Risk assessment using data analysis

Utilizes data from various sources to assess the insurance risk of specific individuals or entities.

Implemented functionality:

• Integration with the customer database to utilize information about clients and their policies in the analysis.
• Use of machine learning for automatic identification of patterns and trends in customer data.
• Application of statistical methods to assess risk and forecast the probability of insurance claims.
• Integration with external data sources, such as weather services and crime data, to evaluate risk in different geographical areas.
• Data visualization to provide a more visual representation of risk analysis results and client information.
• Integration with insurance company business processes to automate risk assessment decisions and provide recommendations.
• Integration with monitoring and auditing systems to ensure data security and confidentiality.
• Providing access to data and analytics only for authorized users and restricting access to confidential information.
• Use of data collection and analysis tools such as SQL, Python, R, and Tableau.
• Ability to update and modify risk assessment models based on changes in market conditions and client data.