The Deception Industry: How AI Turned Fraud Into a Market With Salaries, Pricing Models, and KPIs

There is an industry that has pricing plans, monthly subscriptions, HR departments, performance reviews, KPIs, and AI copilots. It generated more than $400 billion last year. It isn't Silicon Valley. It's global fraud. It has never been a small-scale operation. But AI removed the final barrier: what previously required a team of people with different skill sets (a linguist, a designer, a voice actor) is now sold as a subscription costing just a few dollars a month.In this piece, I’ll look at how AI has changed fraud, how this system works, discuss salaries for fraudsters, and share some thoughts on how to fight it. System of a Down Most large-scale fraud schemes are not run by lone hackers, but by entire factories. I often think back to the well-known example of Asian “scam compounds” that came into the spotlight in 2024. They grew out of casinos that had closed during the pandemic. Chinese criminal groups that had lost their gambling revenue repurposed hotels and casinos into fraud call centers when COVID swept across the world. The UN estimated the number of “employees” working in these compounds at 300,000 people, TIMES reports. Human rights activists say that many of them are victims of forced labor, lured there by fake job offers. And when I call it a corporation, I am not exaggerating. Researchers Mark Bo, Ivan Franceschini, and Lin Li describe these compounds in their 2025 book Scam as genuinely developed organizations: inside a “scam company,” there are cafeterias, clinics, and brothels; employees operate multiple phones at the same time from early morning until midnight, and failure to meet targets is punished with beatings. These companies use the same principle of division of labor as legitimate businesses. As the anti-fraud service, DeepIDV notes, instead of one criminal mastering document forgery, biometric bypass, and money laundering, each specialist focuses on a specific niche and sells that service on the open market. Inside these fraud corporations, workers actively use modern technologies to meet the KPIs set by their employers. In the age of AI, criminal groups obviously could not ignore technologies that became available so cheaply. Fraudsters use deepfakes to “carry out social engineering schemes with frighteningly high efficiency, exploiting people’s trust and emotions,” according to a report by the UN Office on Drugs and Crime. CSIS writes that between 2022 and 2023, the number of deepfake-related fraud cases in the Asia-Pacific region increased by 1,530 percent. Fraudsters use deepfakes for fake investment campaigns, create pornographic material, and also steal other people’s identities - usually those of influential individuals - exploiting their reputation to commit crimes. The Industry Price List: What Everything Costs The market for fraud tools is structured much like the legitimate SaaS market: subscriptions, pricing tiers, and customer support on Telegram. Deepfakes and Synthetic Identities According to Group-IB, a synthetic identity package - an AI-generated face, a cloned voice sample, and forged documents - sells on underground marketplaces for around $5. A subscription to an "uncensored" language model for generating scam scripts costs about $30 per month. More advanced LLM-based fraud tools, such as FraudGPT and WormGPT - versions of language models with their safety guardrails removed - are sold on a subscription basis for $200-1,700 per month. Verification Bypass There is also a service in which a live operator uses a deepfake face swap to pass biometric verification on behalf of a client. The cost ranges from $100 to $500 per successful attempt. A fully verified account with a fintech service or bank costs anywhere from $200 to more than $2,000, depending on the institution the profile is created for. Phishing Ready-made phishing kits are often distributed for free. The menu also includes templates for fake online stores, priced between $5 and $50, while more advanced adversary-in-the-middle kits for bypassing two-factor authentication, such as Tycoon 2FA, cost $120 for 10 days or $350 per month. At its peak, this malware was used in attacks targeting more than 500,000 organizations per month, until Microsoft and Europol carried out a coordinated takedown of 330 domains in March 2026. What else? There are also subscriptions offered under the Fraud-as-a-Service model. Entry-level access costs around $50 per month, providing access to phishing kits, databases of stolen credentials, and bot infrastructure. Salaries in the Legitimate AI Market vs. "Salaries" in Scam Factories Paradoxically, recruiters for scam compounds use the language of the ordinary job market: victims are lured in with ads promising "easy work with a high salary" for positions in IT, programming, and customer support. For example, Shuaibu, a 24-year-old Ugandan, was promised $850 a month for a courier job, while Malik, from Pakistan, expected to earn $1,200 a month in an IT position. Both ended up in locked scam compounds, where failing to meet daily quotas (for example, five new contacts per day) was punished with fines, beatings, or electric shocks. The price of buying back one's freedom typically exceeds $50,000. The return on investment is equally striking. According to Chainalysis, AI-enabled cryptocurrency fraud generates an average of $3.2 million per operation - 4.5 times more than traditional fraud schemes that do not use AI. Jobs Inside the Fraud Economy – and the Layoff Paradox This economy has its own professional hierarchy, one that almost perfectly mirrors the structure of a legitimate company. Recruiters lure victims with fake job postings, "lead generators" are responsible for making first contact with potential victims, and "closers" specialize in building trust and persuading victims to transfer money. There are team leads with revenue-based KPIs, IT specialists who maintain the infrastructure, and deepfake operators responsible for voice and video calls. This is where the central paradox emerges. On the one hand, the legitimate job market is undergoing layoffs driven by automation: routine tasks, call centers, and document processing are all increasingly being taken over by AI. On the other hand, that same AI is creating demand for labor in the underground fraud economy. It is entirely possible that some of this demand is being filled by people who have been displaced from legitimate industries by automation. Interestingly, recruiters for scam compounds deliberately target not low-skilled workers, but educated people with backgrounds in IT and customer service – the very same group of professionals that is most vulnerable to automation in the legitimate economy. At the same time, as Fortune notes, some researchers believe AI will soon replace people inside the compounds themselves. Chatbots are already capable of carrying on conversations with victims in dozens of languages without any human involvement, while compound bosses use AI tools to monitor and control the workers themselves. Experian already describes "agentic AI fraud" – fully automated attacks that require no human involvement at any stage, from identifying a victim to cashing out the stolen funds – as one of the leading new threats of 2026. In other words, AI isn't just changing the labor market "somewhere out there." It is simultaneously pushing people out of legitimate employment, creating a shadow labor market for them, and then beginning to automate that market as well. So What Do We Do About It? AI-powered fraud is not a collection of isolated incidents – it is a system. Behind a single scam call, there is often a $30 subscription to a deepfake service, a $5 synthetic identity package, a script generated by an unrestricted language model, and an operator in a scam compound trying to hit a daily quota under the threat of punishment. It is an assembly line, not an isolated event. The practical conclusion is that we need to respond not to individual scams, but to the infrastructure that produces them – from data centers and telecom providers to payment gateways and cryptocurrency exchanges through which the money is laundered. This is already the approach taken by major law enforcement operations. For example, in May 2026, Europol launched the EU Anti-Scam Platform precisely because it had come to view fraud-as-a-service as a form of infrastructure-based organized crime rather than a collection of isolated offenders. Personally, I have also made fighting fraud at the systemic level my mission, and I am developing a free solution that prevents AI fraud in the users’ communication channels such as messengers and emails. AI has made fraud far more effective, so we need equally effective AI-based systems to defend ourselves.