What is one of the main strategies employed by anti-fraud bureaus?

Utilizing data analysis for fraud detection is a key strategy employed by anti-fraud bureaus because it allows them to identify patterns and anomalies that may indicate fraudulent activity. Through advanced analytics and algorithms, these bureaus can sift through vast amounts of data from various sources, including claims history, provider information, and even social media activity. By pinpointing inconsistencies or unusual behaviors, they can flag potential fraud cases for further investigation, enabling a more proactive approach to combating insurance fraud. This strategy not only helps in detecting fraud but also serves as a deterrent, as potential fraudsters become aware that sophisticated methods are in place to monitor and analyze claims.

The other options do not directly contribute to the primary goal of fraud detection and prevention. Reducing insurance coverage options or limiting consumer claims may affect customer satisfaction and businesses' market competitiveness rather than effectively combating fraud. Similarly, increasing policy costs for all customers could lead to loss of clientele without addressing the root cause of fraudulent activities.