What is streaming fraud?

Steaming fraud refers to manipulative tactics that artificially inflate streaming metrics such as views, plays, and engagements on digital content platforms for streaming music, video, or live-streaming.
 
Fraudsters exploit these platforms to generate illegitimate revenue by manipulating content rankings and deceiving advertisers and consumers about the popularity of a piece of content.

Streaming fraud typically involves the use of automated bots, scripts, or fake accounts to repeatedly play or engage with digital content and skew metrics. Fraudsters fake streams to inflate plays for songs, videos, or broadcasts, and manipulate performance metrics, royalties, and advertising payouts. This fraudulent practice also distorts the real value and popularity of the content. Fraudsters sometimes get paid by presenting themselves as marketers or affiliate partners to an artist asking for money in exchange for plays.

Streaming fraud takes many forms, leveraging both automated systems and human efforts to manipulate metrics, inflate content popularity, and generate illegitimate revenue. Common models of streaming fraud include:

• Bots and Automation: Bad actors use bots to inflate content plays, boost metrics tied to payouts, or manipulate rankings. Bots may also register and control fake accounts to stream specific content.
• Streaming Manipulation Services: Paid services artificially boost views, listens, or engagement for a fee, often targeting creators or marketers seeking rapid growth.
• Fake Accounts: Bots create and control fake user accounts to generate streams or engagement, inflating metrics for specific songs, videos, or playlists.
• Account Takeover (Hijacking): Hackers take control of real user accounts to manipulate streams, diverting legitimate engagement to target content.
• Playlist Manipulation: Fraudsters infiltrate high-visibility playlists to prioritize specific content, distorting its organic reach and popularity.
• Botnets: Networks of automated bots repeatedly play content, generating large volumes of fake streams.
• Click Farms: Real operators manually access content repeatedly to simulate authentic engagement, often for bulk fraudulent streaming.

Streaming fraud inflates the value of content by inflating its user interaction metrics, unfairly distributes royalties, and distorts the ranking and recommendation systems on media platforms. The result harms legitimate content creators who lose out on earnings and visibility, as well as the overall credibility of streaming platforms. 

Streaming fraud also hinders the effectiveness of streaming ads, as bots using fake or existing accounts to stream music, for example, are also served advertisements. This results in wasted ad spend and ineffective campaigns, as a percentage of the advertisements were not actually viewed by humans.

Streaming platforms fight streaming fraud by using detection systems powered by AI, auditing playback data, and enforcing stricter user verification processes. Streaming platforms also monitor unusual patterns and take down suspicious content or accounts. The complexity of real-time detection poses a significant challenge to the integrity of content metrics, however, as fraud tactics constantly evolve. 

Striking the proper balance between fraud prevention and user experience ensures fairer distribution of revenue and enhanced trust in the streaming platform metrics.

As streaming fraud has different ways to infiltrate, HUMAN offers different ways to interfere with this fraud. The Account Takeover solution uses machine learning to parse suspicious login attempts, while the Compromised Accounts solution monitors stolen credentials to identify future targets. Ad Fraud Sensor identifies suspicious advertising analytics to keep data clean and reassure ad partners. 

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