Here is a talk I gave at the Tableau Event in Boston. I talk about how to use Tableau and other data visualization techniques in the Insurance analytics space. A video link of the talk can be found on Youtube

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Massachusetts: Chart Champ
https://public.tableau.com/profile/shatrunjai#!/vizhome/TBW_FINAL_CAHRTCHAMP_SUBMISSION_JAI_20160904/D_01_Fina
l_Dashboard
Dashboard analyzing
MA school districts:
• Finding the schools with the
highest SAT Scores in the
neighborhoods with the lowest
house prices
• We found that schools
 Away from Boston,
 Low population densities,
 Low crime rate and
 Highly skilled teachers,
tend to outperform other schools
on our SAT/house-price metric

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Where How
So
What?
Where do we use Tableau ?

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Where do we use Tableau ?
EDA on historic data
Underwriting
Long term care
Marketing
Reserving
Monitor real-time
Performance
Predictive Analytics
Automated
Underwriting
Claims
trends
UW Decision
Monitor
Historic
Performance
Market
Segmentation
Market
Mix
Modelling
Who will buy,
lie and die
models
Fraud
Prevention

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Where How So
What?
How do we use Tableau ?

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Creating a 360 view of our customers
• Following the data
journey of a Vitality
customer
• Tableau allows for
quick integration
from multiple data
systems allowing us
to generate 360
insights

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Visualizing the journey of data
• Finding gaps in historic data allowed us to prioritize data scrubbing more efficiently
Data
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Data
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Data
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Data
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Data
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Data
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Viewing data with Geospatial capabilities within Tableau
• Maps within
tableau allow for
quick geo-analysis.
• Inbuilt data sources
inside tableau store
a wealth of data
Ability to select zip’s within x miles

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Monitoring Data Health
• The match rate after combining multiple real time datasets can be quickly monitored from
dashboards uploaded on our internal tableau server
Data
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Data
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Data
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Data
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Data
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Data
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In combination with R for advanced analytics
• The advanced analytical capabilities missing in tableau can be substituted by integrating R-
Shiny based web apps
• These R web apps can be added to a story thus allowing quick decision trees

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In comparing predictive model performance
• We frequently use
tableau to
compare different
predictive models
• Integration with
SAS, Python and R
outputs allows
heterogenous
modelling
comparisons in
Tableau

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Creating user guides allows for faster dashboard ingestion
• A quick cross-tab allows for faster bi-variate analysis in tableau
• We have created in-house ‘how to guides’ enabling faster ingestion of our analytical
dashboards

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Where How
So
What?
Source: Tweets for # Careers in Finance Analytics; # Careers in Health Analytics;# Careers in Insurance Analytics

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What has Tableau done for us
Time saved
Make the world of data
beautiful again
Get to actionable insights faster

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Nuggets of wisdom
• Use the tools to their strengths
Data
Engineering
Data
Visualization Modelling
• Good visualization practices saves $$$
Save the Pies for dinner
Soothing
MVR
White spaces make
everything better
Data to Ink ratio is king
Space bars appropriatelyStart axis at 0 Tableau Instant Karma

17. Things Data Visualization rookies say..
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• I have two numbers, I’ll still make a graph anyway…
• Vertical bars are way better than Horizontal bars...
• 3D graphs are cool…
No, the human eye tends
to compare horizontal bars better!
No, just write the
numbers instead
Not cool at all..

18. How to lie with visuals..
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Remove scales altogether
Use 3-D Pie charts
Scale don’t need to start at 0 Shapes don’t need to match data

19. Increased
Impact
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Increased
Insights
Reduced Software Spending
Reduced ETL time
What has Tableau done for us

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3D Pie
Chart
Fin
shatrunjai_singh@jhancock.com
www.shatrunjai.com
https://public.tableau.com/profile/shatrunjai#!/
https://github.com/shatrunjai