Nbh Bank Appears in 0.0% of AI Answers. Here's Our Five-Step Plan to Improve Its AI Visibility.

Mark HuntleyBy Mark HuntleyFounder and CEO
11 minutes read

Key Takeaways

  • Nbh Bank had 0 mentions and 0 recommendations across 165 benchmark answers for business checking accounts.
  • The first verified monthly record is a baseline, with no prior month available for comparison.
  • The plan starts with fact verification, then moves to page consistency, external source review, and priority page briefs.
  • Buyer-question content should be based on the bank’s own sales and support conversations, not on the benchmark alone.

Answer Capsule

In November 2026, Nbh Bank appeared in 0 of 165 AI answers included in the Business Checking Accounts benchmark (0.00%). It received 0 recommendations (0.00%), with 0 Top 3 placements and 0 first-place recommendations. A mention means the company appeared in an answer; a recommendation means the answer affirmatively endorsed it.

Our plan compares the company with its competitors, checks conflicting AI claims against reliable sources, and identifies website pages, third-party sources and buyer questions to address. The historical results show how the figures changed across available months. Different monthly samples limit those comparisons, and conflicting AI claims require verification before corrections are proposed.

Current AI visibility

Questions This Section Answers

  • How do Nbh Bank mentions, recommendations and placements compare with its Business Checking Accounts peers?

Nbh Bank recorded 0 mentions (0.00%) and 0 recommendations (0.00%) across 165 answers included in the benchmark. Top 3 placements numbered 0; first-place recommendations numbered 0. Framing among its mentions was 0 positive, 0 neutral and 0 negative.

Rank

Company

Mentions

Mention rate

Recommendations

Recommendation rate

Top 3

Top 3 rate

#1

#1 rate

1

Bluevine

126

76.36%

106

64.24%

84

50.91%

74

44.85%

2

Mercury

121

73.33%

98

59.39%

63

38.18%

6

3.64%

3

Relay

122

73.94%

90

54.55%

58

35.15%

4

2.42%

4

Found

92

55.76%

61

36.97%

15

9.09%

1

0.61%

5

U.S. Bancorp

82

49.70%

43

26.06%

15

9.09%

2

1.21%

6

Axos Bank

47

28.48%

34

20.61%

12

7.27%

2

1.21%

7

Bank of America Corp.

66

40.00%

17

10.30%

4

2.42%

0

0.00%

8

Chase Credit Journey

95

57.58%

9

5.45%

5

3.03%

2

1.21%

9

PNC Bank

30

18.18%

7

4.24%

1

0.61%

0

0.00%

10

Varo Bank

11

6.67%

5

3.03%

2

1.21%

1

0.61%

10

Wells Fargo & Co.

36

21.82%

5

3.03%

0

0.00%

0

0.00%

12

Citi

24

14.55%

3

1.82%

3

1.82%

0

0.00%

12

Truist Bank

19

11.52%

3

1.82%

1

0.61%

1

0.61%

14

Citizens Bank & Trust

2

1.21%

1

0.61%

0

0.00%

0

0.00%

14

Current

58

35.15%

1

0.61%

1

0.61%

0

0.00%

16

Align Credit Union

0

0.00%

0

0.00%

0

0.00%

0

0.00%

16

Autobooks

0

0.00%

0

0.00%

0

0.00%

0

0.00%

16

Baker Boyer Bank

0

0.00%

0

0.00%

0

0.00%

0

0.00%

16

Bank Of The West

1

0.61%

0

0.00%

0

0.00%

0

0.00%

16

Banknewport

0

0.00%

0

0.00%

0

0.00%

0

0.00%

16

Baselane

2

1.21%

0

0.00%

0

0.00%

0

0.00%

16

Candescent

0

0.00%

0

0.00%

0

0.00%

0

0.00%

16

Capital One Platinum Mastercard

3

1.82%

0

0.00%

0

0.00%

0

0.00%

16

Carroll Bank And Trust

0

0.00%

0

0.00%

0

0.00%

0

0.00%

16

Centime

0

0.00%

0

0.00%

0

0.00%

0

0.00%

16

Clear Mountain Bank

0

0.00%

0

0.00%

0

0.00%

0

0.00%

16

Codat

0

0.00%

0

0.00%

0

0.00%

0

0.00%

16

Field & Main Bank

0

0.00%

0

0.00%

0

0.00%

0

0.00%

16

First Bank Of Berne

0

0.00%

0

0.00%

0

0.00%

0

0.00%

16

First County Bank

0

0.00%

0

0.00%

0

0.00%

0

0.00%

16

First Federal Bank

0

0.00%

0

0.00%

0

0.00%

0

0.00%

16

First Security Bank Of Missoula

0

0.00%

0

0.00%

0

0.00%

0

0.00%

16

Five Star Bank

0

0.00%

0

0.00%

0

0.00%

0

0.00%

16

Fps Gold

0

0.00%

0

0.00%

0

0.00%

0

0.00%

16

Hanmi Bank

0

0.00%

0

0.00%

0

0.00%

0

0.00%

16

Ixonia Bank

0

0.00%

0

0.00%

0

0.00%

0

0.00%

16

Mainstreet Bank

0

0.00%

0

0.00%

0

0.00%

0

0.00%

16

Merchant's Pact

0

0.00%

0

0.00%

0

0.00%

0

0.00%

16

Merrimack County Savings Bank (the Merrimack)

0

0.00%

0

0.00%

0

0.00%

0

0.00%

16

Mid Penn Bank

0

0.00%

0

0.00%

0

0.00%

0

0.00%

16

Mid-missouri Bank

0

0.00%

0

0.00%

0

0.00%

0

0.00%

16

Mountainone

0

0.00%

0

0.00%

0

0.00%

0

0.00%

16

Nbh Bank

0

0.00%

0

0.00%

0

0.00%

0

0.00%

16

North Valley Bank Ohio

0

0.00%

0

0.00%

0

0.00%

0

0.00%

16

Northwest Community Bank

0

0.00%

0

0.00%

0

0.00%

0

0.00%

16

Outdoor Bank

0

0.00%

0

0.00%

0

0.00%

0

0.00%

16

Progressive Ozark Bank

0

0.00%

0

0.00%

0

0.00%

0

0.00%

16

Sanibel Captiva Community Bank

0

0.00%

0

0.00%

0

0.00%

0

0.00%

16

Susser Bank

0

0.00%

0

0.00%

0

0.00%

0

0.00%

16

United Federal Credit Union

0

0.00%

0

0.00%

0

0.00%

0

0.00%

16

West Gate Bank

0

0.00%

0

0.00%

0

0.00%

0

0.00%

Nbh Bank does not appear in any of the answers reviewed for this benchmark, so there is no recommendation record to improve yet. The absence is the finding: the bank is not part of the set of business checking providers these answers discuss at all.

That matters because the names that do appear are the ones a buyer would hear when asking an AI assistant for a checking account. Before chasing placement, the bank needs to understand which questions it is missing from and whether its own materials give an assistant anything to work with.

We would start by mapping the questions where the bank is absent and comparing them with the questions where it is present. That gives a realistic starting point rather than a target pulled from competitors' numbers.

What changed since last month

Questions This Section Answers

  • How did Nbh Bank counts and coverage differ across the available monthly snapshots?

Metric

Nov 2026

Mentions

0 / 165 (0.00%)

Recommendations

0 / 165 (0.00%)

Top 3 recommendations

0 / 165 (0.00%)

#1 recommendations

0 / 165 (0.00%)

Only months with verified results are shown. Monthly sample coverage is listed in Methodology.

There are insufficient usable monthly observations for a prior-period comparison.

This is the first verified monthly record for Nbh Bank, and it shows no mentions and no recommendations. There is no earlier month with usable observations, so nothing here can be described as a rise, a fall or a trend.

The wider benchmark history covers different company sets in earlier months, which is why those months are excluded from this comparison. The sample of answers also differs between months, so even where figures exist they are separate selected samples rather than a continuous series.

For the client, the practical reading is simple: this month is a baseline, not a verdict. We would treat it as the reference point against which later months are read, with the comparability limits stated alongside any movement.

AI recommendation trend

Observed recommendation rate (%), Nov 2026

  • Nbh Bankno change
    Nov 20260.00%

Separate selected monthly samples. Missing points are unavailable, not zero. Provider/prompt equivalence is unverified; rate movement does not demonstrate causation.

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Step 1. Measure

Questions This Section Answers

  • What should the agency measure and verify first for Nbh Bank?

AI answers contained 0 conflicting claims about Nbh Bank: 0 critical, 0 high, 0 medium, 0 low. Of these, 0 were rated critical or high priority; the critical claims are included in that total. These ratings help prioritize fact-checking. They do not establish that a company or publisher made an error.

With no conflicting claims recorded about Nbh Bank, there is nothing to correct and nothing to defend. That is a quieter starting position than it sounds, because it also means the answers contain no verified description of the bank to build on.

A visibility comparison would show which questions the bank could reasonably enter and which belong to other kinds of providers. A short list of claims worth checking would confirm what the bank actually offers before any content is written.

We would propose a baseline scorecard and a scoped fact-review list, each entry with an owner and a source requirement, so later work rests on confirmed facts rather than assumptions.

Step 2. Make the website consistent

Questions This Section Answers

  • Which recorded claim differences about Nbh Bank should be verified before proposed page edits?

No results are available for this part of the analysis.

Both columns quote AI answers, not verified company facts. Resolve the entity, date and source before deciding whether a correction is warranted; different dates can explain an apparent conflict.

No disputed topics were supplied for this part of the analysis, so there is no claim to adjudicate and no page to rewrite on that basis. The honest position is that consistency work cannot begin until there is something specific to check.

Where claims do surface later, the first step is to resolve the entity, the date and the source. An apparent conflict can come from two different dates or two different institutions sharing a similar name, and neither warrants a correction.

We would propose conditional page briefs: drafted only after the bank confirms the underlying facts, and only for pages the bank actually controls. Ambiguous matches would stay out of the correction queue.

Step 3. Align the external narrative

Questions This Section Answers

  • Which cited third-party pages are relevant to fact review for Nbh Bank?

No results are available for this part of the analysis.

These pages were selected because they relate to the company in the captured answers. Their current contents still need checking before any correction request. A page linked to a conflicting claim is not necessarily its cause, and the same answer may contribute to more than one row.

No external pages were selected for review in this analysis, so there is no publisher list to work from and no correction request to justify. That absence should not be read as evidence that outside sources are accurate or inaccurate about the bank.

When pages are identified, each one needs its current contents checked against primary sources before any request is made. A page that appears alongside a claim is not necessarily the cause of it, and a citation does not show that a source shaped an answer.

We would propose a source review that separates confirmed edits, no-change decisions, outgoing requests and responses, so the bank can see what was asked and what came back.

Step 4. Optimize priority company pages

Questions This Section Answers

  • Which observed Nbh Bank website pages should receive review briefs?

No results are available for this part of the analysis.

The company's website was cited 0 times across 0 distinct page addresses; the table shows 0 pages selected for review. Zeros in the answer columns mean no matching answers were recorded. A cited page is not automatically a page that accompanied a recommendation.

The bank's website was not cited in the answers reviewed, and no pages were selected for review. That means there is no page-level evidence yet about which of the bank's own pages assistants draw on, if any.

Page briefs would therefore start from approved facts and the questions buyers actually ask, not from guesses about what a page currently says. A cited page would not automatically be treated as one that produced a recommendation.

We would propose briefs for a small set of priority pages, each tied to confirmed product details and reviewed by the bank before publication.

Step 5. Publish around buyer questions

Questions This Section Answers

  • Which observed buyer questions support content briefs for Nbh Bank?

No results are available for this part of the analysis.

These are recorded answer observations, not search volume, verified demand, or proof of missing website content.

No buyer questions were recorded for this analysis, so there is no observed question set to turn into content briefs. The questions buyers ask about business checking are still worth planning around, but they need to come from the bank's own sales conversations and support enquiries rather than from this report.

Recorded answer observations are not search volume, verified demand or proof that a page is missing. A question appearing in an answer does not by itself justify a new page.

We would propose checking existing coverage first, then drafting buyer-question content only where a genuine gap is confirmed.

Our 90-day action plan

Questions This Section Answers

  • How should the agency sequence the proposed Nbh Bank work and judge completion?

Period

Deliverable

Completion criterion

Days 1–30

Baseline scorecard, scoped fact-review register and page/source shortlist

Each record has an owner, evidence requirement and review status

Days 31–60

Approved page briefs and justified publisher requests

Separate confirmed edits, no-change decisions, requests and responses

Days 61–90

Buyer-content briefs and a fresh scorecard

Record work completed separately from measured answer outcomes and comparability limits

The first month is for establishing a baseline scorecard, a scoped fact-review list and a shortlist of pages and sources, each with an owner and a review status. Nothing in that stage depends on the bank appearing in answers.

The middle month turns confirmed facts into approved page briefs and justified publisher requests, with confirmed edits, no-change decisions, requests and responses recorded separately. The final month adds buyer-content briefs and a fresh scorecard.

Delivered work is recorded separately from measured answer outcomes. Completing a brief or sending a request does not establish that visibility changed, and the report will keep those two things apart.

Methodology

Questions This Section Answers

  • How are Nbh Bank answer metrics and citation populations defined?

This report covers 2026-11. The exact dates when the original AI answers were collected have not been verified. The visibility rates use 165 answers that met the benchmark's inclusion rules. A company is recommended only when the answer both endorses it and uses positive wording. Top 3 and first-place counts are part of those recommendations, not extra recommendations.

An answer can mention or recommend several companies, so company counts cannot be added to find the number of distinct answers. The net sentiment score is positive minus negative mentions, divided by all company mentions; it describes answer wording, not customer satisfaction.

The wider citation analysis covers 800 captured answers and 5565 appearances of cited URLs. Citation appearances across all captured answers differ from the number of benchmark answers citing a page and the number that also recommend a company. The current contents of cited pages and disputed company claims still need independent verification.

Monthly sample coverage:

Reporting month

Answers included

AI services covered

Services

Nov 2026

165

6

ChatGPT, Copilot, Gemini, Google AI Mode, Google AI Overviews, Perplexity

July 2026 measured a different set of companies, so it is excluded from this comparison. August 2026 measured a different set of companies, so it is excluded from this comparison. September 2026 measured a different set of companies, so it is excluded from this comparison. October 2026 measured a different set of companies, so it is excluded from this comparison.

The answer samples differ between months. These comparisons show how the recorded results changed; they do not establish why they changed.

This report covers a single month, and the exact dates when the original answers were collected have not been verified. The visibility figures rest on answers that met the benchmark's inclusion rules, and an answer can mention or recommend several companies, so company counts cannot be added to find a number of distinct answers.

A recommendation requires both an endorsement and positive wording. Top-three and first-place counts sit inside recommendations rather than adding to them. The wider citation analysis covers a larger set of captured answers and is not the same measure as the benchmark.

Monthly samples differ, and comparisons show how recorded results changed, not why.

Our first three priorities

First, confirm the facts. Before any content or outreach, the bank should verify its business checking details against primary sources so that briefs and any later correction requests rest on confirmed information rather than on assumptions.

Second, build the baseline. A scorecard that records which questions the bank appears in, and which it does not, gives the next few months something concrete to compare against, with the sample limits stated alongside it.

Third, prepare buyer-question content from the bank's own sales and support conversations, checking existing pages before proposing anything new. These three steps are proposed work, not measured outcomes, and none of them guarantees a change in how assistants describe the bank.

/ Learn More

Understanding AI search visibility.

AI search experiences create answers by pulling information from many places online and summarizing it into a single response.

What Is AI Citation Intelligence?
AI citation intelligence is the process of measuring where AI platforms source their information and how frequently a brand is mentioned or referenced in AI-generated responses. Because LLMs synthesize across multiple sources, the sites and brands that appear repeatedly tend to influence how a topic or company is framed. This practice focuses on identifying which sources shape AI outputs and tracking brand visibility across different AI systems.
What Is Citation Architecture?
Citation architecture describes the set of sources that consistently inform how AI systems talk about a brand, product, or topic. LLMs draw from websites, articles, forums, and public discussion, and the sources they rely on most often become the backbone of their answers. Building strong citation architecture means ensuring that accurate, credible, high authority sources are the ones most likely to shape the way AI tools summarize and recommend a brand.
What Is Generative Engine Optimization?
Generative engine optimization (GEO) is the practice of improving the chances that AI systems use and cite your brand or content when generating answers. While traditional SEO is centered on ranking pages in search results, GEO focuses on how LLMs retrieve, interpret, and combine information when responding to a question. The objective is to strengthen the content and sources AI systems rely on, so your brand is treated as a trusted reference in AI responses.
What Is AI Share of Voice?
AI share of voice tracks how often a brand appears in AI-generated answers compared with competitors in the same category. It reflects visibility across AI platforms such as ChatGPT, Gemini, Claude, and Perplexity. Monitoring AI share of voice helps organizations see whether AI systems consistently include and recommend their brand for key queries or whether competitor brands are showing up more often.

About The Author

Mark Huntley

Mark Huntley

Founder and CEO

Mark Huntley, J.D. is founder of CiteWorks Studio, a strategic advisory focused on visibility, authority, and recommendation presence in AI-shaped search environments. His work centers on embedding-level GEO, vector optimization, and cosine gap engineering — helping brands align their digital presence with the retrieval systems that increasingly shape discovery, interpretation, and choice.

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