Guides for finance teams evaluating AI
Written for a mid-market finance leader who has already tried ChatGPT, found it unreliable for numbers, and wants to understand why before spending money on an alternative.
AI for Financial Analysis: 2026 Buyer's Guide
12 criteria, 6 approaches compared including ChatGPT and Claude, an honest scorecard, and the questions that expose a weak vendor in a demo.
Find Your Fit
Eight questions about your team and systems. Get a ranked recommendation across all six approaches: several paths point somewhere other than DataWyse.
Head-to-head comparisons
DataWyse against ChatGPT, Claude, Copilot, Datarails, Mosaic, Cube, Drivetrain, and Fathom. Every page names where the alternative wins.
Practitioner guides
Long-form guides on variance analysis, cash forecasting, cohort retention, reconciliation, and the real cost of ad-hoc work.
Finance glossary
245 terms across FP&A, accounting, SaaS metrics, cash management, and AI in finance: defined in plain English, with the definition traps named.
Free finance tools
21 tools for the question in front of you right now. No signup, runs entirely in your browser.
Which of these you need depends on where you are
You have already tried ChatGPT or Claude and it did not stick
Start with the ChatGPT comparison or the Claude comparison. Both explain the mechanism behind the failure rather than just asserting it: a language model predicts arithmetic as text rather than executing it, and holds no durable knowledge of your fiscal calendar or metric definitions. Understanding that is what stops you buying the same problem twice.
You are evaluating tools and want a framework
The buyer's guide sets out twelve criteria and scores six approaches against them, including general-purpose chat, BI copilots, FP&A platforms, and hiring a person. It names where each one genuinely wins, including where they beat us. If you would rather skip the reading, Find Your Fit asks eight questions and ranks all six for your situation in about two minutes.
You have a specific job to do right now
Go straight to the free tools. Twenty-one of them, no signup, running entirely in your browser. The paste-and-go set: cohort retention, ledger reconciliation, P&L variance bridges, each replace an analysis that takes twenty minutes or more to assemble by hand in a spreadsheet.
You want to understand the problem before the products
The practitioner guides cover variance analysis, thirteen-week cash forecasting, cohort retention, and month-end reconciliation, with worked arithmetic rather than summary. The glossary defines 245 terms in plain English and, where finance teams genuinely disagree on a definition, says so, because a metric only means something once you know whose definition it uses.
Everything here is written by DataWyse and we build an agentic analysis product, so read the comparisons and the scorecard with that in mind. We have tried to be accurate about where other approaches win outright, and several paths through the decision tool recommend something other than us.
Which approach fits your team?
Eight questions, about two minutes, and an answer that sometimes points away from us.