IDMA 2016 Digital Insurer: New Models, Risks & Opportunities

IDMA Annual Conference - April 18, 2016

Public

Digital Insurer: New Models, Risks &

Opportunities

Pat Saporito, SAP

Brent Cavan, Tokio Marine

© 2015 SAP SE or an SAP affiliate company. All rights reserved. 2Public

What’s HappeningNew Business Models, Customer Experience & Value Paradigms

UberThe world’s largest taxi company, owns

no vehicles.

AlibabaThe most valuable

retailer, has no inventory

AirbnbThe world’s largest

accommodation provider, owns no real

estate.

ORGANIZATIONAL LEADERS REQUIRE A VISION TO LEAD IN THE DIGITAL ECONOMY


Living in a Digital Economy

90%Of the world’sdata has been

generated1

40%Growth in

adoption of business

networks2

212

Billion“Things” will

be connected3

51%Of workloadsprocessed in

the cloud5

The need to

provide

analytics to

everyone

Reduce cost

and complexityAutomate

analytics in the

age of the

algorithm

Travel in light

years with

enterprise

speed and

scalability

HYPERCONNECIVITY IS DRIVING NEW CHANNELS AND CONNECTED ECOSYSTEMS


The Need Has Never Been Greater….

90%Need access to

analytics by 2020*Gartner

Today

High workloads and scarcity of digital skill sets

Inaccessible data and technology

Siloed approaches and analytics technologies

Lack of predictive, real-time insights

Future

All Analytics, All Data, All Users, Anywhere

Access – in real time!

Analytics for Everyone

Own the Outcome

Be the One to Know


Agility

Cost

Innovation

Quality

Other

Financial

36%Already replaced or

planning to replace with

SaaS BI

Already complementing or

planning to complement

with SaaS BI31%

Within the next 2 years Primary reasons for investingIn the public cloud

Source: "Application Adoption Trends :The SaaS Boom Continues As Businesses

Demand Agility“. ForresterSource: Gartner CIO Survey

56%

14%

13%

10%

7%

5%

5

The Cloud is Eating Analytics

KEEP YOUR DATA WHERE IT IS

ACCESS ANYHOW, ANYWHERE - CLOUD AND ON PREMISE

MUST INCLUDE SECURITY AND COMPLIANCE.


Sales Planning,

Marketing

Planning

6

ANALYSTS & PLANNERS

Data Discovery,

Visualization,

Variance

Analysis

Retention and

Revenue

Analysis

Risk-adjusted

Bus/Opps

Planning

Predictive

Modeling

DATA SCIENTISTS

Big Data

Discovery

Prescriptive and

Preemptive

Analytics

Loss Prevention

Analytics

Budgeting,

Planning,

Profitability

Modeling

FINANCE

Mgmt. Reporting,

Variance Analysis

Predictive

Planning

Forecasting

Risk-adjusted

Planning

KPIs,

Scorecards,

Initiatives

Forecasts

C-SUITE

Board Reports

& Dashboards

Forecasts

Ent. Risk

Reporting,

KRIs

Budget input

INFO CONSUMERS

Production

Reporting /

Dashboards

Forecasting

Ent. Risk Reports

EPM/PLANNING

REPORTING/ VISAULIZAITON

PREDICTIVE

GRC

EPM/PLANNING

PREDICTIVE

GRC

Address All Users with All Analytics

ENTERPRISE ANALYTICS, NOT ANALYTIC SILOS

REPORTING/ VISAULIZAITON


Digital core

Omnichannel

network

The Internet of Things

network

Service and supplier

network

Workforce network

Front

office

Middle office Back office

SAP HANA platform

Property Life Health

Real Time Data & Analytics

Digital Framework for InsurersData & Analytics is the life blood of Digital

Personalized experience

Reduce FTE costs

Engaged partners & suppliers

Optimized risk management

Operational AgilityDigital Orchestration Full analytic transparency

Transactional & Analytic Data Platform


Real Time Platform

End-to-end Value Chain

SPATIAL

PROCESSING

ANALYTICS, TEXT,

GRAPH, PREDICTIVE

ENGINES

CONSUME

COMPUTE

STORAGE

SOURCE

INGEST

Application

Development

Environment

Transformations & Cleansing

Smart Data Integration Smart Data Quality

StreamProcessing

Smart Data Streaming

STREAM

PROCESSING

LogsTextOLTP Social MachineGeoCore SensorStore & forward

Smart Data Access

Virtual Tables

User Defined Functions

1010100

1010110

1001110

Dynamic Tiering

Aged datain Disk

In-Memory

Data model& data

Calculation Engine

Fastcomputing

Column Storage

High performance analytics

Series Data Storage

Store time-series data

Reporting &Dashboards

High Performance Applications

Data Exploration& Visualization

Ad hoc & OLAP Analytics

PredictiveAnalytics

Enterprise Performance Management

Governance Risk &

Compliance

Big Data

Hadoop / NoSQL

MapReduce

YARN

HDFS

On Premise, Cloud and Hybrid


Data Challenges

Challenges

• Data is everywhere

• Multiple data types

• Data integration

• Analytic tools

• Analytic skills

Impact

• Data silos

• Data credibility

• Data access

• Lack of data use

• GIGO – “Junk” analytics


Insurers Digital ProgressP&C is ahead of L&H, but still has room for improvement!

http://www.bain.com/Images/GLOBAL-DIGITAL-INSURANCE-2015.pdf

http://www.bain.com/Images/GLOBAL-DIGITAL-INSURANCE-2015.pdf


Digital Transformation Roadmap

Define a Digital Strategy

• What does digital mean to

your organization? Your

customers? Your partners?

• How does digital relate to

your strategic

plans/initiatives?

• What are your digital

opportunities? Risks?

Develop a Digital Culture

• Business processes

• Skills and behaviors

• Agility

Review your Digital

Capabilities

• Data management

• Analytics

• Data bases

• Analytic platform


Insurance Industry Disrupters

Trends/Models

Peer to Peer Insurance

Usage Based Insurance

Spot / OnDemand

Insurance

Contract/Service

Management

Aggregators/Quote

Engines

Source: Friendsurance


Digital Insurance Models

Analytic Analyzers Digital Distributors

Customer Centric Insurers Effective Operators

Tokio Marine’s Digital

Journey


Tokio Marine NA – Digital Transformation Roadmap

Digital Strategy “V. 1”

• Advanced Analytics

• Quoting/Submission Portals

• Mobile Services for Agents

(reporting, commission tracking,

app / form downloading)

• Mobile Services for Accounts

(policy docs, ID cards, claim status)

• CRM Enhancements

• Integrating Web Sites with the

Content Management System

• Web Analytics Upgrades

• Expanded Social Media Output

Digital Culture

• Agility – Analytics / Visualization

Prototyping

• Imagination – Design Thinking

• Control – The Art of “Guided Tours”

• Self-Service – Running with “Safety

Scissors”

• Round 1 – Business Process Wins

• Round 2 – Engagement Programs

• WARNING: Build or “Fade Away”

Digital Capabilities

• Advanced Analytics AND Data

Visualization TOGETHER

• Data Source “Be Damned”

• Business Rule Automation

• Real-Time Delivery

• Platform Independence

• Expand on the “Known”

• Typical Foundational WorkGOOD

• “Have Data, Will Use It”

• Explore Sources / DeliveryBETTER

• “50 Shades of Gray”

• Elevating UsersBEST


Tokio Marine NA – Customer Service Knowledge Example

Customer Segmentation

• Demographic, Geographic, Psychographic, Behavioral (SAP and IBM Tools)


GRPCO1

Tokio Marine NA – Customer Service Targeting Examples

Scoring Models

• Exploiting NPS vs. Issue Satisfaction, Performance, Sales Activity

Users can select a set of criteria to group target agencies, and then drill through to key details on each.


Tokio Marine NA – Customer Execution Examples

Profiles

• Agency Production, Submissions, Surveys, and Affiliation

Blue Dots – Average “Customer Experience” Score on an Issue for Agencies in a SegmentGreen Dots – GRPCO1-rated Score, where GRPCO1 Did NOT OverateRed Dots – GRPCO1-rated Score, where GRPCO1 DID Overate


Tokio Marine NA – Harnessing the Internet of Things (IoT)

Digital Strategy “V. 2” – Maybe

• Health – Bed Motion Sensors

• Auto – Tablets / iPads for Adjusters

• Auto – Telematics (Sensors, Video)

• Property – Building Management Systems

• Property – Smart Sensors (NEST)

• Property – Drones (Damage / Other Evaluations)

• Weather – NC4 and Everbridge Alerts

DATA! DATA! DATA! for Analytics

Example—Hail Patterns within Storm Tracks

Would You Know How to Use the Data?


Tokio Marine NA – Where to Start (Strategically)

Evaluation of IoT “Things”

• Not Every Shiny Object is Equal

• Focus on “Where’s the Money?”

Customer Lifetime Value

CLV – Combined Ratio, Premium Margin, Retention, Goal

Overall Renewal Retention Goals are critical. The impact can be even greater for higher profit margin products.


Tokio Marine NA – Where to Start (Tactically)

Many IoT “Things”

• Expansion of Data

• Expansion of Possibilities

• Expansion of Crap

• Focus on “Objectives”

• Focus on “Questions”

• Focus on “Sampling Plans”

Objectives

Define Your Objectives! At the Beginning!


Tokio Marine NA – Design Framework I

Design Thinking

• Know the “Known”

• Find Out the Rest!

• Focus on “Customer Experience”

• Focus on “Possibilities”

Way to go, Einstein!

Einstein’s Special Theory of IoT

“I’d spend 55 minutes thinking about the problem

and 5 minutes thinking about solutions.”


Tokio Marine NA – Design Framework II

Design Thinking

• Think – through Solutions

• Build Fast

• Measure Results!

• Focus on “Change”

• Focus on “Disruption”

Who Do You Think You Are…

Einstein?

Einstein’s General Theory of IoT

“The world as we have created it is a process

of our thinking. It cannot be changed without

changing our thinking.”


SAP Design Thinking FrameworkInnovating with a Design Thinking approach

© 2015 SAP SE or an SAP affiliate company. All rights reserved.

Thank you

Pat Saporito, CPCU, FIDMSr. Dir., Global COE for Analytics

SAP Labs

+1 (201) 681-9671

[email protected]

Twitter: @PatSaporito

Linkedin:patriciasaporito

Author Applied Insurance Analytics

Amazon http://amzn.to/1mfmYiC

Brent Cavan, MBAManager, Advanced (Predictive) Analytics

TMNA Services, LLC

+1 (610) 538-2162

[email protected]

Digitalist Magazine by SAP

Hasso Plattner Design Institute at Stanford Univ.

mailto:[email protected]

http://amzn.to/1mfmYiC

mailto:[email protected]

http://www.digitalistmag.com/

http://dschool.stanford.edu/dgift/

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