# How Capital One uses H2O.ai

**5,000** Mobile logins monitored per minute

As published on [h2o.ai](https://h2o.ai/case-studies/capital-one-h2o). Captured by usedby on 2026-10-17.

- Company: [Capital One](https://www.usedby.ai/companies/capital-one.md)
- Tool: [H2O.ai](https://www.usedby.ai/tools/h2o-ai.md)
- Industry: [Banking & Mortgages](https://www.usedby.ai/companies/industry/banking-mortgages.md)
- Teams: Operations, Incident response

## What the story says

Capital One's operations team uses H2O Sparkling Water and H2O-3 to forecast normal mobile app login volume and flag anomalies in real time. The models replaced fixed thresholds and alert the incident response team when traffic deviates from the forecast.

Summary written by usedby from the source page, in English. The figures are those of H2O.ai and Capital One, not ours.

> In one case, a spike of more than 20,000 unexpected logins at 11:15pm triggered an anomaly alert that reached the incident response team at 11:17pm, four minutes before any other alarm.

- **20,000**: “a spike of more than 20,000 unexpected logins at 11:15pm triggered an anomaly alert”

> This was a huge win for our customers, and for the teams who are responding to these types of incidents
>
> Donald Gennetten, data engineer at Capital One

Source: [h2o.ai](https://h2o.ai/case-studies/capital-one-h2o), captured 2026-10-17.

## What usedby checked

We compared the story with its live page on 2026-10-17.

- Checked: the figure 5,000 is on the page; its label is our wording.
- Checked: the passage quoted above is copied word for word from the page, near the name of Capital One.
- Checked: each number in our summary is printed on the page.
- Checked: Capital One uses H2O.ai. Confirmed line. Latest check across sources: 2026-10-17.
- Not checked: the result itself. We quote it; we did not measure it.

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Source: https://www.usedby.ai/case-studies/capital-one-h2o-ai · How we check: https://www.usedby.ai/methodology