Supporting Information

A pattern to help users understand complex financial terms in the moment using specific components based on content.

Purpose

The supporting information pattern is designed to help users understand complex financial terms in the moment, without losing their place in a journey. It supports confidence, reduces
reliance on external sources (for example, Google), and avoids disrupting task flow by
keeping users on the same page.

Pattern Summary

Flow diagram showing an information icon button launching a drawer

The icon button triggers a drawer to present the supporting information

  • A recognisable ‘i’ icon button placed inline next to a term
  • Selecting the button opens additional explanatory content in the appropriate component
  • The drawer provides concise, plain-English explanations, with space for
    structured content and links where needed
  • The pattern could be used alongside (not instead of) a page-level glossary,
    giving users multiple ways to access help

Content Display

The following table outlines the components to use for displaying supporting content.

On the React Native platform, the default approach for all is to use a Drawer.

Content

Web Component

React Native Component

Text only

Tooltip

Drawer

Text and single image

Popover

Drawer

Long text, nested components and various media

Overlay Dialog

Drawer

Why does this pattern exist?

Research showed that users:

  • Expect ‘i’ icons to provide explanations of unfamiliar terms
  • Prefer help that keeps them on the same page, rather than opening new pages
    or external links
  • Often skim help content, typically reading only the first sentence, so clarity and brevity is essential
  • Use external sources (Google, FAQs, support) when in-product explanations are
    unclear or hard to find

Design principles to follow

Stay in context - Never navigate users away from their current task to explain a term
Be familiar - Retain the ‘i’ icon rather than relying on links or styling alone
Be concise first - Assume users will skim, lead with the most important explanation