Insurance Agent Performance & Metrics Analysis
Budget: ₹600 – ₹1,500 INR
The objective is to improve the agents’ existing knowledge used for agent segmentation in a supervised predictive framework.
Problem Statement Scenario:
An insurance group consists of 10 property and casualty insurance, life insurance and insurance brokerage companies. The property and casualty companies in the group operate in a 17-state region. The group consists of major regional property and casualty insurer, represented by more than 4,000 independent agents who live and work in local communities through a six-state region. Define the metrics to analyze agent performance based on several attributes like demography, products sold, new business, etc.
Below are the Visualization charts that need to be incorporated:
a. Summary stats by agency
b. Product line: Commercial Line/Personal Line wise analysis
c. Agency wise and state-wise distribution of Retention Ratio (Top 10)
d. Hit ratio distribution across different Quotes-systems (also by PL/CL)
e. Add a few more based on your understanding of the data
• Growth rates from 2006 to 2013 have to be computed and converted to independent attributes and included in the data for modeling.
• Compute Hit ratio based on bounds and quotes for each Quotes-system
• Compute required aggregations at Agency ID, state, and year
• Decide if binning the data works for this situation
Problem Statement Scenario:
An insurance group consists of 10 property and casualty insurance, life insurance and insurance brokerage companies. The property and casualty companies in the group operate in a 17-state region. The group consists of major regional property and casualty insurer, represented by more than 4,000 independent agents who live and work in local communities through a six-state region. Define the metrics to analyze agent performance based on several attributes like demography, products sold, new business, etc.
Below are the Visualization charts that need to be incorporated:
a. Summary stats by agency
b. Product line: Commercial Line/Personal Line wise analysis
c. Agency wise and state-wise distribution of Retention Ratio (Top 10)
d. Hit ratio distribution across different Quotes-systems (also by PL/CL)
e. Add a few more based on your understanding of the data
• Growth rates from 2006 to 2013 have to be computed and converted to independent attributes and included in the data for modeling.
• Compute Hit ratio based on bounds and quotes for each Quotes-system
• Compute required aggregations at Agency ID, state, and year
• Decide if binning the data works for this situation