40 Accounting and Finance Dissertation Topics for UK Students, Each With a Dataset (2026)

Forty accounting and finance dissertation topics for UK undergraduate and MSc students, grouped by sub-field, each with a one-line research question and the named dataset that answers it — Companies House, FAME/Orbis, the Financial Reporting Council, HMRC, ONS, the Charity Commission and FTSE index data. Use the three-test method at the end to check any topic is genuinely researchable before you commit to it.

Accounting dissertations sit in an unusually good position for UK data access: unlike many social-science topics, a large share of the raw material — filed accounts, audit reports, governance statements — is a matter of public record at Companies House, free of charge, before you even reach your university library’s paid databases. The forty topics below deliberately lean on that access, grouped into eight sub-fields so you can see where the open ground and the well-trodden ground both sit. For the wider catalogue of free UK datasets by subject beyond accounting specifically, see where to find UK data for your dissertation.

Narrowing a list of accounting dissertation topics down to one researchable question
Eight sub-fields, each with five worked topic-and-dataset pairings.

Financial reporting and disclosure

  1. Has mandatory climate-related financial disclosure (TCFD-aligned) changed the length and specificity of UK-listed companies’ annual reports? Dataset: Companies House filings + FRC’s corporate reporting review outputs.
  2. Do UK SMEs preparing accounts under FRS 102 disclose materially different information than those choosing the micro-entity regime? Dataset: Companies House filing history, comparing filing type by company size band.
  3. How has the length of the strategic report section of FTSE 250 annual reports changed over the last five years? Dataset: Companies House iXBRL filings for a sampled FTSE 250 cohort.
  4. Does earnings management (measured by discretionary accruals) increase in the year before a UK firm changes auditor? Dataset: FAME/Orbis financial statement panel data.
  5. Is there a measurable “Big Four discount or premium” in audit fees disclosed by UK-listed companies? Dataset: Companies House filings’ audit fee disclosures, or FAME/Orbis if your library holds it.

Audit and assurance

  1. What proportion of FRC Audit Quality Review inspections since a given year identified significant findings, and does this vary by audit firm tier? Dataset: FRC’s published Audit Quality Inspection reports.
  2. Has the introduction of Key Audit Matters (KAMs) reporting changed audit report length in the UK? Dataset: Companies House filings, comparing audit report sections pre/post the KAM requirement.
  3. Do FTSE 350 companies that rotate auditor show a measurable change in audit fee the following year? Dataset: FAME/Orbis or hand-collected Companies House audit fee notes.
  4. What sanctions has the FRC issued against audit firms and individual auditors, and what patterns exist in the breaches identified? Dataset: FRC’s published enforcement cases and their sanction outcomes.
  5. How does audit committee composition (independence, financial expertise) relate to the likelihood of a qualified or modified audit opinion? Dataset: Companies House filings’ governance disclosures matched to audit opinion type.

Corporate governance

  1. Does board gender diversity relate to reported ESG performance among FTSE 100 companies? Dataset: Companies House filings + company-published ESG/sustainability reports.
  2. How has UK executive pay (CEO pay ratio disclosure) changed since the pay-ratio reporting requirement took effect? Dataset: Companies House filings’ remuneration reports, comparing disclosed pay ratios over time.
  3. Is there a relationship between board size and financial performance among AIM-listed companies? Dataset: Companies House filings + London Stock Exchange AIM company data.
  4. Do companies that comply fully with the UK Corporate Governance Code report differently on risk than those that “comply or explain” a departure? Dataset: Companies House filings’ corporate governance statements.
  5. What explanations do UK companies give for departing from the Corporate Governance Code, and do these cluster by sector? Dataset: Companies House filings’ “comply or explain” statements.

Management and cost accounting

  1. How have UK manufacturing SMEs adapted costing methods in response to post-2021 energy price volatility? Dataset: ONS producer price and energy price statistics matched to a small primary survey of local manufacturers.
  2. Does activity-based costing improve pricing decisions in UK SME service businesses compared with traditional overhead absorption? Dataset: primary survey/interview data with a small sample of SME finance managers.
  3. What budgeting practices do UK charities use, and how do they differ from private-sector budgeting norms? Dataset: Charity Commission accounts data for a sampled set of registered charities.
  4. How does UK hospitality-sector management accounting practice differ between independent and chain operators? Dataset: primary interview data, supplemented by Companies House filings for financial context.
  5. Do UK manufacturing firms that adopt lean accounting report different cost-variance patterns than those using standard costing? Dataset: primary survey data; ONS manufacturing sector statistics for context.

Taxation

  1. What has been the measurable revenue and compliance-cost impact of Making Tax Digital for VAT on UK small businesses? Dataset: HMRC’s published Making Tax Digital statistics and evaluation reports.
  2. How does the UK’s tax gap (the difference between tax owed and tax collected) break down by tax type and business size? Dataset: HMRC’s annual Measuring Tax Gaps publication.
  3. Has the UK’s Diverted Profits Tax measurably changed the reported profit margins of large multinationals operating in the UK? Dataset: Companies House filings for a sampled set of large UK subsidiaries of multinationals.
  4. What effect has the corporation tax rate change (from 19% to 25% for larger profits) had on UK companies’ reported effective tax rates? Dataset: FAME/Orbis or Companies House filings, comparing effective tax rates pre/post the change.
  5. How do UK SMEs perceive and respond to R&D tax credit changes introduced in recent Finance Acts? Dataset: HMRC’s R&D tax credit statistics, supplemented by a primary survey of SME finance decision-makers.

Sustainability and ESG reporting

  1. How consistent is Scope 3 emissions disclosure across FTSE 100 annual reports, and where do the biggest reporting gaps sit? Dataset: Companies House filings + company sustainability reports for a sampled FTSE 100 cohort.
  2. Does the quality of a UK company’s ESG disclosure relate to analyst forecast accuracy? Dataset: Companies House filings + company ESG reports, matched against published analyst estimates where accessible via your library.
  3. Has mandatory TCFD-aligned reporting genuinely changed the substance of climate risk disclosure, or mainly its length? Dataset: a before/after content analysis of Companies House filings for a sampled cohort around the mandatory reporting date.
  4. What patterns of “greenwashing” indicators appear in UK retail-sector sustainability reporting? Dataset: company-published sustainability reports for a sampled set of UK retailers, content-analysed against a named greenwashing framework.
  5. Do UK companies with a dedicated sustainability committee report more detailed environmental disclosures than those without one? Dataset: Companies House filings’ governance and sustainability disclosures.

Behavioural and social accounting

  1. How do UK SME owner-managers’ personal risk attitudes relate to the conservatism of their financial reporting choices? Dataset: primary survey/interview data with SME owner-managers.
  2. Does accounting information framing (gains vs losses) measurably affect non-expert investors’ decisions in a controlled scenario? Dataset: a primary experimental survey with student or public participants.
  3. What accounting information do UK crowdfunding platform investors actually use before deciding to invest? Dataset: primary survey data with crowdfunding platform users, supplemented by platform-published campaign data.
  4. How do UK charity donors’ trust levels relate to the charity’s published financial transparency (Charity Commission accounts quality)? Dataset: Charity Commission accounts data + a primary donor survey.
  5. Does accounting numeracy affect how UK small-business owners interpret their own management accounts? Dataset: primary survey/interview data with small-business owners.

Public sector and charity accounting

  1. How transparent are UK local authorities’ published accounts under the CIPFA Code, and does transparency vary by council type? Dataset: local authority statements of accounts, which English councils must publish on their websites under the Accounts and Audit Regulations 2015.
  2. What proportion of registered UK charities file their accounts late, and does this correlate with charity size or sub-sector? Dataset: Charity Commission’s register of charities and annual return data.
  3. How has NHS trust financial reporting changed following recent NHS accounting framework updates? Dataset: NHS trust annual accounts, published individually by trusts and summarised by NHS England.
  4. Do larger UK charities show different reserves policies than smaller ones, and how do these compare with Charity Commission guidance? Dataset: Charity Commission accounts data for a sampled set of charities across size bands.
  5. What does variance between local authority budgeted and outturn spending reveal about UK council financial planning accuracy? Dataset: local authority budget and outturn reports, published under statutory financial reporting requirements.
Annual report filings used as a free dataset for a UK accounting dissertation
A large share of accounting dissertation data is public record at Companies House, free of charge.

How do you turn one of these into a real research question?

Run each candidate through three tests before committing. The data test: can you actually access the dataset named above, at the access level your library or Companies House provides for free, within your timeline? The scope test: could you defend your sample size and period in a viva without hand-waving — a panel of 20 FTSE 100 companies over three years is defensible; “all UK companies” is not. The contribution test: does answering the question add something a marker could not already find in one existing paper — a different sector, a different time window around a specific regulatory change, or a UK-specific angle on international findings, is usually enough.

Two of the sub-fields above are worth flagging separately. Management and behavioural accounting topics (16–20 and 31–35) mostly need primary data from real people rather than a downloadable dataset — strong topics, but plan your ethics application and recruitment timeline earlier, since that is usually the rate-limiting step, not the analysis. Public sector and charity topics (36–40) benefit from the fact that local authority and charity accounts carry a genuine statutory-transparency obligation, so refusal or delay in accessing the underlying data is rare compared with private-sector research relying on a company’s goodwill.

How does Tesify help once you have picked a topic?

Tesify can help turn one of these forty questions into a full proposal — sharpening the research question, mapping out the methodology chapter, and structuring your literature review around the specific sub-field.

Frequently asked questions

Is Companies House data really free to use for a dissertation?

Yes — Companies House provides free access to filed accounts and a free API for bulk data, making it the most accessible primary dataset for a UK accounting dissertation with no library subscription required.

Do I need access to FAME or Orbis, or can I manage with Companies House alone?

Companies House alone is workable for smaller samples collected by hand; FAME/Orbis (accessed via most UK university libraries) saves substantial time for larger panel datasets by providing standardised, pre-extracted financial statement data across many companies at once.

Can I use a topic that needs primary survey or interview data instead of secondary datasets?

Yes — several topics above (management accounting, behavioural accounting) are primary-data designs; check your department’s ethics approval timeline early, since primary data collection with human participants needs sign-off before you can start.

How many companies or years of data do I need for a panel study?

There is no fixed rule, but a sample of 20–50 companies over three to five years is typical and defensible at undergraduate level; state your sampling logic explicitly rather than just taking whichever companies were easiest to find.

Should I pick a topic tied to a very recent regulatory change?

It can be a strong angle (less existing literature, genuine novelty) but check the data actually exists yet — a change effective this year may not have produced enough filed accounts under the new rule to analyse by your submission date.

Where can I find more general accounting dissertation topic ideas beyond this list?

See dissertation topic ideas by subject for UK students for the cross-subject pillar and the four-test narrowing method it uses alongside this accounting-specific list.

What is the difference between this list and the finance data-sources article?

This article gives forty complete topic-and-dataset pairings to choose from; where finance students get dissertation data compares the databases themselves in depth (access, cost, what each holds) once you already know roughly what you want to study.

Can two students in the same cohort use the same topic from this list?

It is best avoided where possible — even with the same starting question, choose a different sector, time period or company sample so your dissertations do not end up analysing near-identical data, which can raise unnecessary similarity flags and makes for a weaker viva.