S MART GROWTH AT THE N AVY Y ARD ? Photo: Michael Grealish and Kimberly Holmes.
Chief Analytics Officer Fall USA 2017 - Kimberly Holmes - XL Catlin
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Transcript of Chief Analytics Officer Fall USA 2017 - Kimberly Holmes - XL Catlin
Analytics and the Insurance
Business Model of the Future
October 2, 2017
© 2017, XL Catlin companies. All rights reserved. I MAKE YOUR WORLD GO 1
© 2017, XL Catlin companies. All rights reserved. I MAKE YOUR WORLD GO 2
AGENDA
• Insurance model of the future
• Analytics operating model
• Q&A
© 2017, XL Catlin companies. All rights reserved. I MAKE YOUR WORLD GO 3
AGENDA
• Insurance model of the future
• Analytics operating model
• Q&A
Insurance Innovation is Driven by Analytics
Analytics is at the core of new sources of
efficiency, insight, customer experience and
value-add © 2017, XL Catlin companies. All rights reserved. I MAKE YOUR WORLD GO 4
Transforming Insurance
Customization of technology, data and process
Risk-by-risk underwriting
Qualitative judgment only
Manual data capture
Scale through people
Know our policy
Sell risk capacity
Siloed systems
Disconnected data
Modularization / standardization
Portfolio underwriting
Qualitative + quantitative
Automated data capture + enhancement
Scale through technology
Know our customer holistically
Sell diversified services
Accessible connected data
Insight on demand
Underwriter skillset
evolution
Long-term strategic
technology + data
investments
It Takes Capabilities Beyond Analytics
© 2017, XL Catlin companies. All rights reserved. I MAKE YOUR WORLD GO 6
New
Insights
Automated
Real Time Data
Automated
Model Trigger
Reporting
• New data, both internal and external, and new uses of existing data
• Analysis of business decisions
• Testing of conventional wisdom and hunches
• Internal and external data populated in real time
• Typically no manual data entry
• No gaming the system
• Minimal disruption to process
• No opting out
• Model is “invisible”
• UI automatically delivered
• Real time monitoring of decisions
• Drill down capabilities
• Accountability and transparency
• Fosters portfolio view for line underwriters
• The discipline of measuring decisions
© 2017, XL Catlin companies. All rights reserved. I MAKE YOUR WORLD GO 7
AGENDA
• Insurance model of the future
• Analytics operating model
• Q&A
The Core of Innovation is Understanding What
Capabilities Your Stakeholders Need
Successfully Innovate With Analytics by
• Identifying and prioritizing the capabilities needed by stakeholders
and we design and build the capabilities
• Defining and agreeing on, in advance, what metric we will improve
• Considering business context (# records, signal, availability/quality of
data) when designing solutions
• Understanding what is good enough; balancing speed of delivery with
improvement in business results
• Relentlessly focusing on change management, process and people
• Collaborating with underwriting, claims, actuarial, IT and finance –
multidisciplinary teams are more successful
8 © 2016, XL Group Ltd. All rights reserved. I MAKE YOUR WORLD GO
9
Analytics Organization
Team Lead
Business Liaison(s) Machine Learning
Steering Committee
Program Management
Information and Data
Management
Evangelize analytics
Set analytics roadmap
Opportunity
Identification &
Assessment
Capability Development
and Support
Analytics Standards and
Education
Liaise between modeling
and business
Identify viable solutions
for
Assess business impact
Project Delivery
Feature engineering
Model design, selection,
testing, build, validation
Heat maps
Implementation support
Acquire, reconcile,
profile, match data
Build relational data
model
Manage technical
capabilities – software,
model monitoring,
reports
Liaise with IT
10
Opportunity Identification Process
Identify
Understand Define Assign Align
Business Initiated
Business communicates opportunities to
enhance analytics through various channels:
Intranet submission
On-going interactions with Analytics
Analytics Initiated
Analytics proactively identifies opportunities to
leverage analytics for the business through:
Mining data to develop preliminary insights
Collecting market / competitive intelligence
Business & Analytics Coordinated
Business & SA identify opportunities to
enhance analytics through:
Scheduled business working sessions
Collaborate with Business
Actuary to understand existing
analytical tools
Collaborate with Senior
Underwriter(s) to understand the
underwriting decision process
and performance of book
Coordinate with Business
Actuary to define and consolidate
project opportunities
Assess feasibility and impact on
business
Align with Business Actuary to
assign opportunities to either SA
or the business
Assign projects to SA that are
transformational2 or that the
business does not have the
resources to execute
Evaluate opportunities
Collaborate with Line of
Business Lead to prioritize
projects for SA to execute
Develop high-level project
description3
History of model development
Data sources and uses
Underwriting decision criteria
Tool support for underwriting
Profitability issues
Feasibility
Impact on business
Transformational capabilities of
opportunities
Resources to execute
Impact on business results
Estimated resources required
from business
Risks
Timeline
1
2 3 4 5
Key A
cti
vit
ies
Key
Co
nsid
era
tio
ns
11
Opportunity Assessment Process
Prioritize Select Confirm
Consolidate opportunities across channels
and business units
Review and validate completeness of
project descriptions1 for each potential
opportunity
Leverage the prioritization framework to
assess and prioritize each opportunity
Select opportunities to pursue as projects
Communicate to key stakeholders that
either the project is waiting final
confirmation or the project was not selected
to progress
Confirm project selection
Communicate selected projects to Steering
Committee
Communicate project selection or deferral
to key stakeholders
Data readiness
Business resource availability
Profit impact
Project timing and duration
Analytics resource capacity
Alignment with enterprise strategy and key
priorities
Key A
cti
vit
ies
Key
Co
nsid
era
tio
ns
12
Prioritization Framework
Resource Availability D
ata
Re
ad
ine
ss
Low
Low High
Hig
h
Lo
w
Size of Premium Impact High
Prioritization Illustration Key Criteria
Medium
1. Data Readiness
Evaluate internal and external data availability, applicability
and accessibility
Rate data readiness on a scale from low (data will be
difficult to obtain, cleanse and / or link) to high (data will be
easily accessed, is ready for analysis and / or can be linked
to internal databases)
2. Business Resource Availability
Assess business willingness to work with Analytics and
availability of resources to dedicate to the project
Rate business resources availability on a scale from low
(business is not open to working with Analytics and is
unlikely to dedicate resources) to high (business is open to
partnering with Analytics and will dedicate the appropriate
number of resources)
3. Size of Premium Impact
Estimate the premium impact from loss ratio improvement
and / or premium growth resulting form the implementation
of the analytics solution
High impact opportunities that have accessible data and willing business
counterparts will be prioritized and selected to move forward.
Effectiveness Measurement Framework
To measure and communicate the impact of SA, it is critical to identify, track and
report on key metrics that align with the organization’s strategy.
What to
Measure
Every project begins with identifying what metric we want to change. Top line,
loss ratio or expense ratio
Commitment Written agreement on changing metric agreed in a project charter which keeps
all stakeholders aligned to the same outcome.
Identify Driver
of the Metric
Identify specific actions that need to happen (or change) in order to bring
about the improvement in the targeted metric
Measure
Early – measure if action is happening
Results – indications that the targeted metric is changing
13
© 2017, XL Catlin companies. All rights reserved. I MAKE YOUR WORLD GO 14
AGENDA
• Insurance model of the future
• Analytics operating model
• Q&A