Public filing-derived company inputs.
Stock scoring methodology
How Fintrics scores stocks and organizes company research.
Fintrics uses public company data, sector-relative comparison, and macro context to turn raw inputs into a more readable stock research workflow. The methodology is built to explain the framework behind the scores, not to present a stock verdict.
Last updated: 13 July 2026
This page answers four practical questions: what goes into the model, why sector context matters, what the scores can and cannot tell you, and how to use the framework inside a real stock report.
Fintrics scores summarize research context. They are not personal guidance, recommendations, or predictions of future returns.
Sector-aware scoring framework.
Research and education context only.
General information only
Fintrics PTY LTD does not provide personalized outputs. Fintrics content, including scores and commentary, is for general information and education only. Historic relationships and model outputs are not reliable indicators of future results. See our Terms of Service, data sources page, and the explainer routes linked below.
What goes into a Fintrics stock score
The methodology starts with public company data, then adds sector and macro context.
The point is not to compress a company into one magic number. The point is to give users a repeatable structure for reading company reports, supported metrics, and changing score context.
Step 01
Collect the inputs
Fintrics gathers supported filing-derived company metrics and public context data.
Step 02
Compare in context
Those inputs are reviewed in a sector-aware framework so the comparisons stay more relevant.
Step 03
Summarize the research
Category and overall scores help users scan the report before reading the detailed underlying data.
Why sector context matters
A useful score should compare businesses in a relevant setting.
Debt, margins, growth, cash generation, and other metrics can look very different across industries. Sector-relative scoring helps Fintrics avoid treating every business model as if it should behave the same way.
- The framework is designed to make comparisons more relevant for the type of company being analyzed.
- Scores become easier to interpret when they are linked to sector norms instead of one-size-fits-all thresholds.
- Macro context adds another layer when broader economic conditions help explain company results.
Methodology pillars
Fintrics organizes stock research through several connected layers.
These are the main ingredients behind the stock scoring methodology and the report structure users see on company pages.
Public company metrics
Fintrics starts with filing-derived company metrics, reported financials, and related disclosures that can be processed into a repeatable research structure.
Sector-relative comparison
Each company is evaluated in the context of its sector so the score framework stays more relevant to the kind of business being reviewed.
Macro context where relevant
Public macroeconomic series help frame whether company data is landing in a stronger or weaker economic environment.
Weighted category scoring
Supported metrics roll into category-level views that make it easier to see where company context appears stronger or weaker.
Overall research summary
Category scores contribute to a broader company-level view that helps users scan the report before reading the detailed supporting data.
Refresh after new source data
Scores update after supported public source data is processed. Fintrics is not a live feed and does not treat old and new periods as the same thing.
What a Fintrics score can tell you
Scores can help you scan a company faster and compare it more consistently.
- Whether the model reads supported company metrics as stronger or weaker in relative context.
- Which categories may deserve closer attention before deeper research.
- Whether broad report context appears to be improving, weakening, or staying relatively stable over time.
What a Fintrics score cannot tell you
The methodology still has real limits.
- A score cannot account for your personal circumstances, objectives, or risk tolerance.
- It cannot remove source delays, restatements, or data-processing limits from public information.
- It should not be treated as a recommendation, guaranteed ranking, or prediction of future performance.
How to use the methodology with a stock report
Use the methodology as the trust layer behind the report workflow.
The best way to use this page is alongside the score and movement explainers. Read the methodology, open a report, inspect the score breakdown, and then review the source context that matters most for your own research.
FAQ
Common questions about the Fintrics stock scoring methodology.
A few quick answers on what the model uses, why sector context matters, what the score can tell you, and how to read it inside a report.
What goes into the Fintrics stock scoring methodology?
Fintrics uses public filing-derived company metrics, sector context, and macroeconomic inputs where relevant, then organizes them into category and overall research-context scores.
Why does Fintrics use sector context in stock scoring?
The same raw metric can mean different things in different industries. Sector context helps Fintrics compare companies against more relevant business conditions instead of one universal threshold.
What can a Fintrics stock score tell me?
A score can help you see whether a company appears stronger or weaker within the modelled research framework. It does not tell you what action to take and should not be treated as personal guidance.
How should I use the methodology with a stock report?
Use the methodology to understand what the scores are measuring, then open a report and review the supporting metrics, source context, and score movement before forming your own view.