Data Science in Action for an Insurance Product - Shawn Jin

1. 1
Data Science in Action for an Insurance
Product
Shawn Jin
Managing Director, Head of Analytics
Plymouth Rock Home Group
Nov 18th 2019

2. 2
We changed our product with easy quote process
with great service

3. targeting new customers which are profitable
competitive and marketable
Profitable:
Target Rate is Below filed Rate
Competitive:
Filed Rate is Below Competitor
rate
Marketable:
Needed Acquisition Cost is
Below Allowable Acquisition
Cost
Target

4. 4
Renewal
Potential
customer
Quote
Subm
ission
Pricing
PolicyServicing
§ Submission prioritizations
§ Agent management
§ Distribution channel
▪ Retention
▪ Price elasticity
▪ Risk
▪ Residual life time value
▪ Investments
▪ Claims
▪ Severity prediction
▪ Fraudulent claims
▪ Subrogation
§ Pricing
§ Loss cost prediction
§ Price elasticity
§ Life time value
§ Underwriting efficiency
§ Inspections
Operations
Database
Actuary
Prediction
Analytics
with Data Science to support business strategies in
every phase of the customer life cycle
§ Targeted marketing
§ Response model
§ Revenue
§ Risk model
§ Life time value model

5. 5
by continuously acquiring various data sources
to separate good and bad risks
• Data source1
• Data source 2
• ……
• Data source m
Properties with
bind-able rate
Various model scores

6. 6
and constantly test advanced analytical methods
and tools

7. 7
Visual
Correlation
Factor analysis
Clustering/Segmentation analysis
Descriptive
Analytics
Testing
GLM/LogisticRegression/Frequency/Severity
Survival analysis
Time series analysis
Discriminate analysis
DecisionTree/RandomForest/GBM/XGBoost/etc
Neural networks/Deep Learning
Mixed Modelling
on various analytics methods
Predictive
Analytics
DoE—Design of Experiment

8. 8
and actively think and breath with product team
for new strategies to improve the product
• Data scientist
• Data scientist
• ……
• Data scientist
Product TeamR&D team
• Product analyst
• Data scientist
• ……
• Product analyst

9. 9
also enforce standard analytical process
• Sample design
• …
• …
• Feature creation
• …
• …
• Scoring code
testing
• …
• …
• PSI
• …
• …
Project
Design
Execution
Implementation
Monitoring

10. 10
so that the best practice is institutionalized
Project/Model ID
• LOB
• …
• …
Code structure
• Readme
• …
• …
Summary results
• Decsion1
• ….
Insights
• Conclusion
• ….

11. 11
We also build a platform for individual to develop
and excel
• Problem Solver
• ……
• ……
• Fun and pleasant
Technical SkillsPersonal Attributes
• Languages
• ….
• ……
• Communications
Career Advance
• Data Scientist
• …..
• ……
• VP Data Scientist

12. 12
Thank You!
not every company makes it easy to experiment with the insight generated by its advanced
analytic teams, so any really good data scientist who wants to enjoy seeing and being a part of the
impact of his or her discoveries should work for Plymouth Rock.
Bill Martin
Plymouth Rock Home Group CEO