# How Airvantage uses H2O.ai

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

- Company: [Airvantage](https://www.usedby.ai/companies/airvantage.md)
- Tool: [H2O.ai](https://www.usedby.ai/tools/h2o-ai.md)

## What the story says

Airvantage uses H2O Driverless AI to build a machine learning model that scores airtime-advance credit risk for prepaid telecom subscribers in real time. It replaced a static rules-based scoring engine and re-evaluates customers the old rules had rejected.

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

> Its static, rules-based scoring was overly defensive, turning away creditworthy customers, so the team evaluated more than 30 toolkits, ran POCs with four platforms, and chose H2O Driverless AI.

> With H2O Driverless AI's MOJO technology, we are able to integrate strongly with our current infrastructure.
>
> Maram Mishan, Actuarial Data Scientist

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

## What usedby checked

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

- Checked: the passage quoted above is copied word for word from the page, near the name of Airvantage.
- Checked: Airvantage 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/airvantage-h2o-ai · How we check: https://www.usedby.ai/methodology