Streaming fraud is a $2B industry, and the tactics keep spreading

People blame the DSPs first. “Why don’t they just ban the artist?” They do. The bad actor comes back with a new name and a new account.

That’s the tell. Streaming fraud is not a few rogue uploads. It’s an industry now, worth more than £2 billion a year. The people running it learn faster than the systems built to stop them. They steal royalties, and they wreck trust across the supply chain.

Here’s the game as I keep seeing it.

What streaming fraud looks like

• Upload stolen or unlicensed tracks as their own
• Re-upload the same track under different names or metadata
• Use bots or click-farms to inflate streams
• Run ads that mislead users into fake plays
• Create soundalike songs to hijack search traffic
• Copy artist names to siphon fans
• Stuff track titles with trending keywords
• Upload covers or remixes without licenses
• Disguise copyrighted samples as originals
• Exploit public-domain works with misleading metadata
• Loop short audio files to maximise streams
• Split one track into multiple files to game payouts
• Create fake artist profiles to spread uploads
• Use stolen or generated identities to open distributor accounts
• Launder royalties through fake plays and shell labels
• Hijack ISRCs to redirect revenue
• Exploit distributor loopholes to mass-upload spam
• Sell playlist placements backed by botted streams
• Use VPN farms to simulate fanbases
• Embed inaudible audio in white-noise playlists

That’s the surface.

Each of those tactics cuts artist income and chips away at platform credibility.

How music distributors can fight back

Fraud detection is not about blocking uploads. It’s about seeing patterns most humans can’t see without tools.

Start here.

1. Strengthen verification at the door

Automated KYC is not enough. Vet new labels and artists the way a bank would. Digital footprints, linked socials, distributor histories.

2. Analyse behaviour, not just content

Upload timing, release volume, IP reuse, overlapping bank details. Fraud networks work in teams, often under VPNs, and they repeat themselves.

3. Fingerprint the audio and cluster the metadata

Catch near-identical tracks, duplicate ISRCs, and soundalikes that slip past a manual review.

4. Audit the catalogue

Fraudulent uploads can sit for years. Pick a label, pick a random release, investigate. See what you find.

5. Work across distributors

Fraudsters hop platforms. Shared watchlists, blacklists, and hashed identifiers catch repeat offenders. Hard at scale. Still essential. That’s the problem Groovian is built to solve.

The real gap is infrastructure. Fragmented, outdated, easy to manipulate. Metadata, companies, and labels keep drifting further apart.

Every distributor, from a small independent to a major aggregator, has to treat fraud prevention like cybersecurity: continuous, layered, adaptive.

The fraudsters already do.