Digital platforms can algorithmically change rules, prices, and recommendations on a per-user, per-session basis, a practice called "twiddling." This leverages surveillance data to maximize extraction, such as raising prices on payday or offering lower wages to workers with high credit card debt, which was previously too labor-intensive for businesses to implement.

The company Anti-Fraud pioneers a "Snitching as a Service" model where it only earns revenue when its AI-powered investigations lead to government recovery from corporate fraud. This whistleblower-driven approach perfectly aligns incentives and provides a sustainable financial path for investigative journalism, an industry that has struggled with traditional advertising and subscription models.

Internal Meta documents show the company knowingly accepts that its scam-related ad revenue will lead to regulatory fines. However, it calculated that the profits from this fraud ($3.5B every six months from high-risk ads alone) 'almost certainly exceeds the cost of any regulatory settlement'.

Many social media and ad tech companies benefit financially from bot activity that inflates engagement and user counts. This perverse incentive means they are unlikely to solve the bot problem themselves, creating a need for independent, verifiable trust layers like blockchain.

After an internal team successfully slashed problematic ad revenue from China by 50%, Meta CEO Mark Zuckerberg personally intervened. Following his input, the effective anti-scam team was disbanded, as its success was negatively impacting the company's $18 billion in Chinese ad sales.

Meta is directly addressing the long-standing issue of low-quality leads from its ad platform. New verification options, including requiring a work email or SMS confirmation, allow advertisers to filter spam and unqualified submissions. This improves lead quality, reduces wasted spend, and makes the platform more viable for B2B and high-value campaigns.

Meta's core moat is its ability to solve the classic advertiser's dilemma: knowing which half of their ad spend works. By providing granular data on impressions, conversions, and ROI, it created what Pat Dorsey called the perfect advertising platform.

Internal Meta documents project that 10% of the company's total annual revenue, or $16 billion, comes from advertising for scams and banned goods. This reframes fraud not as a peripheral problem but as a significant, core component of Meta's advertising business model.

While 10% of Meta's revenue comes from fraud, the company's anti-fraud team was blocked from taking any action that would impact more than 0.15% of total revenue. This minuscule 'revenue guardrail' was an explicit internal directive to ensure anti-fraud efforts would not succeed.