ChatGPT Enterprise training for finance & accounting teams in Singapore
ChatGPT Enterprise training for finance teams in Singapore: one hands-on day, onsite, on your own files. Analysis and reconciliation. Reporting and commentary.
ChatGPT Enterprise for finance & accounting teams
The reason a finance team buys ChatGPT Enterprise is usually the custom GPT: one reviewed assistant the whole team uses for the same recurring task. This programme builds one on your own finance material and sets the checks that decide whether its output can be relied on.
Where the work happens
- File analysis
- Custom GPTs
- Projects
- Canvas
The distinguishing exercise is building a custom GPT on your own files that a whole team can reuse, plus the verification standards that keep its answers trustworthy.
Who this programme is for
Finance teams, controllers and FP&A leads. Teams building shared internal tools.
- Controllers and finance managers responsible for the accuracy of what gets reported
- FP&A analysts who build variance commentary, budgets and forecasts
- Accountants and finance operations staff running reconciliation and month-end close
- Finance leaders deciding where AI is allowed in the reporting chain and where it is not
Not the right fit
- Teams looking for a vendor demo rather than hands-on practice
- Anyone expecting AI to post entries or approve transactions without human review
- Data science teams building models — this is applied assistant training, not ML engineering
What the day covers
Module 1: Analysis and reconciliation
Ledger extracts are uploaded for analysis, with results independently re-checked against the source before they are used.
Exercise. Work through a sample ledger, identify exceptions and validate calculations against the source.
What you leave with. A reviewed analysis worksheet and reconciliation checklist.
Module 2: Reporting and commentary
A reporting custom GPT is built on your own templates and prior commentary, so variance narratives come out in your house style.
Exercise. Turn verified results into variance commentary, management reports and a board briefing.
What you leave with. A reporting template with source references and review checkpoints.
Module 3: Close and planning
The close checklist is turned into a reusable GPT for the whole team, with review checkpoints written into its instructions.
Exercise. Draft a close checklist, explain budget movements and prepare follow-up questions for budget owners.
What you leave with. A repeatable month-end workflow and planning brief.
A worked example: A variance commentary custom GPT
One exercise from the day, as it runs on your own material in ChatGPT Enterprise.
- What goes in
- A budget-versus-actual export and last quarter's approved commentary, loaded into a custom GPT.
- What is asked
- Draft commentary for every line over the materiality threshold in house style, stating a driver only where the data shows one.
- What comes out
- Draft commentary with each unexplained variance marked "driver to be confirmed by owner".
- What the reviewer checks
- The GPT is tested against a quarter it has not seen; any driver it states that the data does not show fails the test.
Singapore rules the exercises respect
Finance work in Singapore runs against local standards and regulators, and the exercises are set up with that in mind.
- SFRS(I) treatment, such as lease classification under SFRS(I) 16, is a judgement. The assistant can surface the clauses; the accountant makes the call.
- Figures that feed GST F5 returns to IRAS or ACRA filings keep a named human preparer and reviewer.
- For MAS-regulated firms, assistant use sits within your technology risk management and outsourcing assessments. We work inside what your risk team has already approved.
- Customer and counterparty data stays subject to the PDPA, so exercises use anonymised extracts unless your data protection officer has cleared otherwise.
What this day does not cover
Scope is agreed before the session so the day stays hands-on.
- API work, function calling or anything that requires writing code. This is a day for the people doing the business task.
- Admin configuration, workspace provisioning or SSO setup.
- Fine-tuning. The programme builds custom GPTs on your own files, which is a different thing and the one most teams actually need.
Before the session
- A licensed ChatGPT Enterprise seat for each participant
- Working knowledge of Excel or Google Sheets and your own close or reporting process
- Anonymised or sample working files — ledger extracts, a variance pack, a close checklist
- No coding background required
Format and schedule
- Delivery
- On site in Singapore or remote, delivered live. Cohorts are kept small enough that every participant works on their own files rather than watching a screen share.
- Duration
- Typically one full day, or two half-days scheduled around close. Module order is adjusted to your calendar and tool stack.
- How each module runs
- Each module follows the same pattern: a short walkthrough of the technique, a hands-on exercise on your own data, then a review of what the assistant got wrong and how to catch it.
- Afterwards
- Participants leave with the prompt patterns, templates and review checklists produced during the session, so the work continues after the training day.
How your data is handled
- Exercises run inside your own tenant and your own licences, so your data does not leave your environment for the training.
- Files shared with the trainer in advance are anonymised extracts; live production data stays inside your own tenant and licences.
- Every module includes verification: tracing a figure back to source, checking totals independently, and identifying what the assistant omitted.
- Approval and posting stay with your people. The programme teaches AI-assisted preparation and review, never unattended financial action.
Who runs the session
Abhijit Ghosh
Founder, Eagentix · Data & Generative AI Practitioner · Singapore
The programme is delivered by Abhijit Ghosh, who has spent 25 years in data and AI, including roles at Accenture, IBM, Deloitte, Cloudera, Tibco and Wipro. Sessions are run by the practitioner, not handed to a junior facilitator.
Questions about ChatGPT Enterprise for finance & accounting
What does a finance custom GPT actually do?
It holds your reporting templates, your prior commentary and your review checkpoints, so variance narratives come out in your house style with the checks already built in. The day builds one and then tests it against a period it has not seen.
What is a custom GPT and why does the day centre on building one?
It is a reusable assistant configured once with your own files and instructions, then shared with the team. It matters because it turns a good prompt one person wrote into a repeatable standard everyone uses — including the review checkpoints written into its instructions.
Is our uploaded material used to train the model?
Enterprise plans are sold on the basis that business data is not used for training, and your administrators can confirm the terms that apply to your workspace. We cover what to upload and what to keep out regardless, because access scope inside your own organisation matters as much as the vendor terms.
Is this suitable for MAS-regulated finance teams?
Yes, provided assistant use has been approved under your technology risk and outsourcing assessments. The session works inside that approval and does not extend it. Every exercise keeps a human preparer and reviewer, which is what those frameworks expect for material outputs.
Can we use real ledger data in the session?
Inside your own tenant and licences, yes. Anything shared with the trainer beforehand is an anonymised extract. Counterparty and customer details are removed unless your data protection officer has cleared their use.