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Makes Insurance Smarter.
May 2018
1
2
is empowering the life insurance industry with big data and
predictive analytics. Our cloud-based platform provides data-driven insurance and
annuity specific insights to inform decision making and develop new business
strategies.
Atidot was founded in 2016 and is now working with 2 of the top-10 life insurers
and annuity writers in the USA. We are enabling them to take control of their
existing data to improve retention, sales, in-force management, and profitability.
Barak Bercovitz
CTO
● Lead Researcher and
Innovator in the IDF
technology unit
● Aram Graduate
● Vast hands-on
experience with
technology
● Worked for XIV
● Consultant to startups
Assaf Mizan, FIA
Product and Actuarial
● Chief Actuary of the MOF,
(Ministry of Finance)
● Actuary at EY and Swiss
RE
● Actuarial degree: Witz
University in South Africa
Dror Katzav
CEO
● Data Scientist
● M.S. Information Sciences:
Tel Aviv University
● Talpiot (elite IDF technology
and leadership training)
Graduate
● Team Leader / Project
Manager: IDF Technology
Unit
● Consultant to startups
3
Problems
4
• Consumers want a personalized experience and
lower prices
• Insurers and annuity writers want better strategic
decision making
• Data is a challenge: external data sources,
introduction of IoT and sensors, and existing
unstructured raw data
• Traditional methods and legacy systems do not
produce sufficiently accurate models
Solution
5
Insurance Data Cloud
Life
Provides life insurers with a simple to
integrate, self-service tool to leverage both
internal and external data, thereby
improving business decision making and
profitability, and enabling a more
personalized experience for consumers.
The Platform
6
Data Onboarding
and Enrichment
Modeling and Simulation
Strategy and Operation
https://demo.atiodot.com
Benefits
7
Proprietary Data Preparation
Using AI
Monetizing your data with
predictive ready cleansing and
normalization of internal and
unstructured data enriched with
external sources
Insurance Specific Insights
Incorporate multiple models
including profit and risk to reflect
each of these dimensions based on
the client’s needs. Simulate and
use scenario analysis to improve
decision making
Product Solution
Self Service
Simple Integration
Specialized for Life Insurance and
Annuities
Use Cases – Life Insurance and Annuities
8
Up-Sell and
Cross-Sell
Proactive
Retention
Distribution
Optimization
Market Segmentation /
Product Development
- Identify high
profitability segments
as target markets
- Understand customer
needs and develop
more suitable products
- Determine strength
of marketing and
sales methods
- Design triggers that
lead to higher issue
and placement rates
- Understand why
policyholders lapse
- Identify cohorts by
lapse rate
- Discover
under-insured
policyholders
- Find cross-sell
opportunities
within your
customer base
Market Adoption
9
15% Increase in lapse assumptions accuracy for a Direct to Consumer
life insurer bringing their lapse assumption much closer to the experience
that actually emerged
3X Improvement in operational efficiency in proactive retention
efforts (e.g., by better estimating who will lapse, more of the potential
lapse calls were routed to retention specialists)
25% Under-insured potential discovered within a tier-1 in-force book
of business. Increasing the company’s lead score by 150% (i.e. from 2.5 to
3.7 in a 1-5 scale)
90 Day Framework
10
Our validated pilot framework will show you value in just 90 days.
Data
Onboarding
Define business goals.
Onboard, cleanse and normalize
data.
Augment with external sources.
Validation
Go To
Market
Validate model with existing
benchmarks.
Refine model to meet business
needs.
Prepare model for field test.
Refine model based on
performance and feedback.
Business Model
11
Cloud based platform
Leveraging Azure and
AWS capabilities for
decreased IT cost
Proprietary data
analysis
Monetizing in force data
and external data
sources for prediction
Subscription model
Pay per usage based
on number of cases
and policies under
management
High end service
Top tier data scientist
and actuaries with
deep insurance
understanding to guide
you in the process
12
www.atidot.com * info@atidot.com
Thank You!

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Startup InsurTech Award - Atidot

  • 2. 2 is empowering the life insurance industry with big data and predictive analytics. Our cloud-based platform provides data-driven insurance and annuity specific insights to inform decision making and develop new business strategies. Atidot was founded in 2016 and is now working with 2 of the top-10 life insurers and annuity writers in the USA. We are enabling them to take control of their existing data to improve retention, sales, in-force management, and profitability.
  • 3. Barak Bercovitz CTO ● Lead Researcher and Innovator in the IDF technology unit ● Aram Graduate ● Vast hands-on experience with technology ● Worked for XIV ● Consultant to startups Assaf Mizan, FIA Product and Actuarial ● Chief Actuary of the MOF, (Ministry of Finance) ● Actuary at EY and Swiss RE ● Actuarial degree: Witz University in South Africa Dror Katzav CEO ● Data Scientist ● M.S. Information Sciences: Tel Aviv University ● Talpiot (elite IDF technology and leadership training) Graduate ● Team Leader / Project Manager: IDF Technology Unit ● Consultant to startups 3
  • 4. Problems 4 • Consumers want a personalized experience and lower prices • Insurers and annuity writers want better strategic decision making • Data is a challenge: external data sources, introduction of IoT and sensors, and existing unstructured raw data • Traditional methods and legacy systems do not produce sufficiently accurate models
  • 5. Solution 5 Insurance Data Cloud Life Provides life insurers with a simple to integrate, self-service tool to leverage both internal and external data, thereby improving business decision making and profitability, and enabling a more personalized experience for consumers.
  • 6. The Platform 6 Data Onboarding and Enrichment Modeling and Simulation Strategy and Operation https://demo.atiodot.com
  • 7. Benefits 7 Proprietary Data Preparation Using AI Monetizing your data with predictive ready cleansing and normalization of internal and unstructured data enriched with external sources Insurance Specific Insights Incorporate multiple models including profit and risk to reflect each of these dimensions based on the client’s needs. Simulate and use scenario analysis to improve decision making Product Solution Self Service Simple Integration Specialized for Life Insurance and Annuities
  • 8. Use Cases – Life Insurance and Annuities 8 Up-Sell and Cross-Sell Proactive Retention Distribution Optimization Market Segmentation / Product Development - Identify high profitability segments as target markets - Understand customer needs and develop more suitable products - Determine strength of marketing and sales methods - Design triggers that lead to higher issue and placement rates - Understand why policyholders lapse - Identify cohorts by lapse rate - Discover under-insured policyholders - Find cross-sell opportunities within your customer base
  • 9. Market Adoption 9 15% Increase in lapse assumptions accuracy for a Direct to Consumer life insurer bringing their lapse assumption much closer to the experience that actually emerged 3X Improvement in operational efficiency in proactive retention efforts (e.g., by better estimating who will lapse, more of the potential lapse calls were routed to retention specialists) 25% Under-insured potential discovered within a tier-1 in-force book of business. Increasing the company’s lead score by 150% (i.e. from 2.5 to 3.7 in a 1-5 scale)
  • 10. 90 Day Framework 10 Our validated pilot framework will show you value in just 90 days. Data Onboarding Define business goals. Onboard, cleanse and normalize data. Augment with external sources. Validation Go To Market Validate model with existing benchmarks. Refine model to meet business needs. Prepare model for field test. Refine model based on performance and feedback.
  • 11. Business Model 11 Cloud based platform Leveraging Azure and AWS capabilities for decreased IT cost Proprietary data analysis Monetizing in force data and external data sources for prediction Subscription model Pay per usage based on number of cases and policies under management High end service Top tier data scientist and actuaries with deep insurance understanding to guide you in the process