FINANCIAL ANALYSIS
Conversational Financial Analysis on Sage Intacct Data
The gap between a question and an answer is where finance loses its afternoons. Conversational analysis on Sage Intacct closes it: ask in plain language, get a sourced answer sliced by any dimension, and turn the good questions into standing management views.
- Conversational analysis turns a report build into a plain question and a sourced answer.
- Sage Intacct dimensions let the analysis slice by location, department, project or class in one sentence.
- The Finance Intelligence agent on Sage Copilot already answers questions, on an Early Adopter basis.
- The next step is standing management views that update themselves, not just one off answers.
- ChatFin answers, sources every figure, and can act on the answer with a governed transaction.
FP and A spends more time preparing analysis than doing it. Export, model, format, repeat. Sage Copilot is the embedded assistant, and the Finance Intelligence agent that runs on it lets users ask questions of their financial data. That agent is still in a phased Early Adopter rollout, switched on per company by an administrator, and several Copilot features launched in the US and UK first. That handles the ad hoc question.
Conversational analysis on Intacct goes further because of the data model. Sage Intacct tags every transaction with dimensions rather than burying detail in a long segmented account code. The standard set covers location, department, project, class, customer, vendor, employee and item, alongside any custom dimensions a company defines. A question about margin by region and product line resolves cleanly, and the good questions can graduate into standing views that refresh on their own.
Ad hoc questions, answered in place
The daily reality of FP and A is a stream of questions from around the business. Why did marketing spend jump. Which projects are underwater. How does this region compare to last year. Each one used to mean a small build. Now it means a sentence.
A good conversational layer returns the number and the transactions behind it, so the answer is checkable rather than a claim.
The dimension advantage
Sage Intacct tags every transaction with dimensions rather than burying detail in a long segmented account code. The standard set covers location, department, project, class, customer, vendor, employee and item, alongside any custom dimensions a company defines.
That is why Intacct is a strong base for analysis. The slices you want to analyze by are already on the data. See dimensional analysis for how deep this goes.
From questions to standing views
The questions people ask repeatedly should become standing management views. Margin by product line, spend by department, project profitability. Once defined, they refresh from the ledger rather than being rebuilt each month.
This is the bridge from answering to management reporting, covered on board packs and management reporting.
Where native Copilot reaches
The Finance Intelligence agent answers questions and shows its reasoning, and Copilot variance analysis flags what moved. For a user inside Intacct wanting a quick answer, that is a real capability. ChatFin extends it into sourced, standing analysis and into action.
Answers you can defend
An answer in chat is only useful if it survives scrutiny. ChatFin sources every figure to the underlying transactions and keeps a record of the question and the data assembled, so a number can be defended in a board meeting, not just quoted.
Acting on the answer
Analysis that ends in an insight is half the job. When the answer implies an action, a reclass, a correction, a follow up, ChatFin can draft it and route it for approval, closing the loop between asking and doing.
Rolling it out
Start with the questions your team answers every week, confirm them against known reports, then widen. The guide to AI agents for FP and A covers the broader toolkit.
Ask, Analyze and Act on Sage Intacct Data
Conversational analysis turns a report build into a plain question and a sourced answer, and Sage Intacct dimensions make the slicing precise.
ChatFin answers, sources every figure and can act on the answer. Book a demo to try it on your own data.