{
  "id": 18161,
  "title": "Mastercard spent decades training its fraud system to see bots as thieves. Now bots are the ones doing the buying.",
  "url": "https://urgent.news/2026/07/30/mastercard-spent-decades-training-its-fraud-system-to-see-bots-as",
  "topic": "world",
  "section": "World",
  "published": "2026-07-30T16:57:14.000Z",
  "source": {
    "name": "VentureBeat",
    "slug": "venturebeat",
    "url": "https://venturebeat.com/security/mastercard-spent-decades-training-its-fraud-system-to-see-bots-as-thieves-now-bots-are-the-ones-doing-the-buying"
  },
  "original_language": "en",
  "account": "Mastercard has spent decades perfecting its fraud detection system, which can analyze 175 billion transactions per year in under 100 milliseconds. However, with the rise of generative AI, the company is now faced with the challenge of enabling bots to make purchases while maintaining security and preventing fraud. Greg Ulrich, Mastercard's chief AI and data officer, explained that the company has had to modify its risk framework and rules to accommodate this new reality. The company's Safety Net system has already stopped over 70 billion fraudulent transactions, and Mastercard is building its own transformer model on its transaction data to power new safety, security, and personalization solutions. The stakes extend beyond merely preventing fraud, as about 40% of Mastercard's business is now based on services, including AI-driven fraud and security solutions. As agentic commerce grows, with more agents delegating authority on behalf of consumers and businesses, trust becomes increasingly crucial. Mastercard has built five layers of security to address these challenges: identity verification, verifiable intent, controls, execution through Agent Pay, and intelligence spanning risk rules, insights, and monitoring. The ultimate goal is to enable agentic commerce, such as automated procurement agents managing inventory and supplier relationships. To achieve this, Mastercard must establish clear standards for identity, intent, and communication across various parties, ensuring a robust trust infrastructure for autonomous transactions.",
  "summary": "Every time a Mastercard gets tapped, the network has less than a tenth of a second to judge how likely the purchase is to be fraudulent. It made that call across 175 billion transactions last year. Now the buyer on the other side of that judgment is starting to change, and Greg Ulrich, the company's chief AI and data officer, spelled out the consequence for the VB Transform 2026 audience in Menlo…",
  "key_points": [
    "Mastercard perfected fraud detection system analyzing 175B transactions/year",
    "Bots now making purchases, posing new security challenge",
    "Mastercard building transformer model for safety and personalization"
  ],
  "editors_take": null,
  "illustration": null,
  "coverage": {
    "outlets": 1,
    "also_reported_by": []
  },
  "ai_generated": true,
  "disclaimer": "Summaries, key points and the editor’s take are written by software from other outlets’ reporting and may contain errors — always check the linked original."
}