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Competitive Compass Research  ·  US Credit Cards  ·  August 2026

The Trust Transfer Index

What AI assistants tell prospects and existing customers about your credit card today, and what you can change about it. Fifty open US consumer cards, read across five assistants, scored on the answer a customer is reading right now.

Coverage  50 open US consumer credit cards
Issuers  12 brands, 8 categories
Period  August 2026
Refresh  Quarterly
50
Cards measured
5
AI assistants
1,500
Answers read
10,923
Claims audited
Executive readout

What the study found.

Assistants describe US credit cards to customers every day. The numbers below say how well they do it, and where a bank can change the outcome.

20.6
Points of spread

The strongest and the weakest card sit twenty points apart.

Fifty cards on one scale, measured on answers customers are reading today.

2.3×
More separation

The answer already running divides the market more than better evidence could.

What is published today is doing the sorting. That is the lever with the shortest handle.

41
Point credit gap

The facts are right. The bank is rarely named for them.

The median card is stated correctly 86 percent of the time and credited to the bank 45 percent of the time.

75.3
Highest card score

The standard the market can read already exists.

Citi Double Cash leads all fifty cards. Capital One holds the strongest issuer average at 71.3.

A question worth asking

If a customer asked an assistant about your flagship card today, do you know what it says?

The business issue

The assistant answers before the customer reaches the bank.

It picks the facts, the conditions, and the source. The bank page is often the second thing the customer reads.

The question goes to the assistant

Customers ask which card suits them, what it earns, and what it costs. An assistant answers all of it in one pass, in its own words.

The assistant picks the evidence

It reads what it can find on rates, rewards, and conditions, then names a source for the claim. That source is usually a third party.

The bank page arrives last

By the time the customer opens it, the comparison has been made and the shortlist is set.

What to do

Publish the facts an assistant needs before the customer asks for them. Write the card page as evidence, not as a brochure.

Exhibit 1  ·  The main finding

Today's answer separates cards more than better evidence would.

AI Quality spans 20.6 points across the fifty cards. Trust Upside spans 9.1. The answer already in the market creates 2.3 times more separation than the upside from clearer evidence.

AI QualityAnswer seen today
20.6
Trust UpsidePossible gain
9.1
0510152025
Points of spread
What to do

Correct the facts, conditions, and sources on the page before commissioning another market test.

AI Quality measures the answer customers read now: are the facts correct, current, complete, and credited to the bank. Trust Upside estimates how much clearer evidence could move trust, consideration, verification, and intended action. The first is observed. The second is modelled. Source: Trust Transfer Index analysis, August 2026. n = 50 cards.

Exhibit 2  ·  The field of fifty

The best and the weakest card are 20.6 points apart.

The line below is the whole field: fifty open US consumer cards on one scale. The strongest sits at 75.3, the weakest at 54.7. Everything a customer reads about the other forty-eight falls between them.

Weakest card
54.7  ·  Unnamed
Citi Double Cash
75.3  ·  Strongest card
The other 48 cards sit along this line
50556065707580
AI Quality score

What this means

A twenty point spread on a measure customers act on is a real distance. It separates a card that explains itself from a card that leaves the explaining to someone else.

What to do

Find your own cards in this field before the next planning cycle. A card you have read an AI answer for is a card you are managing.

Where the scale comes from

Each card is scored on whether the facts are correct, current, complete, and credited to the bank across five assistants and three question types.

Exhibit 3  ·  Portfolio strength

Capital One leads with consistency.

The dot is each issuer's portfolio median. The line is the distance from its lowest to its highest scoring card. Capital One sits at the top with the tightest span in the study: a customer gets the same quality of answer whichever of its cards they ask about.

Capital One
68.6 to 73.3
Discover
55.3 to 72.8
Bank of America
62.4 to 73.4
American Express
66.9 to 73.6
U.S. Bank
57.9 to 73.3
Navy Federal
60.4 to 71.9
Wells Fargo
59.0 to 71.3
Synchrony
65.3
Chase
56.9 to 69.6
Citi
52.9 to 75.3
Barclays
58.9 to 66.0
First PREMIER
55.3
50556065707580
AI Quality score

What this means

A high median with a short line is the strongest position on this chart. It says the standard behind the best card has reached every other card in the house.

What to do

Take your clearest card page and make it the house template. A standard travels further than a campaign, and costs less.

Reading the chart

Single-card issuers appear as one point. Source: Trust Transfer Index analysis, August 2026.

Exhibit 4  ·  The leading card

Citi Double Cash is the clearest card in the market.

75.3, the top score in the study. It leads because there is almost nothing to interpret: one promise, stated once, in language an assistant can quote without hedging.

Terms that fit in a sentence

One earning rule, no tiers to summarise, and every footnote points the same way as the headline.

Every fact in one place

What a customer asks about lives together on the card's own page, current and dated, where it can be read in a single pass.

Quoted, not paraphrased

Unambiguous wording gets repeated as written, and the bank keeps its name on the claim.

What to do

Simplicity is a design choice, available to any issuer. Write the next card page so there is nothing left to interpret.

A question worth asking

Which of your cards could a customer explain back to you correctly after one answer?

Exhibit 5  ·  The evidence gap

AI gets the facts right. Someone else gets the credit.

The median card scores 86 percent on correct and current facts, and 45 percent on bank source authority. The 41 points between those two numbers is the clearest job on this page.

Facts correct and current
86%
Bank credited as the source
45%
0%25%50%75%100%
Median of 50 cards

What this means

Review sites and news outlets receive the credit while the bank's own facts are accurate. The customer reads a correct sentence with a third party's name on it.

What to do

Make the official facts easier to find, easier to pull, and easier to quote. One dated fact page per card, written to be read by a machine.

The size of the prize

41 points of source authority sit inside the bank's own control, and the content behind them is already written.

A question worth asking

Your facts are right and a third party is quoted for them. What is that worth, and to whom?

Exhibit 6  ·  Assistant behaviour

The assistants credit the bank at different rates.

Fact accuracy holds near the 86 percent median on all five. What differs is whether the bank's own page is shown as the source. ChatGPT and Claude do it far more often than Gemini and Copilot.

ChatGPT
High
Claude
High
Perplexity
Medium
Copilot
Building
Gemini
Building
How often the bank appears as the source

Perplexity cites constantly and names the bank some of the time. Source: Trust Transfer Index analysis, August 2026. Claim-level diagnostics, ranked.

What this means

What works on one assistant carries partway to the next. An assistant that shows your page is the one sending the customer to it.

What to do

Test each assistant separately, and read the answers yourself once a month.

A question worth asking

Do you know which assistant your best customers use, and how it describes you to them?

Exhibit 7  ·  Consumer opportunity

Where clearer evidence pays back first.

Trust Upside estimates how a customer's response could change if the evidence were clearer. Each bar is the average share of available points earned across the fifty cards. The bars near the bottom hold the most headroom.

Resilience3.9 of 5
79%
Authority premium6.6 of 10
66%
Action intent6.1 of 10
61%
Trust movement8.6 of 15
57%
Consideration5.3 of 10
53%
0%25%50%75%100%
Average share of available points, 50 US credit cards

30.4

Median base score across the fifty cards.

26.4

Lowest base score in the field.

35.4

Highest base score in the field.

Read it as

A directional estimate from a synthetic panel rather than a market result. Use it to choose which cards to test first, then measure real customer behaviour.

The model already exists

The leading card is the simplest one to read.

Citi Double Cash leads all fifty cards because its terms are simple, stated in one place, and easy to quote. Any card can be written that way.

01

A rewards card

One fact page carrying the earning rules, the redemption value, the transfer rules, and the conditions that change any of them. Dated, in plain sentences, on the bank's own domain.

02

A balance transfer card

One page carrying the intro period, the deadline, the fee, how purchases are treated, and two worked payoff examples. An assistant quotes a number that exists as a number.

03

Every other card

Same structure, same headings, same date stamp. A portfolio reads consistently to a machine when it is written consistently by people.

What to do

Give every card one fact page, written the same way.

The first quarter

Where to start.

Start with a flagship, a growth card, and one you already suspect reads badly. What works there becomes the standard for the rest.

Read the answers

Every assistant, every card in the set, with transcripts in front of the people who write the pages.

Publish the facts

One dated fact page per card. Current terms, plain conditions, written so a machine can quote them whole.

Read them again

Same questions, same assistants, one quarter later. What moved is the measure.

The ask

Approve the cards and the standard their pages will be written to.

A question worth asking

A quarter from now, which single number do you want to have moved, and by how much?

How we did this

How the study was run.

Read the results as a direction rather than a scoreboard. The specification was locked before collection began, and every figure traces back to a recorded answer.

01 Scope

Fifty open US consumer credit cards, across eight categories and twelve issuer brands.

02 Collection

Five assistants answered three card questions twice, in fresh sessions. Natural discovery added category visibility.

03 Evidence

Every card received a current first-party source package before scoring.

04 Review

The final audit covers 10,923 claims. Independent blind coding and adjudication resolved the determinate differences.

05 Trust Upside

A 5,000 agent synthetic panel produced at least 60,000 seeded assignments across three scenario bands.

06 Limits

AI Quality comes from observed answers. Trust Upside comes from a synthetic experiment and is a directional estimate only.

AI Representation Quality

Are the facts correct, current, complete, and credited to the bank, in the answer running today.

Trust Upside

Modelled change in trust, consideration, verification, and intended action if the evidence were clearer.

Bank source authority

How often the bank's own page is shown as the source for a claim about its own card.

The answer a customer reads is now part of the product.

It can be written as deliberately as the product itself. The Trust Transfer Index, August 2026, runs to 15 pages and is free to open.

Download the report