Quantifying Insurance Agency Channel Dynamics Using Premium Sales Big Data and External Factors

Area of Science:

• Business analytics and computational modeling in the insurance sector.
• Development of novel segmentation and evaluation frameworks for insurance agencies.

Background:

• Insurance product sales predominantly occur through independent agencies, highlighting the need for effective agency evaluation.
• Current agency evaluation methods in the insurance industry rely heavily on internal business data, neglecting external factors.
• Limited scientific attention has been given to the complex problem of insurance agency evaluation.

Purpose of the Study:

• To propose a computational approach for modeling insurance agency behavior traits by integrating premium sales big data with external facts.
• To develop a segmentation-based agency evaluation model that incorporates utilization, response, and governance dimensions.
• To enhance the understanding and evaluation of insurance agency performance beyond traditional metrics.

Main Methods:

• Developed a computational model to translate behavior traits into utilization, response, and governance features.
• Adapted point-of-interest data to compute utilization scores, reflecting agency potential and profit conversion capability.
• Incorporated premium sales big data (127 million transactions) and external socioeconomic factors for model training and validation.

Main Results:

• The proposed approach efficiently extracts relevant features from production logs.
• Behavioral models are intuitive, facilitating straightforward application in agency segmentation and evaluation.
• The segmentation-based model offers an improvement over traditional methods that solely rely on premium production metrics.

Conclusions:

• The developed behavioral models provide a comprehensive understanding of insurance agency dynamics.
• The integration of external facts and big data analysis enhances agency evaluation accuracy and insight.
• The proposed model demonstrates significant performance and usability improvements in practical insurance analytics systems.