In a data driven economy, analysts must be concerned with how data is collected, processed and subsequently used to improve online customer experiences, during those moments that matter.
Unlocking Value & Controlling Risk by #MindYourPrivacy
Smarter comm"The Future of Privacy". Aurélie Pols at IBM Smarter Commerce Global Summit 2014erce future privacy aurelie pols
1. #smartercommerce
Aurélie Pols
Co-founder & Chief Visionary Officer
Mind Your Privacy & Mind Your Group
aurelie@mindyourprivacy.com
@aureliepols
The Future of Privacy
Data is the New Oil, Privacy is the New Green
Unlocking Value & Controlling Risk
2. @AureliePols
About me
Aurélie Pols
Chief Visionary Officer
Mind Your Privacy
• Grew up in the Netherlands, Dutch passport
• French mother tongue
• Most of my friends are bilingual at least
• Have Polish & Russian origins
• Set-up my 1st start-up in Belgium in 2003
• Sold it to Digitas LBi (Publicis), in 2008
• Moved to Spain in 2009
• Created 2 other start-ups in Spain in 2012
Mind Your Group, Putting Your Data to Work
Mind Your Privacy, Data Science Protected
Yes, a “law firm” but we prefer to say
a bunch of Data Scientists working with
a bunch of Lawyers
3. @AureliePols
Context: Privacy tri-partite
Joint effort by:
1. Governments &/or international
Associations => legislation,
guidelines, …
2. Citizens/voters/consumers
3. Businesses
Each party wanting to defend:
– Personal Data Protection & the Rule of
Law through respect of Fundamental
Rights
vs.
– Profits & hopefully Sustainability
Governments
Citizens/vot
ers/consum
ers
OUR GLOBAL
SOCIETY
Businesses
Analytics vendors / Agencies / Data Users
4. @AureliePols
About Mind Your Privacy
Boutique consultancy firm providing security
consultancy services and legal Privacy advice
Our typical international clients manage
sensitive data within an international
landscape
Pluricultural and multi-skilled profiles - legal,
data scientists and technical
Providing complete solutions to complex data
and privacy issues
6. @AureliePols
Privacy, the Word
From our Wikipedia friends:
From Latin: privatus "separated from the rest, deprived of something, esp. office, participation in
the government", from privo "to deprive”
The ability of an individual or group to seclude themselves or information about
themselves and thereby express themselves selectively.
The boundaries and content of what is considered private differ among cultures and
individuals, but share common themes.
When something is private to a person, it usually means there is something to them
inherently special or sensitive.
The domain of privacy partially overlaps security, including for instance the concepts
of appropriate use, as well as protection of information.
Privacy may also take the form of bodily integrity.
Source: https://en.wikipedia.org/wiki/Privacy
7. @AureliePols
Privacy, nothing to hide?
“If you have something that you don’t want
anyone to know, maybe you shouldn’t be doing it
in the first place.”
Eric Schmidt, 2009
https://www.youtube.com/watch?v=A6e7wfDHze
w
Tip: Follow Daniel Solove on LindedIn!
8. @AureliePols
An Anglo-Saxon term?
Source: http://web.mit.edu/bigdata-priv/
http://www.whitehouse.gov/sites/default/files/docs/big_
data_privacy_report_may_1_2014.pdf
12. @AureliePols
Regulatory law
“Every country is a little different.
You run into different regulatory regimes and you need
to make sure you have the right tools so that people
can implement the right policies they are required to
by law…
They aren’t that different”
Source: Bloomberg Singapore Sessions
April 23rd 2014
http://www.bloomberg.com/video/big-
data-big-results-singapore-sessions-4-23-
kHN5zrGbR_Wq6hbmV9~aXQ.html
13. @AureliePols
A global perspective
US & UK EU APEC
Common Law Continental Law Continental
law
influenced
Class actions Fines
(by DPAs: Data Protection Agencies)
Privacy Personal Data Protection (PDP)
Business focused Citizen focused: data belongs to the
visitor/prospect/consumer/citizen
Patchwork of sector based
legislations: HIPPA, COPPA,
VPPA, …
Over-arching EU Directives & Regulations
PII: varies per state Risk levels: low, medium, high, extremely
high
14. @AureliePols
Democracy & the rule of law
US & UK EU APEC
Common Law Continental Law Continental
law
influenced
Class actions Fines
(by DPAs: Data Protection Agencies)
Privacy Personal Data Protection (PDP)
Business focused Citizen focused: data belongs to the
visitor/prospect/consumer/citizen
Patchwork of sector based
legislations: HIPPA, COPPA,
VPPA, …
Over-arching EU Directives & Regulations
PII: varies per state Risk levels: low, medium, high, extremely
high
15. @AureliePols
Data Protection
In light of fuzzy interpretations of Privacy, could
we agree upon
• Thinking of it as data protection
• Protecting the data we are entrusted with
• While respecting the Right to “Privacy”
• Taking into consideration information security
measures
16. @AureliePols
Democracy & the rule of law
US & UK EU APEC
Common Law Continental Law Continental
law
influenced
Class actions Fines
(by DPAs: Data Protection Agencies)
Privacy Personal Data Protection (PDP)
Business focused Citizen focused: data belongs to the
visitor/prospect/consumer/citizen
Patchwork of sector based
legislations: HIPPA, COPPA,
VPPA, …
Over-arching EU Directives & Regulations
PII: varies per state Risk levels: low, medium, high,
extremely high
17. @AureliePols
PII: ah but we don’t collect it!
Medical information as PII
California
Arkansas
Missouri
New Hampshire
North Dakota
Texas
Virginia
Financial information as PII
Alaska North Carolina
Iowa North Dakota
Kansas Oregon
Massachusetts South Carolina
Missouri Vermont
Nevada Wisconsin
New York* Wyoming
Passwords as PII
Georgia
Maine
Nebraska
Biometric information as PII
Iowa
Nebraska
North Carolina
Wisconsin
Source: information based on
current ongoing analysis (partial
results)
18. @AureliePols
So what is considered PII?
Personal Information (based on the definition commonly used by most US states)
i Name, such as full name, maiden name, mother‘s maiden name, or alias
ii Personal identification number, such as social security number (SSN), passport
number, driver‘s license number, account and credit card number
iii Address information, such as street address or email address
iv Asset information, such as Internet Protocol (IP) or Media Access Control (MAC)
v Telephone numbers, including mobile, business, and personal numbers.
Information identifying personally owned property, such as vehicle registration
number or title number and related information
Source: information based on
current ongoing analysis (partial
results)
19. @AureliePols
If you collect PII… then
US & UK EU APEC
Common Law Continental Law Continental
law
influenced
Class actions Fines
(by DPAs: Data Protection Agencies)
Privacy Personal Data Protection (PDP)
Business focused Citizen focused
Patchwork of sector
based legislations:
HIPPA, COPPA, VPPA,
…
Over-arching EU Directives & Regulations
PII: varies per state Risk levels: low, medium, high,
extremely high
20. @AureliePols
PII & legislation questions
• Who knows their Chief Privacy Officer?
According to the DMA (US), CMOs should abide
to an average # of 300 pieces of legislation
• Is PII really PII?
Zip code + gender + date of birth can uniquely
identify 87% of the US population
Source: Microsoft Latanya Sweeney (2000)
http://dataprivacylab.org/projects/identifiability/paper1.pdf
21. @AureliePols
PII vs. Risk levels
Low
Medium
(profiling)
High
(sensitive)
Risk
level
Data type
Information Security Measures
Extremely high
(profiling of sensitive data)
PII
23. @AureliePols
The Privacy framework 1
User consent
Fair & Legal process:
FIPPs
Information for approved
use
Data diving analysis / Big
Data
New business opportunity
through data
Purpose
24. @AureliePols
The Privacy framework 2
User consent
Fair & Legal process:
FIPPs
Information for approved
use
Data diving analysis / Big
Data
New business opportunity
through data
Purpose
26. @AureliePols
Data collection
• Purpose – Consent
– Reason for data collection:
• Website improvement, better User Experience
• Marketing communication
• Opt-in? Opt-out? Double opt-in?
– Depends upon:
• Type of data: PII, sensitive data
• Type of sector: financial, health, …
• Geography: US vs. EU vs. ???
28. @AureliePols
Trust & creepiness
Consent is about a reasonable expectation of the use of data
– There’s a fine line
between
feeling charmed
vs.
feeling invaded
– Create win-win situations:
• Customers give company information
• Customers get better service/value for money
29. @AureliePols
Consent & Trust for Telcos
Slide borrowed from Stephen John Deadman from Vodafone Group Services Limited, IAPP
congress Brussels, November 2013
30. @AureliePols
Typical personal data misconceptions
Very often present in technology companies
– We do not identify the user while using the data, so we have no
issues with Privacy law
– We only use the serial # of the users device, so the data is
anonymous and we have no issues with Privacy laws
– We encrypt the data so we are no longer
using/sending/receiving personal data
– We use hashes to replace all serial #, so the data is now
anonymous and we have no issues with Privacy laws
– We anonymize the data, so we are not using personal data
– We can use the user’s data for anything we want, as long as we
keep the data to ourselves
– Look: big name companies are doing the same, so we are ok
Slide borrowed from @simonhania from TomTom, IAPP congress Brussels, November
2013
31. @AureliePols
EU fines?
Spain: responsible for 80% of data protection fines in the EU
Source: http://i0.kym-
cdn.com/photos/images/newsfeed/00
0/242/381/63a.jpg
Source:
http://www.mindyourprivacy.com/downlo
ad/privacy-infographic.pdf
38. @AureliePols
Balancing Risks & Benefits
Risks
SaaS PIAs: Privacy
Impact Assessment
Security evaluation of
your own information
Nature of your own
data
Benefits
Price
Transfer of
responsibility?
Availability (BYOD,
strike, natural
disaster, …)
Source:
http://www.labeshops.com/image/cache/data/summitcollection/7918l-
lady-justice-3-feet-statue-800x800.jpg
39. @AureliePols
Compliance vs. Risk Assessments
• Achieving 100% compliance is a chimera
– Compliance is a journey, not a destination
– Level of required compliance linked to
• Sector
• Personal internal management
• Company risk profile
• Risk is a moving target
– Risk of being fined
– Risk of being breached
– Brand perception => subjective
40. @AureliePols
A simple example
PII viewer for Google Analytics
http://davidsimpson.me/pii-viewer-for-google-analytics/
Customer
DBData Collection
Data Visualization
Privacy Policy
Hosting
Security
Terms of Use
Access
Consent
FIPPs
Data
retention
period
(Hosting)
Security
Access
What data is Chrome sending?
Is your company accountable?
41. @AureliePols
Other ex.: BBVA Commerce 360
26M
transactions/day
25% of
marketshare for
Spain
Source:
http://www.slideshare.net/cib
bva/juan-carlos-plaza-explica-
los-proyectos-sobre-big-data-
de-bbva
43. @AureliePols
What to do?
1. Know your information structure (cloud)
– Can you exactly draw the Cloud supplier slide?
2. Cloud inventory (PIA)
– Provider (& sub-contractors)
– Location
• Cloud service HQ
• Servers
– Applicable law: our friend Snowden
– Physical location: earthquakes?
• Any incidents to report?
• In-house control access (risk)
• Terms & Conditions
– Information Security measures
– Related to Privacy
44. @AureliePols
What to do?
3. Know your Data structure: data inventory (cloud)
– (Do you know which data can be found where)?
– Have you reviewed your information security
measures?
– What happens in case of a breach?
4. Authorization required?
– Approval International Data Transfers (IDT)
– Safe Harbor
– Binding Corporate Rules (BCR)
– User consent
45. @AureliePols
Moving to the cloud
1. List your departments
2. What type of data needs to be moved?
3. What are your data risk levels?
– Low / Medium / High / Extremely High
4. What do you need for compliance?
Have a list of questions ready
to ask your cloud provider
except for the price!
49. @AureliePols
MYP Services
For Data Users
Risk Assessment to define maturity model (COBIT) and roadmap
Define processes to establish proper security measures and create policies to
structure these process
Audit the level of compliance of security measures that are in place
Train staff to align them with security plan while reducing the risk of suffering
a data breach
Define KPIs to adequately deploy a data governance program
50. @AureliePols
MYP Services
Analytics SaaS Providers
Advice during the procurement process to define the best provider in terms of
data security management and privacy compliance
Audit providers´ management of data and privacy
For Analytics vendors & agencies
WEMindYourPrivacy Seal
53. Aurélie Pols
Co-founder & Chief Visionary Officer
Mind Your Privacy & Mind Your Group
aurelie@mindyourprivacy.com
@aureliepols
Privacy in Digital Marketing:
Regulatory Threats vs. Data Opportunities
Berlin - June 2nd 2014
http://digitalanalyticshub.com/berlin2014/workshops/#ND68
Next full day workshop