Fraud Risk

Fraud risk refers to the danger that AI systems will be manipulated or misused to commit or enable fraudulent activities, such as deepfakes for identity theft, synthetic transaction data to hide money laundering, or automated schemes to file false insurance claims. Organizations need to address this because fraudsters often adopt new tools faster than defenses catch up, and AI-powered fraud can scale quickly across millions of customers before detection. Governance frameworks should require fraud risk assessments during AI development, monitoring for suspicious patterns in model outputs, and controls to prevent unauthorized use of generative capabilities like voice or image synthesis.

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ResearchUS2026-09-27

AI Billing Tools Added $942M in Unwarranted Healthcare Costs, Insurer Study Finds

A Blue Cross Blue Shield Association analysis found that hospitals using AI tools during insurance claim submission generated an extra $942 million in healthcare spending over two years. The analysis identified a surge in patients documented as having complex conditions, but found no corresponding change in actual care delivered. The finding signals that AI-assisted medical coding is inflating claims without clinical justification.

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