This piece is in the research pipeline. The thesis and the questions we are answering are below. The fully-drafted article will publish when the Office has finished working through the literature. Subscribe via the contact form to be notified when it lands.
- Thesis
The argument.
Streaming counts are only the first layer of fraud screening. This paper walks through the multi-layer methodology - geographic clustering, device fingerprinting, playlist velocity, listener retention curves, royalty-to-play ratio anomalies - and explains why any single layer is insufficient. The "manufactured chart week" is a recognisable pattern; the methodology to identify it is shareable.
- Research questions
What we are answering.
What techniques do streaming fraud operators currently use (2024-2026)?
What does academic and industry literature say about bot screening methods in audio streaming?
How have DSPs (Spotify, Apple Music, Amazon) responded publicly to fraud - what screening do they claim to run?
Are there published incident reports or investigations into specific fraud campaigns?
What is the estimated financial scale of streaming fraud globally?
What multi-layer screening approaches are documented in fraud screening literature (not necessarily music-specific)?
- Tone & format
How it will read.
Technical and authoritative. Audience is label ops or DSP trust-and-safety. Reads like an internal methodology paper made public.
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