Prepare for the InsurTech Wave

INSURANCE TECHNOLOGY TRENDS
Data and Analytics – Underwriting
1.
Underwriting, Pricing & Risk Selection
Underwriting: The
process of determining
how risky a potential
insured person will be.
Factors such as age,
gender, health, medical
and financial history,
career and hobbies go
into determining a
rating / underwriting
score.
Underwriting History (2)
1990
2000
2010
Now
Human element /
problem solving
Simple Automation
Basic Profiling & Risk
Scoring
More automation
Predictive Modeling &
Automation dominate
the industry
Underwriting, Pricing & Risk Selection
Data & analytics help to automate
underwriting, making the process, as well
as the actual underwriters, become more
efficient and valuable (1)
Benefits of Automated Underwriting
Accurate pricing: Prevalence of more
accurate risk models such as loss predictive
models, rate evasion predictive models, and
modeling relative to the probability of loss
across policies
Speed: Partially automated or fully
automated underwriting systems can help
experienced underwriters to improve
productivity per customer
Challenges of Automated Underwriting
Loss of human insights & perspectives:
Predictive models may not be able to identity
anomalies, detect nuances in risk quality or
incorporate real-time data (2)
From that perspective, Ernst & Young
believes there will be a shift back to a
balance between the human element and
automation in underwriting
Recently
acquired by
Pattern Matching:
Some companies
have applied other
sophisticated risk
profiling technologies
such as "pattern
matching" for
assessing and
scoring risk
“In an industry that still embraces
continual learning, there is an
increased realization that models
cannot and should not be the final or
absolute arbiters in underwriting
decisions. Rather, they are best viewed
as one component in the broader risk
selections and pricing process.” (2)
Serving 3 of the top 10 P&C insurance carriers in
the U.S. and Canada, EagleEye Analytics uses
machine learning predictive analytics techniques to
improve insurers’ pricing and underwriting
Business intelligence for (re)insurers to
monitor aggregates, assess performance,
price risk and review reserving
Praedicat develops software that creates liability
catastrophe models for the P&C industry by
mining unstructured text data in over 22 million
scientific journal articles and profiling thousands
of corporations
Analyze Re provides a
platform for reinsurance
technology such as software
analytics for risk pricing and
optimization
Source: IBM: “Harnessing the power of data and analytics for insurance."
(1) www.PropertyCasualty360.com: “Data-driven underwriting matures and supports policy management."
(2) Ernst & Young: ‘’Are Underwriters Smarter than Predictive Modeling?"
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