post-separation metrics (non-audit service fees as a percentage of audit fees, audit opinion modifications, FRC inspection outcomes) across all four firms.

Data source: Firm transparency reports filed with the FRC, annual reports of FTSE 350 audit clients, FRC inspection data.

Source: FRC operational separation requirements and 2025 monitoring reports.

This study compares the effectiveness of digital forensic tools against traditional forensic auditing techniques in detecting financial crime within UK corporate investigations.

Gap: The UK Economic Crime and Corporate Transparency Act 2023 expanded corporate criminal liability, increasing demand for forensic audit expertise, but comparative effectiveness studies remain scarce in 2025-2026.

Methodology: Mixed-methods: quantitative analysis of 40-50 Serious Fraud Office case outcomes categorised by investigation technique, plus 8-10 interviews with forensic audit practitioners.

Data source: SFO published case outcomes, Crown Prosecution Service data, primary interview data from forensic audit specialists.

Source: UK Economic Crime and Corporate Transparency Act 2023; SFO annual reports 2024-2025.

This study examines whether heightened workload during peak audit season reduces professional scepticism and, consequently, the likelihood of detecting material fraud indicators.

Gap: FRC audit quality inspections in 2025 continued to identify insufficient challenge of management representations as a recurring theme, yet the relationship between seasonal workload spikes and scepticism has not been isolated.

Methodology: Survey experiment: 120-150 audit seniors and managers complete fraud detection scenarios under simulated high-workload and low-workload conditions, analysed using logistic regression.

Data source: Primary experimental survey data collected through ICAEW or firm-based distribution; FRC inspection reports for contextual analysis.

Source: FRC Audit Quality Inspection reports, 2025.

This study examines how multiple emerging technologies (AI, blockchain, cloud platforms) interact when deployed together within a single audit engagement, and whether integration produces efficiency gains beyond individual tool adoption.

Gap: Abderrahman & Makarem (2026) found that existing research examines individual technologies in isolation; no study investigates how multiple technologies interact when deployed together within a single audit engagement.

Methodology: Embedded case study of 2-3 audit firms that have deployed at least two technologies concurrently. Data collected through process observation, system logs, and 12-15 interviews with engagement teams.

Data source: Primary data from participating firms; supplementary data from firm technology investment disclosures in transparency reports.

Source: Abderrahman & Makarem, Journal of Risk and Financial Management, Vol. 19(3), 2026.

This study empirically tests blockchain-enabled continuous assurance in a live audit engagement, measuring real-time error detection rates against periodic audit findings from prior-year traditional engagements.

Gap: Aladeeb & Alaoui (2026) argued that blockchain enables a transition from centralised periodic processes to distributed continuous assurance, but noted that empirical validation of this transition is still missing.

Methodology: Action research or design science approach: collaborate with one firm piloting blockchain verification to track assurance outcomes over a 6-month engagement cycle, measuring real-time error detection rates against periodic audit findings.

Data source: Transactional data from the participating firm's blockchain pilot; comparative audit findings from prior-year traditional engagements.

Source: Aladeeb & Alaoui, Cogent Business & Management, 2026.

This study investigates which specific infrastructure barriers (IT infrastructure, data quality, regulatory capacity, workforce training) most strongly predict AI adoption success in tax audit settings across jurisdictions.

Gap: Anjarwi (2026) found that developing economies face persistent infrastructure constraints that prevent effective deployment of AI-driven audit tools, but did not investigate which specific infrastructure barriers matter most.

Methodology: Comparative survey of 80-100 tax auditors across two developing economies and the UK, using structural equation modelling to identify which infrastructure dimensions most strongly predict AI adoption success.

Data source: Primary survey data; ITU digital infrastructure indices; OECD Tax Administration comparative data.

Source: Anjarwi, Journal of Tax Administration, 2026.

This study replicates and extends Aladeeb and Alaoui's bibliometric dataset with a focused coding of methodological approaches, identifying the five most under-researched empirical questions in blockchain audit research.

Gap: Aladeeb & Alaoui (2026) found that dominant methodologies in blockchain audit research are conceptual and theoretical, with a significant shortage of empirical and quantitative work.

Methodology: Systematic literature review replicating and extending Aladeeb and Alaoui's dataset with a focused coding of methodological approaches, followed by a gap-mapping framework that identifies the five most under-researched empirical questions.

Data source: Scopus and Web of Science databases; the original corpus of papers identified in the Aladeeb & Alaoui review, extended through forward citation tracking.

Source: Aladeeb & Alaoui, Cogent Business & Management, 2026.

This study examines whether generative AI tools mitigate or reinforce the cognitive biases (anchoring, confirmation bias) that already affect auditor judgement in tasks such as going concern assessment and fraud risk evaluation.

Gap: Abderrahman & Makarem (2026) found near-zero empirical research on generative AI in auditing, specifically on how AI assistance interacts with known cognitive biases in audit judgement.

Methodology: Experimental design: 80-100 audit trainees and seniors complete judgement tasks (going concern assessment, fraud risk evaluation) with and without generative AI assistance. Bias indicators measured through validated scales and scenario-based assessments.

Data source: Primary experimental data collected through participating firms or university auditing programmes; published cognitive bias measurement instruments.

Source: Abderrahman & Makarem, Journal of Risk and Financial Management, Vol. 19(3), 2026.

This study investigates the documented technology maturity gap between Big Four and non-Big Four firms and its consequences for audit quality outcomes in PIE engagements where challenger firms are rapidly gaining market share.

Gap: Mugwira et al. (2026) found that Big Four firms are transitioning from moderate to advanced technology maturity while non-Big Four firms remain at early-to-moderate stages, but the consequences for audit quality outcomes in non-Big Four PIE engagements have not been examined.

Methodology: Mixed-methods: quantitative comparison of FRC audit quality inspection findings for Big Four versus non-Big Four PIE engagements (2022-2025), paired with 12-15 interviews with non-Big Four technology leads exploring investment constraints and adoption barriers.

Data source: FRC Audit Quality Review published reports; firm transparency reports; primary interview data from non-Big Four firms active in the PIE market.

Source: Mugwira, Fotoh, Lorentzon & Almasri, Journal of Accounting Literature, Vol. 48(5), 2026; FRC December 2025 data.

This study examines how the expanded corporate criminal liability under the ECCT Act 2023 has changed what auditors report, and whether audit firms have updated their fraud risk assessment procedures in response.

Gap: The Act introduced a "failure to prevent fraud" offence for large organisations in 2024-2025, but no academic study has assessed how auditors have adjusted their engagement-level fraud risk assessments since implementation.

Methodology: Mixed-methods: content analysis of 60 audit reports from FTSE 350 firms pre-Act (2022-2023) and post-Act (2024-2025), coding for changes in fraud-related disclosures, combined with 10-12 interviews with audit partners on procedural changes.

Data source: Published annual reports and auditor reports from Companies House; primary interview data from Big Four and mid-tier firms.

Source: UK Economic Crime and Corporate Transparency Act 2023, effective provisions 2024-2025.

This study assesses whether mandatory rotation of audit firms for public interest entities has stimulated innovation in audit approaches or primarily affected fee competition and tendering costs.

Gap: The FRC's December 2025 data shows non-Big Four firms now hold 40% of PIE audits, suggesting rotation is reshaping the market, but no study has isolated whether rotation drives innovation (new methodologies, technology investment) or simply redistributes fees.

Methodology: Quantitative panel data analysis of audit fee trends, technology disclosure statements, and audit approach changes across 80-100 PIE audit transitions occurring between 2020 and 2025.

Data source: Audit fee data from company annual reports (Companies House); firm transparency reports filed with the FRC; Audit Analytics UK database.

Source: FRC, Audit Market and Competition Update, December 2025.

This study investigates the causes of the persistent backlog in English local authority audits and evaluates whether proposed reforms can restore timely public sector assurance.

Gap: By 2025, hundreds of local authority audit opinions in England remained outstanding, representing a systemic failure in public sector assurance. Academic analysis of root causes (fee levels, auditor capacity, accounting complexity) is minimal.

Methodology: Mixed-methods: quantitative mapping of backlog severity across all English local authorities using published audit completion data, combined with 10-15 interviews with local audit partners, chief finance officers, and PSAA representatives.

Data source: Public Sector Audit Appointments (PSAA) published data on audit completion rates; NAO reports on local audit; DLUHC consultation documents on local audit reform; primary interview data.

Source: NAO and DLUHC reports on local audit delays, 2025; PSAA audit completion statistics.

Q: "What can be an interesting thesis (Msc) topic in audit?" — ResearchGate

The most interesting MSc audit topics right now sit at the intersection of regulatory change and technological disruption. If your programme expects primary research (and most UK master's programmes do), you want a topic where you can access real data within 3-4 months.

Three areas stand out in 2026. First, generative AI in audit firms. The 2026 Abderrahman and Makarem systematic review found almost no empirical work on this despite rapid practitioner uptake. Even a small-scale interview study with 12-15 auditors about how they're using (or avoiding) AI tools would fill a documented gap. Second, ESG assurance readiness. With ISSB-aligned disclosures becoming mandatory, you could survey audit professionals about their confidence in verifying non-financial data. Third, the non-Big Four expansion into PIE audits. The FRC's data shows challenger firms nearly doubled their market share in four years, and nobody has studied the quality implications yet.

What makes a topic "interesting" to your supervisor isn't novelty for its own sake. It's a clear gap backed by a credible source, a feasible methodology, and a contribution that matters to someone beyond your university. Pick one of these three areas, narrow it to a specific research question, and you'll have something worth defending.

Q: "Hello I am a master's student in auditing. What is the hot topic for ..." — ResearchGate

The hottest topics in auditing for 2026-27 cluster around two forces: technology reshaping how audits get done, and regulation expanding what audits must cover.

On the technology side, generative AI is the clear frontrunner. Firms are deploying large language models for everything from workpaper review to risk memo drafting, yet almost no academic research exists on how these tools affect auditor judgement. If you can get access to 15-20 professionals willing to be interviewed, you have a publishable study. Blockchain-based continuous assurance is the second major technology angle. The theoretical case is well-established (Aladeeb and Alaoui mapped a full decade of it in their 2026 bibliometric review), but empirical testing in live audit environments is still missing.

On the regulation side, ESG assurance is expanding rapidly. UK firms are being asked to verify climate and sustainability data under frameworks they didn't train for. The gap between regulatory expectations and audit capability is wide, and it's measurable. The other regulatory hot spot is the Economic Crime and Corporate Transparency Act 2023, which introduced a "failure to prevent fraud" offence. No study has yet examined how auditors have adjusted their reporting in response. Either of these gives you a timely, well-sourced dissertation.

Q: "What would be a recent audit topic to approach for my ..." — ResearchGate

"Recent" in academic terms means your topic is anchored to something that changed in the last 12-18 months. Not a topic that was current in 2020 and still technically applies.

Here's a concrete test: can you point to a specific 2025 or 2026 source (an FRC report, a journal article, a piece of legislation) that creates the gap your dissertation fills? If yes, it's recent. If you're relying on a 2019 paper's "future research" section, it's not. The FRC's December 2025 market update, the Abderrahman and Makarem 2026 systematic review, and the Anjarwi 2026 study on AI-driven tax audits all provide this kind of anchor. Pick the one that aligns with your access to data and your supervisor's expertise, then build your research question around the specific gap that source identifies.

For example, Abderrahman and Makarem explicitly note that research on generative AI in auditing is almost non-existent. That's not a vague "more research is needed" statement. It's a documented absence. Your dissertation can be the first (or among the first) to fill it.

Q: "I have been doing research into auditing. A very intresting subject area, what with Auditor Independence and Corporate goverance being controversial etc. I have chosen to do my dissertation in this area, can anyone give me a guiding hand as to what would be a good current issue to debate about." — accountancy.com.pk

Auditor independence and corporate governance are excellent territory, but you need to move past the general "is independence important?" framing that dozens of dissertations have already covered. The current issues worth debating are structural, not philosophical.

Start with the FRC's operational separation mandate. Big Four firms have been required to ring-fence their audit practices from consulting, and the question now is whether this structural intervention has actually improved independence or simply added compliance cost. You can measure this: compare non-audit service fees as a percentage of audit fees before and after separation, and pair that with FRC inspection outcomes. That gives you a quantitative backbone with a genuinely debatable conclusion.

Alternatively, look at the non-Big Four surge. If challenger firms now hold 40% of PIE audits (FRC, December 2025), is that competition improving independence because clients have more choice, or is it creating new risks because smaller firms may face greater economic dependence on large clients? That's a debate with real evidence on both sides.

The key is to anchor your argument in a 2025-2026 structural change, not a timeless theoretical question. Your examiner has read plenty of dissertations about independence in the abstract. Give them one that engages with what's actually happening in the market right now.

Q: "I'm in my final year, and I'm basically conducting a questionnaire for my dissertation; on the topic of 'the value of forensic accounting and auditing in preventing financial crimes'." — The Student Room

You've got a workable topic, but "the value of forensic accounting and auditing in preventing financial crimes" is very broad. Your questionnaire will be stronger if you narrow it.

One concrete way: focus specifically on the UK context post-Economic Crime and Corporate Transparency Act 2023. The Act introduced a "failure to prevent fraud" offence for large companies, which changes what's at stake for both forensic accountants and auditors. Your questionnaire could target two groups: forensic accountants who investigate corporate fraud, and external auditors who assess fraud risk during statutory audits. Ask them how the new legislation has changed their workload, their methods, and their perception of whether forensic techniques are now more or less valued by clients.

For your sampling, aim for 60-80 respondents minimum if you want to run any meaningful statistical tests. Distribute through ICAEW, ACCA, or the Institute of Chartered Forensic Accountants networks. Use a Likert-scale structure for the attitudinal questions, but include 2-3 open-ended questions to capture nuance your scales will miss. And be explicit in your methodology chapter about why you chose a questionnaire over interviews. Supervisors want to see that choice justified, not just stated.

Q: "Hi guys, I'm currently in my final year of my degree and I'm doing my dissertation on auditor independence. I'm looking for undergraduate students that have studied or are currently studying auditing to take part in my study." — The Student Room

This tells me you're collecting primary data on perceptions of auditor independence, which is a solid approach. But surveying other undergraduates introduces a limitation you'll need to address head-on in your methodology: students can tell you what they've learned about independence in their courses, but they can't tell you how independence works in practice because they haven't experienced it.

If you're committed to a student sample (which is fine for an undergraduate dissertation), frame your research question around perception and education rather than practice. For example: "Do UK auditing students perceive the FRC's operational separation of Big Four firms as an effective independence safeguard?" That way your sample matches your question. You could also add a small comparator group of 8-10 qualified auditors through LinkedIn or ICAEW student networks. Even a few practitioner responses would strengthen your discussion chapter significantly.

For your questionnaire design, use established independence constructs from the academic literature (DeAngelo's economic bonding theory, the familiarity threat framework from ISA 260). Ground your questions in those frameworks and your supervisor will see theoretical rigour, not just a list of opinion questions.

Q: "What can be an interesting thesis (Msc) topic in audit?" — ResearchGate (second instance)

If you're drawn to quantitative work, consider the relationship between audit firm rotation and audit quality in UK PIE engagements. The data is publicly available through Companies House annual reports and FRC inspection findings, so you don't need to negotiate firm access. You could build a panel dataset of 80-100 rotation events between 2020 and 2025 and test whether quality indicators (restatements, going concern accuracy, key audit matter specificity) change in the first year post-rotation. That's a clean, defensible quantitative design.

For qualitative students, the junior auditor experience is underexplored and surprisingly timely. Audit automation and AI are changing what junior auditors actually do day-to-day, and the effect on skill development hasn't been studied. Twelve to fifteen interviews with trainees at Big Four and mid-tier firms would give you rich data. Supervisors tend to like this kind of topic because it connects to workforce and professional development debates that the profession itself cares about.

If you want something more niche, cryptocurrency auditing is still genuinely novel. Auditing digital asset holdings raises verification challenges that existing ISA standards don't fully address. A case study of how 2-3 firms have adapted their audit procedures for clients holding significant crypto assets would be original and topical.

Q: "Hello I am a master's student in auditing. What is the hot topic for ..." — ResearchGate (second instance)

Since I addressed technology and regulation angles in my first response to this question, let me point you toward two additional hot areas that are often overlooked.

Public sector auditing in the UK is in genuine crisis. Hundreds of local authority audit opinions are outstanding, and the National Audit Office has repeatedly flagged the backlog as a systemic failure. If your programme permits a public sector focus, this is one of the most practically important topics available. You could investigate root causes (fee inadequacy, auditor capacity, accounting standard complexity) through a mixed-methods design combining published PSAA completion data with interviews of local audit practitioners.

The second area is behavioural auditing. The AI Overview for auditing dissertation searches specifically highlights "exploring workplace habits and communication patterns to predict and intercept internal corporate fraud." This connects to organisational psychology as much as accounting, which means your literature review can draw on a richer theoretical base. If your university has a psychology department willing to co-supervise (or even just advise on research instruments), you'll produce something distinctive.

Q: "What would be a recent audit topic to approach for my ..." — ResearchGate (second instance)

Building on the first answer's guidance about anchoring your topic to a specific 2025-2026 source, let me give you a different concrete example here.

The Aladeeb and Alaoui 2026 bibliometric review mapped six principal themes across a decade of blockchain research in auditing. One of their key arguments is that blockchain enables a move from periodic to continuous assurance. But they also noted that empirical validation is thin. If you find blockchain interesting, your dissertation doesn't need to build a blockchain system. It could instead be a qualitative study examining why UK firms haven't adopted blockchain-based audit trails despite the theoretical support. Interview 10-12 technology leads at audit firms and you'll produce primary data that directly addresses a gap two researchers documented this year.

Another very recent angle: Anjarwi's 2026 study in the Journal of Tax Administration showed that AI-driven tax auditing works well in technologically advanced jurisdictions but poorly where infrastructure is lacking. If you have connections to tax authorities or audit firms operating across multiple countries, a comparative case study would extend Anjarwi's findings with new primary evidence.

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