An examination of how social data is impacting the insurance industry and how practices are adapting to those changes. Participants were introduced to entrepreneurs, startups and innovators influencing the way people are sharing data, and examined many issues facing the ever-changing landscape of insurance.
0930 23andMe: Health Insurance, Genetics and Social Data, Marisa Nelson (Business Development Associate)
1045 Depart for HealthTap
1100 HealthTap: Medicine and How People Express Themselves, Ron Gutman (Founder and CEO)
1230 Lunch at Stanford
1400 Social Data Summit at Stanford
1430 Introductions and Expectations, Social Data Lab Members (Stanford students)
1715 Presentations by Lab
The Power of Social Data (Karthik)
Social Data Intelligence Test (Aldo,Tim)
1830 Dinner at Three Seasons
Monday, May 17th, 2011 -- WORKSHOP
1450 Andreas Weigend
1540 Tom Warden - Overview of Social Data work at ARPC & Allstate
1620 Coffee / Cookies-Pastries (defining break out topics)
1630 Break out
1715 Rapporteurs present findings
1745 Dr. Weigend's Summary
1815 Transfer to San Francisco for dinner
Participants were introduced to some of the exciting startups that are influencing the way insurance is doing business. The startups were focused predominantly around the topic of health and data.
They aim to help people understand what their genes mean by indexing them and highlighting significant findings. 23andMe allows its clients/users to study their ancestry, genealogy, and inherited traits. The company also markets to researchers and scientists, for whom they provide neatly categorized and easily searchable data.
HealthTap is an Interactive Health company passionately dedicated to improving your health and well-being, and to improving the overall process of care for you and your doctor, while reducing costs.
What is the value of data?
How do we measure the value?
“Equation of the business”
Why do people share?
Need to belong
What does true customer centricity mean, and how do social data make a difference?
CRM as part of the managerial economy, vs customer centricity?
What makes people change their behavior (emotions)?
How can we get people to understand trade-offs?
In the digital world, you can share information with people you don’t know.
What builds trust?
What destroys trust?
Asymmetry / Balance
Digital vs physical (O2O: online to offline)
What has changed?
Startups that might embed learning that we can tease out for insurance
Color, Hunch: generalized model of consumer prefs
App to communicate with the agent
What could be shared that is useful for agent and not negative for customer
What be cases where customers share with an institution?
Different levels of anonymized data (readings Cynthia Dwork paper + video, http://stanford2009.wikispaces.com/9_Privacy+Wed%2C6.10, esp How To Break Anonymity of the Netflix Prize Dataset : "The dataset is intended to be anonymous, and all customer identifying information has been removed. We demonstrate that an attacker who knows only a little bit about an individual subscriber can easily identify this subscriber's record if it is present in the dataset, or, at the very least, identify a small set of records which include the subscriber's record." [Narayan and Shmatikov, 2006]
matching “anonymized” data to non-annonymized with some degree of confidence so that the information ratio in the match overcomes the noise the lack of good matching creates
Designing incentives / business model such that people give truthful answers
Behavior change: Drivers young and old
How do behavioral beliefs change over lifecycle (psych principles): What motivates young and old ppl to change their behavior? (In our case, to share data)
e.g., postitive vs negative rewards
given by whom?
time scale: minutes or years
Students to think one level higher up
In general terms (e.g., to find ways for customers to friend their agent)
general behavioral trade vs specific
Insurance specific questions:
Why data is important (information asymmetry)
Data = raw material
Data within the company
Collected by company
Is the data correct?
Cost of data: Cost of false data, cost of correcting data
Collected by user
Data that sit elsewhere
Social norms I.
Assume everything recorded... how would it change your behavior?
What does it mean to own data?
Data creation / collection / sharing / distribution / consumption...