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6
Data Capture – Use Cases
Geographical
segmentation
Geography is a highly discriminant feature
in car insurance. Taking geography
into account can be performed through
a zoning which assigns a pricing modulation
coefficient to each zip code.
A robust estimation on each of the 6 300
zip codes seems barely feasible in regards
to the required data volume. Market
approaches mainly head towards a
residuals spatial smoothing or a demographic-based
classification (density,
agglomeration type,...). However, these
approaches lie on strong and hardly verifiable
assumptions.
Data capture makes the zoning building
reliable through external data integration
with the market zonings. Data capture
may thus be seen as an indirect
means to access other players’ portfolio
information.
Price elasticity model
The price impact on the customer’s behavior
constitutes a critical piece of information
for the gross premium positioning.
The customer behavior is taken into account
within the pricing process through
a price elasticity model which aims to describe
the subscription, cancellation and renewal
dynamics.
Sia Partners has developed a price elasticity
model that includes the market prices
from the data capture on one of its customers’
home insurance product.
Variables relative to pricing positioning are
displayed among the 10 most explanatory
variables of the cancellation model. Moreover,
the model analysis highlights an
increasing importance of these variables
over time. The customer behavior evolution
and the cancellation facilitation lead
us to conclude this trend could continue
growing.
Technical zoning
• Mapping the technical model residuals
• Building the zoning with spatial smoothing (Gaussian kernel)
The developed model can predict the
impact of the pricing adjustments on
the cancellation rate of every customer
profile, including taking into account the
competing offer in the market.
Competitors’ zonings
• Selection of market zonings (key players, similar guarantees,…)
• Extracting and reconstructing the retained market zonings
Benchmarking
• Identifying the deviations between technical and market
• Investigating the gaps on robust points
Joint zoning Technique & Market
Application of a credibility model based on the following principles:
• Each zip code coefficient matches a weighting between technical and market zonings’
coefficients.
• The weighting depends on the robustness of the technical zoning estimated from the
company internal data.
The model has been used in order to aim
for two specific profiles during the annual
revaluation :
• Profiles which are strongly sensitive
to the price for which any increase
could translate into a substantial rise
of cancellations.
• Profiles which are poorly sensitive to
the price and then likely to go through
a price increase without any substantial
impact on cancellations.
Data capture reveals its potential within
the gross premium positioning through
developing quantitative models taking
into account the other market players’
impact.