“Excel, Word, PowerPoint, IDEA, ACL, SAP, Power BI.” The tools section of an auditor’s CV often looks like a shopping list. Yet it is read carefully: an audit lead wants to know whether you will be able to extract a general ledger, reconcile two files, test a population of journal entries or document your work in the firm’s tool without someone holding your hand. The section still has to give them that information. This article explains what the recruiter reads in the tools section, the families of software used in audit, the place of the spreadsheet, and above all how to describe real use rather than lining up names.
What the recruiter reads in the tools section
An audit recruiter is not trying to find out how many software packages you know, but what you will be able to do on your own from the first engagement. They read the tools section with three questions:
- can you handle large volumes of data (general ledger, aged balance, journal entry file) without error?
- do you know clients’ systems (ERPs, accounting software) well enough to find information in them or understand an extraction?
- will you be able to document your work in a file tool, following a methodology?
A list of names answers none of these questions. A line that links a tool to a task answers them immediately.
Applicant tracking systems (ATS), for their part, look for keywords. Tool names must therefore appear on the CV, but built into a context that will then convince the human reader.
Data-analysis tools in audit
Data-analysis tools make it possible to work on a whole population rather than a sample: all the entries for a financial year, all the invoices from a supplier, all the payments in a period.
Specialist audit tools. IDEA and ACL Analytics have historically been the most widespread in firms and internal audit departments. They make it possible to import large files, filter them, cross-reference them, extract samples and keep a record of the operations performed, which makes documentation easier.
Data preparation and visualisation tools. Alteryx, Power Query and Power BI, Tableau or Qlik are increasingly used to prepare data from several systems and produce visual analyses: margin trends by site, customer concentration, distribution of entries by user.
Languages. SQL and Python appear in the data-analysis teams of the large networks and in IT audit teams. For an assistant or a senior, they are not required, but they are an increasingly visible asset. The topic is developed in our article on data analytics in audit.
The most common analyses on engagements: journal entry tests (manual entries, period-end entries, round amounts, entries posted by unusual users), searching for duplicate payments, reconciliations between systems, analysis of payment terms, detailed analytical review.
Working-paper software and in-house tools
Every firm documents its work in a file tool: a market product such as CaseWare Working Papers, or a tool developed in-house by the network. These tools structure the file according to the firm’s methodology: understanding the entity, risk assessment, work programme, working papers, open points, summary.
Should you name a firm’s in-house tool? It is not essential, and some proprietary tools have names that will mean nothing to another recruiter. “The firm’s audit tool” is often enough, provided you specify what you did in it: documenting tests, reviewing working papers, tracking open points.
Clients’ software. On the client side, the auditor encounters ERPs (SAP, Oracle, Microsoft Dynamics) and accounting software (Sage, Cegid, accounting firm software). Knowing how to navigate SAP, run a display transaction or understand the structure of an extraction is a real skill, worth mentioning if you have it.
The spreadsheet, a skill expected everywhere
Excel remains the most used tool in audit, and the worst described on CVs. Everyone writes “Excel”; the recruiter wants to know at what level.
A useful level in audit includes:
- lookup and matching functions (XLOOKUP, INDEX and MATCH);
- pivot tables to analyse a trial balance or general ledger;
- advanced filters and conditional formatting to spot anomalies;
- Power Query to import and clean large files;
- building readable working papers, with references to supporting documents and footing checks.
Writing “advanced Excel” proves nothing; writing “Excel: pivot tables, XLOOKUP, Power Query to reconcile the general ledgers of several entities” places your level and gives the recruiter a basis for questioning you.
Describing concrete use rather than a name
The rule is simple: every important tool should appear at least once in an experience line, linked to a task and a result. The skills section then serves as a summary.
Before / after in your experience
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Before: “Used IDEA.”
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After: “Exhaustive journal entry testing for 6 clients in IDEA: extraction of year-end manual entries and round amounts, selection of entries to be supported.”
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Before: “Knowledge of Power BI.”
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After: “Power BI dashboard for analytical review of margins by site and by month, reused by the team on industry-sector engagements.”
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Before: “SAP.”
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After: “Extracted and analysed SAP access rights for 4 groups for the IT audit team: identified segregation-of-duties conflicts.”
In the skills section, group by family:
- Data analysis: IDEA, Alteryx, Power BI, SQL (basic);
- Spreadsheet: Excel (pivot tables, XLOOKUP, Power Query);
- Client systems: SAP (display, extractions), Sage, Cegid;
- Documentation: the firm’s audit tool, CaseWare.
For a data-oriented profile, the question of what SQL level to claim arises in the same way as in data jobs: the article on the SQL level to state on a data CV 🔗 offers a useful grid for assessing yourself honestly.
Common mistakes in the tools section
- Listing obvious office software (Word, Outlook, Teams): it takes up space without saying anything.
- Claiming a tool never used on an engagement: the first interview question will be about it.
- Using gauges or stars: they mean nothing to a recruiter and are poorly read by ATS.
- Forgetting clients’ tools: ease in an ERP is a real skill.
- Confusing a course taken with practice: “introduction to ACL during my master’s” should be presented as such, not as mastery.
- Naming an obscure in-house tool without explanation: a recruiter from another firm will not know it.
For an example of a well-built tools section, see the IT auditor CV example, which cites the SAP transactions and languages actually used, and the audit assistant CV example, which specifies the Excel level. The guide on how to describe your audit engagements complements this advice. Once the section is rewritten, the CV editor lays it out without tables or icons, and produces a PDF that ATS read word for word, which ensures that tool names will be picked up.
Sources
- Haute Autorité de l’audit, the professional standards framework for statutory auditors 🔗.
- KPMG France, recruitment in audit roles 🔗.
Frequently asked questions
Do you need to master IDEA or ACL to be hired in audit?
Not for an internship or a first job: firms train people on their tools. Some first-hand practice, even in class, is nevertheless an asset and is worth mentioning at its real level.
Where should tools go on the CV?
In your experience, linked to tasks, then summarised in the skills section, grouped by family.
Should you mention Python on an auditor’s CV?
If you have used it for a real analysis, yes, describing the use. A simple introduction can appear as “basic”, without highlighting it.
Are vendor certifications worth anything?
They show a training effort and reassure about a specific tool. They do not replace an experience line describing what you did with the tool.