Presentation on Big Data & Algorithms in (Fair) Consumer Finance at Computers, Privacy and Data Protection (CPDP 2017) Panel on ‘Privacy, Data Protection, and the Governance of Algorithms’ https://youtu.be/akEg3Qrkbl0 Catherine G. van Hoogstraten, Digital Governance, Information Technology Law & Policy & Cybersecurity Advisor, Researcher & Lecturer at the Cybersecurity Program -Webster University(Leiden). Lecturer at the Faculty of Public Management, Law and Security - The Hague University of Applied Sciences. Former expert member of the Financial Services User Group(FSUG)-European Commission T: @CatherineGvh

1. Big Data & Algorithms in (Fair)
Consumer Finance
Catherine Garcia van Hoogstraten, Digital Governance, Information
Technology Law & Policy & Cybersecurity Advisor, Researcher &
Lecturer at the Cybersecurity Program -Webster University(Leiden)
Former expert member of the Financial Services User Group(FSUG)-
European Commission
T: @CatherineGvh
George Herbert Walker
School of Business & Technology
CPDP 2017 Panel on ‘Privacy, Data
Protection, and the Governance of
Algorithms’
https://youtu.be/akEg3Qrkbl0

2. Big Data and Algorithms in Consumer Finance
Potential Impacts & Benefits
 Speed up access to financial P’s & S’s
 Financial advice guidance
 Budgetary management
 Preventing over-indebtedness
 Identify fraud, money-laundering, bribery and other
corrupt practices
FSUG-EC (June 2016) Assessment of current and future
impact of Big Data on Financial Services
Catherine Garcia van Hoogstraten, Digital Governance, Information Technology Law & Policy & Cybersecurity
advisor, researcher & lecturer at the Cybersecurity Program -Webster University(Leiden). Lecturer at the
Faculty of Public Management, Law and Security - The Hague University of Applied Sciences . Former
expert member of the Financial Services User Group(FSUG)- European Commission T: @CatherineGvh

3. Detrimental effects of automated decisions applied
in algorithmic creditworthiness assessment requires
adaptive regulation:
 Accurate predictability of future behavior
 Risk profiling assessment
 Algorithmic decision making transparency
 Biased or discriminatory outcomes
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Big Data and Algorithms in Consumer Finance
Catherine Garcia van Hoogstraten, Digital Governance, Information Technology Law & Policy & Cybersecurity
advisor, researcher & lecturer at the Cybersecurity Program -Webster University(Leiden). Lecturer at the
Faculty of Public Management, Law and Security - The Hague University of Applied Sciences . Former
expert member of the Financial Services User Group(FSUG)- European Commission T: @CatherineGvh

4. Automated Decisions applied in Algorithmic
Creditworthiness Assessment
Conditions that must be met for the Art. 22(1) GDPR to
apply:
1. there must be a decision;
2. that decision is based solely on automated data
processing;
3. the data processed for the decision are intended to
evaluate certain personal aspects (creditworthiness) of
the person concerned;
4. the decision must have legal or other significant
effects for the person(unfair discrimination due to the
denial of credit)
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Catherine Garcia van Hoogstraten, Digital Governance, Information Technology Law & Policy & Cybersecurity
advisor, researcher & lecturer at the Cybersecurity Program -Webster University(Leiden). Lecturer at the
Faculty of Public Management, Law and Security - The Hague University of Applied Sciences . Former
expert member of the Financial Services User Group(FSUG)- European Commission T: @CatherineGvh

5. Sources of Bias in the Algorithmic System
 Input
 Training
 Programming
Algorithms that use Big Data techniques for
underwriting consumer credit can be vulnerable
to all three of these types of bias risks.
5
White & Case (2017) Algorithms and bias: What lenders need to know
Catherine Garcia van Hoogstraten, Digital Governance, Information Technology Law & Policy & Cybersecurity
advisor, researcher & lecturer at the Cybersecurity Program -Webster University(Leiden). Lecturer at the
Faculty of Public Management, Law and Security - The Hague University of Applied Sciences . Former
expert member of the Financial Services User Group(FSUG)- European Commission T: @CatherineGvh

6. Impact of Bias in the Algorithmic Creditworthiness
Assessment
 Big Data analytics based in nontraditional data
 Nontraditional data sources: databases containing
internet search histories, shopping patterns, social
media activity etc
 Denial is the output from an opaque algorithm
analyzing nontraditional data= unfair or
discriminatory lending decisions
 Challenges in translating algorithmic decisions when
large potential borrowers are denied credit.
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Catherine Garcia van Hoogstraten, Digital Governance, Information Technology Law & Policy & Cybersecurity
advisor, researcher & lecturer at the Cybersecurity Program -Webster University(Leiden). Lecturer at the
Faculty of Public Management, Law and Security - The Hague University of Applied Sciences . Former
expert member of the Financial Services User Group(FSUG)- European Commission T: @CatherineGvh

7. The right to learn the logic behind processing
Right of access by the data subject Art. 15(h)
GDPR about:
 The existence of automated decision-making
 Meaningful information about the logic
involved and
 The significance and consequences of such
processing for the data subject.
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Catherine Garcia van Hoogstraten, Digital Governance, Information Technology Law & Policy & Cybersecurity
advisor, researcher & lecturer at the Cybersecurity Program -Webster University(Leiden). Lecturer at the
Faculty of Public Management, Law and Security - The Hague University of Applied Sciences . Former
expert member of the Financial Services User Group(FSUG)- European Commission T: @CatherineGvh

8. Legal and Tech challenges ahead
 Profiling and monitoring of individuals by automated
machines
 Transparencyof automated decisions
 Supervision of automated decisions taken by
autonomous machines when collecting personal data
 Accountability of the algorithm design
 Test and monitor the algorithms
 Maintaining human oversight, comprehension and control of
emerging AI systems should be at the core of the technology
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Catherine Garcia van Hoogstraten, Digital Governance, Information Technology Law & Policy & Cybersecurity
advisor, researcher & lecturer at the Cybersecurity Program -Webster University(Leiden). Lecturer at the
Faculty of Public Management, Law and Security - The Hague University of Applied Sciences. Former
expert member of the Financial Services User Group(FSUG)- European Commission T: @CatherineGvh
George Herbert Walker
School of Business & Technology