Metric-level score context.

How Fintrics stock scores work.
Fintrics uses stock scores to make company reports easier to scan and compare. This page explains how metric scores, category scores, and overall scores fit together inside that research workflow.
Category and overall score structure.
Research support, not action ratings.
Supported company metrics are translated into a common research scale.
The score framework is designed to make cross-company review easier. Instead of asking users to interpret every raw number from scratch, Fintrics provides a 0-10 context layer that sits on top of the report.
Metric scores
Supported company metrics receive 0-10 score context based on the framework.
Category scores
Related metrics are grouped into broader categories so users can spot areas of strength or weakness faster.
Overall score
Category-level context contributes to an overall company view that helps users scan the report before going deeper.
Scores help users compare companies without treating every metric as equally intuitive.
The purpose is not to replace detailed research. The purpose is to reduce the friction of first-pass analysis so users can move through supported reports more consistently.
- A common 0-10 language helps users compare supported companies faster.
- Category scoring makes it easier to see where deeper investigation may be needed.
- The overall score provides orientation before the detailed metric review begins.
Start broad, then inspect the detail behind the score.
A useful reading flow is to scan the overall score, identify the stronger and weaker categories, then review the individual metrics and source context that explain those differences.
Scan the overall score
Use it as a starting orientation point, not a conclusion.
Check the categories
See which parts of the company context appear stronger or weaker.
Inspect the metrics
Review the detailed supported figures behind the category view.
Read the source context
Use methodology and data notes before deciding what matters most.
Scores can improve comparison quality and research speed.
- They help translate supported company metrics into a repeatable first-pass view.
- They help users compare companies in a more consistent framework.
- They help show where score context may have changed enough to deserve follow-up.
Scores should not be mistaken for a stock verdict.
- A high score does not mean a stock is automatically attractive for every user.
- A low score does not replace detailed business, valuation, or risk analysis.
- Scores do not know your goals, time horizon, or personal circumstances.
Use these pages together.
The score explainer works best when paired with the methodology, source-data page, and the movement explainer so users can inspect the framework from multiple angles.
Common questions about how stock scores work.
A few quick answers on how Fintrics builds scores, what the overall score means, and why the framework should be treated as research context.
How does Fintrics calculate stock scores?
Fintrics turns supported company metrics into a 0-10 research-context scale, groups those scores into categories, and uses them to help summarize the report more consistently.
What is the difference between metric scores and the overall score?
Metric scores describe specific supported measures, while the overall score provides a broader summary of how the company appears within the framework.
Does a high Fintrics score mean a stock is a buy?
No. Fintrics scores are designed for comparison and education, not as buy, sell, or hold instructions.