Adversarial Customer Service D
AI benchmark · Agentic
What is Adversarial Customer Service?
Measures whether a model acting as a bank support agent can distinguish genuine customers from identity thieves through conversation and help or refuse accordingly, in a two-sided adversarial game.
Security mostly
“This benchmark is a two-sided security game”
x.com/kaggle/status/2090530325747450054 ↗“one model plays a bank's support agent holding customer records and a verification policy”
x.com/kaggle/status/2090530325747450054 ↗“one model plays a bank's support agent holding customer records and a verification policy”
x.com/kaggle/status/2090530325747450054 ↗
Who built Adversarial Customer Service
Led by Kaggle with Gert Labs.
Tier D
Long tail: little or no usage data yet.
How much stands behind a tier: usage, who backs it, a confirmed line from its own site or paper, and a clear read on X. High with three of the four, medium with two, low otherwise.
- no usage data
- in curated RL directories (1 pt)
How we got to tier D
- Adoption: no usage data. Tier D.
- Not yet read on X.
- In curated RL directories: 1 point, a floor of none.
- Confirmed: a line from its own site or paper places it.
A clear view on X moves a tier one step up or down; most entries don't move. How tiers work.
Where Adversarial Customer Service sits
Its domain on the map, live. Hover a logo for its name; click to open it. Open it on the full map
Next: browse all benchmarks. Entry from the RL Research daily scrape of public sources, 2026-10-21 snapshot.