Demonstration environment. Fictional organisations and data where not signed in to your workspace.

For audit practices

Audit Firm AI Engine

Supports audit firms with risk-based planning, journal entry analytics, workpaper drafting and quality review - preserving professional scepticism and the engagement partner's judgement.

Calloway & Partners LLP (fictional)ISA 240 · ISA 315 · ISQM 1 aligned

01Engagement portfolio

Calloway & Partners LLP (fictional) · listed-entity engagements

02Client Delta at a glance

Materiality £4.2m · 1,180 of 2,400 budgeted hours · manager Tom Ashby

Review Hours Released

640

2,140 across the portfolio

DEL640
AST210
BRO380
COR520
ELM390

Engagement workspace · Client Delta

Significant risks ? journal entry analytics ? workpaper review ? quality & EQR ? findings and professional review

Significant risks
Significant risk	Assertions	Inherent risk	Planned response	Status
SIG-01Fraud risk Revenue cut-off around period end, including bill-and-hold arrangements	Cut-off Occurrence	Critical	Test 100% of shipments ±10 days of year end; confirm bill-and-hold criteria with customers. AI support: Full-population cut-off analytics; contract clause extraction	In progress
SIG-02Fraud risk Management override of controls	Occurrence Accuracy	High	Journal entry testing on risk criteria; review of estimates for bias; significant unusual transactions. AI support: JE risk scoring across 1.28m lines	In progress
SIG-03 Valuation of slow-moving inventory	Valuation & allocation	Medium	Recompute provision using ageing and sell-through data; test post year-end sales. AI support: Inventory ageing analytics	Planned

Demonstration

Engagement workflow

Analytics inform; the engagement partner concludes.

1AI-supported
Risk assessment support
Prior-year, industry and client data synthesised for the team.
2AI-supported
Journal entry analytics
Full population scored against ISA 240 risk criteria.
3AI-supported
Workpaper drafting
Procedures documented in firm templates for review.
4Human
Professional scepticism
Engagement team challenges and investigates flagged items.
5Human
Partner conclusion
Engagement partner forms and records the audit conclusion.

Run the workflow to see how automated steps hand off to accountable reviewers.

Methodology scenario

Portfolio-wide adoption of full-population testing

SCN-AF-JE · Methodology

Full-population JE testing across portfolio

Replace sample-based journal entry testing with full-population analytics across all 38 listed-entity engagements.

Approved

Assumptions

Engagements: 38
Rollout: FY26 year-ends

Modelled outcomes

Coverage

100%

from ~3% sampled

Review hours

-2,140 hrs

Favourable

Inspection findings risk

Lower

Favourable

Model confidence88% · Moderate

Owner: Rebecca Thornton, Audit Partner · Updated 27 Sept 2026

AI-supported output. Human review and approval required before use.

Significant risk

Assertions

Inherent risk

Planned response

Status

SIG-01Fraud risk

Revenue cut-off around period end, including bill-and-hold arrangements

Cut-off
Occurrence

Critical

Test 100% of shipments ±10 days of year end; confirm bill-and-hold criteria with customers.

AI support: Full-population cut-off analytics; contract clause extraction

In progress

SIG-02Fraud risk

Management override of controls

Occurrence
Accuracy

High

Journal entry testing on risk criteria; review of estimates for bias; significant unusual transactions.

AI support: JE risk scoring across 1.28m lines

In progress

SIG-03

Valuation of slow-moving inventory

Valuation & allocation

Medium

Recompute provision using ageing and sell-through data; test post year-end sales.

AI support: Inventory ageing analytics

Planned