Detection and prevention of digital fraud

Utilizes technologies for detecting and preventing fraudulent insurance cases.

Implemented functionality:

• Integration with monitoring and auditing systems to track and analyze user activity and identify suspicious actions.
• Use of machine learning for data analysis and detection of anomalies and suspicious activity.
• Integration with authentication systems to verify user authenticity and prevent the use of stolen credentials.
• Integration with access control systems to restrict access to confidential information and access management systems to reduce the risk of data compromise.
• Integration with threat detection and protection systems to ensure network security and protection against cyber threats.
• Use of data collection and analysis tools such as SQL, Python, R, and Tableau.
• Generation of reports and analytics to assess the effectiveness of the detection and prevention system of digital fraud and identify trends and patterns.
• Ability to update and modify the system based on changes in technologies and security threats.