CherryMoney University Training: accounting, invoices, VAT, expenses and AI finance workflows
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Module 7

AI-Assisted Bookkeeping And Review

Use AI suggestions to classify records while keeping review, correction and audit controls.

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Learning Goals

By the end of this module, learners should be able to complete the workflow in CherryMoney and explain the accounting reason behind each important step.

  • Review suggested categories and confidence indicators.
  • Use Approve, Fix category and Ignore actions.
  • Explain why role-gated approval matters.
  • Read audit trail entries for suggestion decisions.

Lesson Plan

Use these lesson blocks for lecture delivery, live demo and class discussion.

Suggestion queue

The queue lets users process suggested categories without exposing them to complex bookkeeping screens.

Confidence and judgement

Confidence is a review signal, not a guarantee. Low-confidence suggestions require careful checking.

Audit trail

Approved, fixed and ignored suggestions should leave a trace so reviewers can understand decisions.

Step-By-Step Lab

This is the student-facing sequence for the practical class. Complete the steps in order, then capture the evidence listed below.

  1. Open the smart suggestions queue.
  2. Filter or scan for high, medium and low confidence suggestions.
  3. Open the source record before approving any suggested category.
  4. Approve a correct suggestion and record the reason.
  5. Fix an incorrect category and choose the better category.
  6. Ignore a suggestion that is not useful or lacks evidence.
  7. Open the audit trail and verify each action was recorded.

Classroom Run Sheet

Use this structure to teach the module in a repeatable classroom or lab session.

Explain
Explain this module Introduce the accounting concept first: customer, invoice, VAT, expense, fund, role or audit trail.
Demonstrate
Demonstrate this module Trainer performs the workflow once in CherryMoney using a projected simulator account.
Practise
Practise this module Students complete the same workflow in their own VM tenant using seeded records.
Review
Review this module Students compare system outputs with expected accounting treatment and discuss errors.
Evidence
Evidence this module Students submit screenshots, exports, PDFs or short explanations for assessment.

Simulator Practice

These are the VM practice tasks for this module. They are written as student-facing tasks and can later be wired into a guided simulator checklist.

Practice Brief

  1. Approve three high-confidence category suggestions.
  2. Fix two wrong categories and write why they were changed.
  3. Ignore one inappropriate suggestion.
  4. Review the audit log for the actions completed.

Knowledge Check

Use these questions for in-class review, a short quiz or a reflective workbook entry. Answers are hidden by default — open each one to check your work.

  1. Q1 What does a confidence badge tell the reviewer? Answer

    How strongly the system believes a suggested category is right. It's a review signal, not a guarantee, so low-confidence suggestions need closer checking.

  2. Q2 When should a user fix a category instead of approving it? Answer

    Whenever the suggested category doesn't match the evidence — approving is never the default action, it's a judgement call for every suggestion.

  3. Q3 Why is the audit trail important for AI-assisted actions? Answer

    It records whether a suggestion was approved, fixed or ignored, and why, so reviewers can understand the reasoning behind every AI-assisted decision later.

Assessment And Evidence

Students should submit proof that the workflow was completed and a short explanation of the decisions made.

Student Evidence

  • Submit a short review note explaining one approved, one fixed and one ignored suggestion.
  • Identify a case where AI should not be trusted without evidence.

Trainer Notes

  • Include ambiguous expenses such as software, training and travel to trigger discussion.

Continue The Course

Move through the modules in order for a complete accounting, invoicing, compliance and AI finance workflow.

Module 5 4 hours

Quotes, Invoices, Cherry Pay And Getting Paid

Run the full sales cycle from quote to invoice, preview, payment request, payment tracking and correction, including Cherry Pay options where enabled.
Module 6 4 hours

Expenses, Purchases, Receipts And Data Intake

Capture expense and purchase records through manual entry, receipt capture, CSV import and review controls.
Module 8 4 hours

VAT, Cherry Tax And Compliance Checks

Prepare VAT reviews, inspect Cherry Tax calculation inputs, understand current MTD/HMRC boundaries and use compliance prompts.
Module 9 2 hours

Payroll Summary Packs

Prepare payroll review packs where the plan includes payroll features.