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By Competitive Compass
Canada Deep Dive · EQ BANK July 2026
Canada · Direct Bank

EQ Bank.

EQ Bank writes the clearest rate content in the Canadian field. Extending the edge treatment Googlebot already receives to named AI crawlers carries it to every agent.

Agent Readiness Score
58 / 100
Technical Readiness
27 / 50
Content Architecture
31 / 50
Rank 11 of 15 · Direct bank · Surfaces reviewed 6 · Range across surfaces 15 to 76 · Band Building

EQ Bank posts an Agent Readiness Score of 58 out of 100 in the AI Compass Canada July 2026 Index. The score splits into Technical Readiness at 27/50 and Content Architecture at 31/50. The rates hub, deposit pages and disclosures are among the best written in this field, and the robots file allows everyone. Aligning the edge with that stated policy and rendering the GIC page are the two moves that follow.

The Read

What an agent receives.

The written content is excellent. The rates hub serves 15 real HTML tables and 105 rows in the first response, including “30 Day Notice Savings Account | 2.75%” and “Registered 5 years | 4.00%”. Mortgage rates arrive as seven tables with 78 distinct percentage figures and APR included, which is rare in this field.

Product pages answer the question directly. The Personal Account h1 reads “Earn 2.75% interest on every dollar”, and the body states the qualifying rule in full: “If you set up direct deposit for your pay of $2,000/month or more, you will start earning 2.75% interest within the first two weeks of the month following your first qualifying transaction.” Disclosures travel with the page, including the CDIC limit and the full list of products offered outside Quebec.

The edge is where the next points sit. The robots file is 79 bytes and fully permissive, allowing everything and naming a sitemap. At the edge, GPTBot, ClaudeBot, ChatGPT-User, PerplexityBot, CCBot, Bytespider and Applebot each receive HTTP 403, while Googlebot and an ordinary browser receive 200 on the same URLs, repeatably. Extending the Googlebot treatment to the named AI crawlers matches the server to the stated policy.

Two pages are ready for the content that already exists. The GIC page returns 200 with the correct title and 3,189 characters of navigation and footer, and the term ladder on the rates hub is ready to move in. The category roots follow the same shape, so the answer arrives where the question lands.

Surface Scorecard

Flagship product by sub-category.

EQ Bank is a focused direct bank, so six sub-categories were reviewed rather than seven. One flagship product was selected for each. Each surface was read from the server response, without a browser session.

Sub-category and flagship product
Tech /50
Cont /50
Score /100
Everyday banking
Personal Account
32
44
76
Cards and payments
EQ Bank Card
32
42
74
Savings
Notice Savings Account
30
40
70
US dollar and FX
US Dollar Account
32
38
70
Mortgages
Residential Mortgage Products
24
21
45
Investing and GICs
GICs
13
2
15
Strengths and Opportunities

What is working and where the value sits.

What Is Working

The central rates hub is genuinely machine readable. It serves 15 real HTML tables, 48 header cells and 105 rows in the first response, including “30 Day Notice Savings Account | 2.75%”, “TFSA Cash Savings Account | 1.50%” and “Registered 5 years | 4.00%”.

Mortgage pricing arrives as parsed tables with APR included. The mortgage rates page serves 7 tables and 78 distinct percentage figures, including “5 Year Fixed 5.24%”, “Annual Percentage Rate (APR) 5.688%” and “Equitable Prime Rate (P) 4.45%”.

Deposit pages serve the rate, the rule and the FAQ as plain text. The Personal Account h1 reads “Earn 2.75% interest on every dollar”, with the qualifying rule stated in full beneath it.

Footnotes, terms and provincial carve-outs travel with the page. The footer serves the base rate, the bonus rate mechanics, “CDIC protection up to $100,000, per insured category, per depositor” and the full provincial product list.

Where The Value Sits

The edge is ready to serve named AI crawlers. Three consecutive requests each returned 403 for GPTBot, ClaudeBot and PerplexityBot on the personal banking path, against 200 for Googlebot on the identical path. Matching the Googlebot treatment aligns the server with the robots file.

The GIC product page is ready for content that already exists. It returns 200 with the title “GICs | EQ Bank” and 3,189 characters of navigation and footer, and the term ladder on the rates hub is ready to move in.

The category landing pages are ready for the same treatment. The personal banking root returns 200 with page title “Site” and 2,409 characters, and the savings root follows the same shape.

Structured data and comparison tables are the open items. Across nine pages fetched there are zero JSON-LD blocks and zero table tags on the six flagship product pages, and the llms.txt path returns a soft 404 with a 200 status.

The encouraging read: content quality of this standard is the part that takes years, and it is already finished. One edge rule and one page render move the score substantially.

EQ Bank publishes the clearest rate tables in this field, and opening the edge carries them to every agent written to read them.
Field Position

Where EQ Bank sits in the Canadian field.

EQ Bank sits in the middle of the Canadian field on a score that understates the quality of its writing. One edge rule change moves it substantially. Scores shown are the nearest neighbours in the July 2026 Canadian field.

10
CIBCBig Five bank
58
11
EQ BankDirect bank · This report
58
12
58
The Two Dimensions

Where the work lives.

Every Agent Readiness Score splits into Technical Readiness and Content Architecture. The two halves point to different teams and different timelines.

Technical Readiness
27 / 50
Access, discovery and retrievability. The robots file is permissive and the rates hub renders fully server side. The points still available sit almost entirely on the edge treatment of named AI agents.
Content Architecture
31 / 50
Whether the page answers the question a person actually asks. Four surfaces answer in full with rate, rule and disclosure. The GIC page is ready for its content, which is why the range runs from 15 to 76.
The 90-Day Path

Four moves to the leading band.

Sequencing, effort estimates and the surface-by-surface build order sit in the full engagement plan. Item one carries the largest share of the available lift.

1

Serve named AI crawlers at the same rate limit Googlebot receives.

Allow the read-only retrieval agents through the edge and state the policy explicitly in robots.txt so the file and the server agree.

2

Server render the GIC page and the category roots.

Move the term and rate content that already exists on the rates hub into the served HTML of the GIC page, with the same table markup, so the answer sits where the question lands.

3

Put the rate tables on the product pages as well as the hub.

The hub proves the tables render server side already. Repeat the relevant rows on each flagship page and add one comparison table per category.

4

Publish an llms.txt and add schema markup.

Replace the current soft 404 with a real index of the roughly 435 sitemap URLs, and add FAQPage and Offer JSON-LD to the deposit and mortgage pages.

The direction of travel favours EQ Bank. Content quality of this standard is the part that takes years, and it is already finished.

EQ Bank has already written the answer. Opening the door and filling one page is the whole of the work.
Methodology

How the score is built.

AI Compass measures what an AI agent receives when it visits a financial institution website on a customer’s behalf. It reads the served response the way an agent does, without a browser session, without scripts, and without a human clicking to reveal a value.

Scoring bands

  • Leading 70 to 100. The page answers the customer question in full.
  • Building 50 to 69. The story arrives and a decisive field is ready to be published.
  • Early 0 to 49. An agent leaves with a partial answer.

How the total works

Each product surface earns a score out of 100, built from Technical Readiness out of 50 and Content Architecture out of 50. The institution score is the average across the surfaces reviewed, up to seven.

Technical Readiness · 50

  • Crawler permission. Robots rules, treatment of named AI agents, sitemap presence, and whether the edge serves them.
  • Machine-readable discovery. An llms.txt index and the quality of what it describes.
  • Server-side completeness. How much of the page arrives in the first response.
  • Retrievability. Stable URLs, working paths, clean status codes, content served ahead of any gate.
  • Disclosure availability. Whether terms and footnotes travel with the page.

Content Architecture · 50

  • Price in text. Rate, APR, fee and bonus values present as readable figures.
  • Eligibility in text. Provinces, balances, income, credit position, qualifying activity.
  • Comparison structure. Tables an agent can parse across products.
  • Question coverage. FAQ content served as text rather than as a call.
  • Plain answers. Wording that maps to how customers ask the question.

Surface selection and review window

Sub-categories come from the personal banking navigation on each brand’s Canadian root. Within each one, the flagship is the product the institution itself features first. Brands with fewer product lines are scored on the surfaces they actually sell, so a focused brand is measured on quality rather than on breadth.

Pages were read on 30 July 2026. Rates, bonus offers and terms move, and scores describe what each site served on that date. Where a site offers more than one language, the version served by default to a request with no language preference was used.

Independence and scope

Scores come from observed page behaviour alone. No institution reviews or approves a score before publication, and every brand is measured against the same rubric. Outlier results are verified against a second independent retrieval pass before publication.

The score covers the public marketing site. Logged-in banking, the mobile app and the branch experience sit outside it. A site can score well here and still have work to do inside the login, and the reverse holds too.

Frequently Asked

Common questions about the EQ Bank score.

What is the AI Compass Canada score for EQ Bank?

EQ Bank carries an AI Compass Agent Readiness Score of 58 out of 100 in the July 2026 Canada Index. That is the sum of Technical Readiness (27/50) and Content Architecture (31/50), scored across 6 product surfaces and read from the server response on 30 July 2026.

How is the EQ Bank AI Compass score calculated?

Each product surface earns a score out of 100, built from Technical Readiness out of 50 and Content Architecture out of 50. Technical Readiness covers crawler permission, machine-readable discovery, server-side completeness, retrievability and disclosure availability. Content Architecture covers price in text, eligibility in text, comparison structure, question coverage and plain answers. The institution score is the average across the surfaces reviewed. EQ Bank sits at 27 on Technical Readiness and 31 on Content Architecture.

Which EQ Bank surface is most agent ready today?

The strongest surface is Everyday banking at 76, with Cards and payments at 74 close behind. The next points sit on the edge rule for named AI crawlers and on server rendering the GIC page from content that already exists on the rates hub.

How often is the EQ Bank AI Compass score refreshed?

Canada scores are refreshed each edition of the AI Compass Index, and a deep dive is refreshed whenever a brand ships a major site or content change. The July 2026 edition reads the served response on 30 July 2026. Subscribe at competitive-compass.com to get the next refresh.