The insurance industry is undergoing significant changes driven by new technologies like the Internet of Things, data analytics, and humanoid robotics. Data in particular will change business models by representing new value and enabling the sharing of customer data while respecting privacy. Best practices include using predictive analytics by insurers like Santam and Progressive to streamline processes, signal fraud, implement usage-based pricing, and develop real-time models. Examples given are using aggregated insurance and public data to target police efforts to prevent burglaries and better prepare for climate change-related events like flooding to lower insurance payouts and premiums.

1. THE INSURANCE BUSINESS IN TRANSITION

2. “ Continuous change is the only
constant factor in our society”
Specialismen:
- Trendwatching
- Strategic marketing
- Business development and innovation
- Omni-channel distribution
- Customer Centric en customer journey's
- New (disruptive) business models (Business Model Generation)
- Blue Ocean Strategy

3. Agenda
3
1. Changing eras and the obviousness
2. Drivers for change
3. Best practises
4. Examples
# DDSbigdata
@RobertWitteveen

4. We do not live in an era of change,
but we are changing the eras

5. The end of the obviousness
5

6. The new obviousness
6

7. Divers for change:
- Internet of things
- Quantified self
- Humanoid robotics
- Data analytics

8. Data will change the
business models:
- Data represents value
- Sharing data
- Privacy re-invented

9. Best practise and bad examples
9
 Bad examples:
– Equens (2013)
• Selling 2.2 billon bank transactions
– ING (2014)
• Selling bank transactions for specific
customer offers

10. Best practise and bad examples
10
 Best practise:
– Santam (South Africa)
• Predictive analitics for streamlining process
• Signaling fraud
– Progressive (US)
• Pay as you drive
• Pay how you drive
• Real time price models
– SNS Bank (Netherlands)
• Predictive analitics on payment accounts
• In combination with public data (Funda)

11. +
Example (I): burglary prevention
11
• All insurance company’s
• Internal burglary data
• CVS
• …
• Weather
• Traffic
• Events
• …
Prevention:
- Targeted police attention
- Better resources
Results:
- Less police deployment
- Less social agitation
- Lower insurance premium
- Lower insurance payment

12. +
Example (II): climate change
12
• All insurance company’s
• Internal overflow data
• CVS
• …
• Forecast KNMI
• Weather
• Infrastructure
• …
Prevention:
- Better gutters
- Better drainage
- …
Results:
- Less water damage
- Better human feeling
- Lower insurance premium
- Lower insurance payment

13. THXS!
@RobertWitteveen
nl.linkedin.com/in/robert01/
robert.witteveen@reaal.nl
robert.witteveen1@gmail.com
+31 – 622 41 9579