Power BI and Data Set.
Budget: ₹600 – ₹1,500 INR
DESCRIPTION
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
NOTE : (Need the screenshots of the work in a word format that is being done along with a short note / description of the task being executed)
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
NOTE : (Need the screenshots of the work in a word format that is being done along with a short note / description of the task being executed)
Related categories:
Power BI