De slide van de Future Proof Financial voor Fagro in Eindhoven

1. The Future Proof
Financial: FinTech
1

2. www.martijnzoet.com
martijn.zoet@zuyd.nl
martijn.zoet@edm-cc.nl
(@mzoet)
“Working together to develop and spread new insights
and solutions for practical problems.“
2

3. An Overview
3
(Copyright Facebook, 2017)
(Copyright Google, 2017)
(Ziwei Liu (刘子纬), 2017)
(Alex Kantrowittz, 2017)
(Copyright InsureAPP, 2017)
(Copyright Betterment, 2017)(The Canadian Press, 2016)(FinExtra, 2017)

4. 4

5. 5

6. https://www.youtube.com/watch?v=IQKsYXH2LCM
6

7. 7
(Macgregor, 2015)
(IBM, 2012)

8. 8

9. 9
( Copyrright Nvidea, 2017)

10. 10
(Broekhuizen ,2017)(Business Insider ,2017)

11. 11

12. 12
(Copyrights of logos are retained by their owners)

13. 13
(Copyrights of logos are retained by their owners)

14. 14
(Techcrunch ,2017)
(Kharpal ,2015)
(Koenie,2015) (Copyrights of logos are retained by their owners)

15. There Is a Fintech Startup for Almost Any Bank Service
(LTP – Sofia, 2016)
15

16. 16
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17. 17

18. 18
http://eur-lex.europa.eu/eli/reg/2016/679/oj

19. 19
https://www.internetconsultatie.nl/uitvoeringswetavg/details
Artikel 38.
Lid 3. Bij de geautomatiseerde
individuele besluitvorming als
bedoeld in het eerste lid deelt de
verwerkingsverantwoordelijke de
betrokkene de logica mee die ten
grondslag ligt aan de
geautomatiseerde verwerking van
hem betreffende gegevens.

20. 20
(https://www.betterment.com/)

21. 21
(https://www.kreditech.com/)

22. 22
(https://www.ing-diba.de/)

23. 23
(Keuning, 2017 )

24. (http://www.economist.com/blogs/economist-explains/2013/05/economist-explains-18)
24
(http://www.safaricom.co.ke/personal/m-pesa/do-more-with-m-pesa/m-shwari)

25. 25
(Brooker, 2015)

26. 26
(Copyrights of content and logos are retained by their owners)

27. (Chen, 2017)
27

28. (Fox, 2017)
28

29. 29
(Akan, 2016)

30. (Bain, 2016)
30

31. 31
Ontwikkeling van robotisering
De ontwikkeling van robotisering kent verschillende vormen van robots
Robots in auto fabrieken
Robots in winkels
Robots in de zorg
Robots in het ziekenhuis IBM Watson
Robots in de financiële functie
(KPN, 2017)

32. 32
Bottom-up approach mogelijkheden robotisering
Bottom-up approach
1. In gesprek gaan met managers over robotisering
2. Begrijpen van de activiteiten en mogelijkheden van
robotisering door in gesprek gaan met de kerngebruikers
3. Totaal overzicht opstellen per afdeling van de mogelijk te
robotiseren processen (werkclusters) en bijbehorende FTE’s
4. Selecteren van mogelijk te robotiseren activiteiten
5. Assessment van mogelijk te robotiseren processen, cross-check
met outside-in informatie
6. Business Case opstellen (Keuzes maken, communiceren en
verdedigen)
7. Roadmap met agile sprint planning vaststellen
Activiteiten binnen de SSO afdelingen
Mogelijkheden voor robotisering
Input voor Business Case
elimineren
standaardiseren
optimaliseren
(KPN, 2017)

33. APPENDIX: Selecteren van processen voor RPA
Processen kunnen worden geselecteerd door de waarde en complexiteit tegen elkaar
weg te zetten
High
Low
High Low
Complexiteit
Waarde
Roadmap
Priority
Automate
Now
Automation
Challenge
Automation
Opportunity
RPA Proces Selectie Matrix
 Is de data die gebruikt moet worden in grote mate
gestructureerd / gestandaardiseerd?
 Heeft het proces een repetitief karakter?
 Zijn er werkinstructies beschikbaar?
 Hoeveel applicaties worden er gebruikt?
 Is de input gestructureerd?
 Is de output gestructureerd?
 Zitten er veel/weinig changes op het proces?
Proces Selectie Criteria
Robotic Process Automation - Enabling the future of Finance 33
(KPN, 2017)

34. 34
(Reuters, 2016)
Al Bello/Getty Images for Octagon

35. 35
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36. Je verliest je baan
niet
36
Maar het werk
wordt anders

37. Wie heeft dit algoritme nog nooit toegepast?
37
Stap 1: Start
Stap 2: Creëer variabelen num1, num2, num3, num4, en som.
Stap 3: Lees waarden num1, num2, num3 en num4.
Stap 4: Tel num1, num2, num3, num4 op en wijs het resultaat aan som toe.
Stap 5: Toon som
Stap 6: Stop

38. Wat is algoritme?
38

39. Wie heeft dit algoritme nog nooit toegepast?
39
Stap 1: Start
Stap 2: Creëer variabelen num1, num2, num3, num4, en som.
Stap 3: Lees waarden num1, num2, num3 en num4.
Stap 4: Tel num1, num2, num3, num4 op en wijs het resultaat aan som toe.
Stap 5: Toon som
Stap 6: Stop

40. Wie heeft dit algoritme nog nooit toegepast?
40
i ← 1
while i < lengte(A)
j ← i
while j > 0 and A[j-1] > A[j]
swap A[j] and A[j-1]
j ← j - 1
end while
i ← i + 1
end while

41. Wie heeft dit algoritme nog nooit toegepast?
41
i ← 1
while i < lengte(A)
j ← i
while j > 0 and A[j-1] > A[j]
swap A[j] and A[j-1]
j ← j - 1
end while
i ← i + 1
end while

42. Wie heeft dit algoritme nog nooit toegepast?
42
xbya 




 2
)(
))((
xx
yyxx
b

43. Wie heeft dit algoritme nog nooit toegepast?
43
xbya 




 2
)(
))((
xx
yyxx
b

44. Wie heeft dit algoritme nog nooit toegepast?
44
(alphaism,2012)

45. 45
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Accounting
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Processing
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Accounting/
Reimbursemen
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Transaction processing External reporting
Purchase to paymentRecord to report (general accounting) Order to cash
Strategic
Planning
Budgeting &
Financial
Planning
Forecasting
Accounting/
Tax Policy
Internal Audit
Financial
Analysis
Internal
Consulting
Finance
Function
Management
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Performance
Management
Training &
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Liaison
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Revenue
Allocations
Performance
Measurement
Multi-
Dimensional
Reporting
Profit Center/
Customer/
Producer
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Divestitures
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Management
(CM)
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Mgmt.
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Business decision support Finance management
Planning Control
Management reporting Specialized expertise

46. 46
(Forrester, 2017)

48. Larry Page:“Artificial intelligence would be the ultimate version
of Google. The ultimate search engine that would understand
everything on the web. It would understand exactly what you
wanted and it would give you the right thing. We’re nowhere
near doing that now. However, we can get incrementally closer
to that, and that is basically what we’re working on.” –

49. Larry Page:“Artificial intelligence would be the ultimate version
of Google. The ultimate search engine that would understand
everything on the web. It would understand exactly what you
wanted and it would give you the right thing. We’re nowhere
near doing that now. However, we can get incrementally closer
to that, and that is basically what we’re working on.” –
Yann Lecun:“Most of human and animal learning is unsupervised
learning. If intelligence was a cake, unsupervised learning would be the
cake, supervised learning would be the icing on the cake, and
reinforcement learning would be the cherry on the cake. We know
how to make the icing and the cherry, but we don’t know
how to make the cake. We need to solve the unsupervised learning
problem before we can even think of getting to true AI.”
Jake Peterson: “90% of the data you collect will never be
actionable or even helpful.”
John Battelle:
“You happily give Facebook
terabytes of structured data about
yourself, content with the implicit
tradeoff that Facebook is going to
give you a social service that makes
your life better.”
Andrew Ng: No one knows what the right
algorithm is, but it gives us hope that if we can
discover some crude approximation of whatever
this algorithm is and implement it on a computer,
that can help us make a lot of progress.
49

50. 50

51. 51

52. 52
Kerngetal

53. 53

54. 54
Proces

55. 55
Proces

56. 56

57. 57
Beslissing

58. 58
Beslissing

59. 59

60. 1 2 3
4
60
(Copyright Photo: APG)

61. De Data-Driehoek
Data science cyclus
Intelligence cyclus
Ontwerp cyclus
61
Beslissing
Rapportage
(Feedback)
Analyse
(Feed-Forward)
C) Welke acties zijn er nodig?
D) Waar exact ligt het probleem?
B) Hoeveel, hoevaak en waar?
A) Wat heeft er plaats gevonden?
H) Hoe zorgen we ervoor dat dit plaats gaat vinden?
G) Wat is het beste dat er nu kan gebeuren?
F) Wat gebeurt er als deze trends doorzetten?
E) Waarom gebeurt dit?
Compliance cyclus
A) Decision Requirements
Model e.g.: DRD
A) Decision Mining
DDrummer
J) Wat is onze rechtsgelijkheid?
I) Welke beslissingen voldoen niet aan de normen?
Data
Compliance

62. Data science cyclus
Intelligence cyclus
Ontwerp cyclus
KerngetalProces
Own data
A) Proces Model
e.g.: BPMN
A) Fact Model
A) Process Mining
e.g.: Celonis
A) ‘Business Intelligence’
e.g.: QlikSense
Beslissing
Rapportage
(Feedback)
Analyse
(Feed-Forward)
C) Welke acties zijn er nodig?
D) Waar exact ligt het probleem?
B) Hoeveel, hoevaak en waar?
A) Wat heeft er plaats gevonden?
H) Hoe zorgen we ervoor dat dit plaats gaat vinden?
G) Wat is het beste dat er nu kan gebeuren?
F) Wat gebeurt er als deze trends doorzetten?
E) Waarom gebeurt dit?
Compliance cyclus
A) Decision Requirements
Model e.g.: DRD
A) Decision Mining
DDrummer
Customer data
Eco-
System data
J) Wat is onze rechtsgelijkheid?
I) Welke beslissingen voldoen niet aan de normen?
Compliance
De Data-Driehoek
62

63. 1 – Emotie, Moraal en Intelligentie
6 – Transparantie2 – Narrow versus Broad
63

64. 1 – Emotie, Moraal en
Intelligentie
64

65. 65

66. 66

67. 67
(Copyright Tesla, 2017)

68. 68
(http://moralmachine.mit.edu/)

69. 69
(Massoudi, 2012)

70. https://www.ted.com/talks/kevin_slavin_how_algorithms_shape_our_world?language=nl
70

71. 1 – Emotie, Moraal en Intelligentie
6 – Transparantie2 – Narrow versus Broad
71

72. 2 – Narrow versus Broad
72

73. 73

74. 74
(Copyright Hemdal, 1984) (Copyright C-2 Pictures, 2003)(Copyright Alcon Entertainment, 2014)

75. 75
(Beckett Mufson, 2017)

76. 76
(Beckett Mufson, 2017)

77. Classificeren Diagnoseren Voorspellen Monitoren Beoordelen
Ontwerpen
/
Configureren
Modelleren Plannen
Roosteren
(wel tijd)
Toewijzen /
Toekennen
(geen tijd)
Registratietaken en Kennistaken
Toevoegen
van gegevens
Wijzigingen
van gegevens
Verwijderen
van gegevens
Kennistaken
Registratietaken
Ontvangen
van gegevens
Presenteren
Gegevens
Verzenden
van gegevens
Communicatietaken
Opvragen
van gegevens
Ontvangen
gegevensverzoek
77

78. 78
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Card Admin
Treasury/ Trust
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Monthly/
Quarterly Close
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Accounting
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Planning
Forecasting
Accounting/
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Internal Audit
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Analysis
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Consulting
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Planning Control
Management reporting Specialized expertise

79. 79

80. 1 – Emotie, Moraal en Intelligentie
6 – Transparantie2 – Narrow versus Broad
80

81. 81

82. Espresso
Espresso
Espresso
Water
Espresso
Warme Melk
Americano Caffé Latte
Melkschuim
Kopje Koffie
82

83. 3. Taak
4. Voorspelbaarheid
5. Autonomie
Kopje Artificial Intelligence
83

84. Taak
Kopje Artificial Intelligence
84

85. 1 – Emotie, Moraal en Intelligentie
6 – Transparantie2 – Narrow versus Broad
85

86. 86

87. Voorspelbaarheid
Kopje Artificial Intelligence
87

88. Gedrag
Voorspelbaarheid
Autonomie
Gedrag
Voorspelbaarheid
Autonomie
Gedrag
Voorspelbaarheid
Autonomie
Gedrag
Voorspelbaarheid
Autonomie
(Copyright Blizzard, 2017)
Kopje Artificial Intelligence: Voorbeeld Spellen
88

89. Gedrag
Voorspelbaarheid
Autonomie
Gedrag
Voorspelbaarheid
Autonomie
Gedrag
Voorspelbaarheid
Autonomie
Gedrag
Voorspelbaarheid
Autonomie
(Copyright Blizzard, 2017)
Kopje Artificial Intelligence: Finance
89

90. 90
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Monthly/
Quarterly Close
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Reconciliation
Billing
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Reporting
Statutory
Reporting
Fixed Asset
Accounting
Tax Planning/
Accounting
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Processing
Accounts
Payable
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T&E
Accounting/
Reimbursemen
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Transaction processing External reporting
Purchase to paymentRecord to report (general accounting) Order to cash
Strategic
Planning
Budgeting &
Financial
Planning
Forecasting
Accounting/
Tax Policy
Internal Audit
Financial
Analysis
Internal
Consulting
Finance
Function
Management
Human
Performance
Management
Training &
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Liaison
Expense/
Revenue
Allocations
Performance
Measurement
Multi-
Dimensional
Reporting
Profit Center/
Customer/
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Management reporting Specialized expertise

91. 1 – Emotie, Moraal en Intelligentie
6 – Transparantie2 – Narrow versus Broad
91

92. 92

93. Autonomie
Kopje Artificial Intelligence
Niveau 1
Volledig uitgevoerd door een mens
Niveau 10
Volledig uitgevoerd door de machine.
93
Niveau 2
Niveau 3
Niveau 4
………
………
………

94. 1 – Emotie, Moraal en Intelligentie
6 – Transparantie2 – Narrow versus Broad
94

95. 6 – Transparantie
95

96. Transparantie
96
xbya 




 2
)(
))((
xx
yyxx
b
i ← 1
while i < lengte(A)
j ← i
while j > 0 and A[j-1] > A[j]
swap A[j] and A[j-1]
j ← j - 1
end while
i ← i + 1
end while

97. 1 – Emotie, Moraal en Intelligentie
6 – Transparantie2 – Narrow versus Broad
97

98. 98
Requisition
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Card Admin
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Monthly/
Quarterly Close
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Reconciliation
Billing
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Fixed Asset
Accounting
Tax Planning/
Accounting
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Processing
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Payable
Cash
Application
Collections
T&E
Accounting/
Reimbursemen
t
Bank
Reconciliation
Transaction processing External reporting
Purchase to paymentRecord to report (general accounting) Order to cash
Strategic
Planning
Budgeting &
Financial
Planning
Forecasting
Accounting/
Tax Policy
Internal Audit
Financial
Analysis
Internal
Consulting
Finance
Function
Management
Human
Performance
Management
Training &
Development
Business
Liaison
Expense/
Revenue
Allocations
Performance
Measurement
Multi-
Dimensional
Reporting
Profit Center/
Customer/
Producer
Profitability
Acquisitions &
Divestitures
Risk
Management
(CM)
Actuarial
Analysis/
Reserving (Ins)
Real Estate
Mgmt.
Project
Management
Business decision support Finance management
Planning Control
Management reporting Specialized expertise

99. 99
(copyright http://www.bitchcoin.biz/)

100. 100
(copyright http://www.marktplaats.nl/) (copyright https://openbazaar.org/)

101. 101
(copyright https://lazooz.net/)(copyright https://uber.com/)

102. 102
(copyright https://dropbox.com) (copyright https://storj.io)

103. 103

104. 104
all others must bring data

105. 105
The text on a Blockchain
transaction:
“In proof we trust”

106. 106

107. Een Normale Bank Transactie
Naam, Rek. Nr., Saldo
Naam, Rek. Nr., Saldo
Naam, Rek. Nr., Saldo
107

108. Een Normale Bank Transactie
Naam, Rek. Nr., Saldo
Naam, Rek. Nr., Saldo
Naam, Rek. Nr., Saldo
Naam, Rek. Nr., Saldo
Naam, Rek. Nr., Saldo
Naam, Rek. Nr., Saldo
108

109. Een Normale Bank Transactie
Naam, Rek. Nr., Saldo
Naam, Rek. Nr., Saldo
Naam, Rek. Nr., Saldo
Naam, Rek. Nr., Saldo
Naam, Rek. Nr., Saldo
Naam, Rek. Nr., Saldo
109

110. Een Normale Bank Transactie
Naam, Rek. Nr., Saldo Naam, Rek. Nr., Saldo
Vragen aan u:
Waardering;
Eigendom;
Bestaan;
Volledigheid;
Afgrenzing;
Accuratesse;
Rubricering;
Tijdigheid;
Continuïteit;
Juistheid.
110

111. 111

112. 112

113. 113
all others must bring data

114. 114
The text on a Blockchain
transaction:
“In proof we trust”

115. Een Normale BitCoin Transactie
115

116. Een Normale BitCoin Transactie
Naam, Rek. Nr., Saldo
Naam, Rek. Nr., Saldo
Naam, Rek. Nr., Saldo
Naam, Rek. Nr., Saldo
116

117. Een Normale BitCoin Transactie
Naam, Rek. Nr., Saldo
Naam, Rek. Nr., Saldo
Naam, Rek. Nr., Saldo
Naam, Rek. Nr., Saldo
117

118. 118

119. 119

120. Een vergelijking
Naam, Rek. Nr., Saldo Naam, Rek. Nr., Saldo
Vragen aan u:
Waardering;
Eigendom;
Bestaan;
Volledigheid;
Afgrenzing;
Accuratesse;
Rubricering;
Tijdigheid;
Continuïteit;
Juistheid.
Vragen aan u:
Waardering;
Eigendom;
Bestaan;
Volledigheid;
Afgrenzing;
Accuratesse;
Rubricering;
Tijdigheid;
Continuïteit;
Juistheid.
120

121. Ledger Capabilities Reference Model
5. Manage Consensus Mechanism
A. Record Management
2. Submit Transaction
B. Product Management
1.1 Design Business Rule Set
C. Identity Management
1. Manage Entities
D. Policy Management
2. Manage Participants
3. Manage Roles
1. Manage Access Control
2. Manage Privacy
3. Manage Consortium Rules
4. Manage Consensus Rules
1.2 Specify Business Rule Set
1.3 Verify Business Rule Set
1.4 Validate Business Rule Set
2. Deploy Smart Contract
4. Evaluate Smart Contract
5. Govern Smart Contract
3. Verify Transaction
4. Create Transaction Set
5. Submit Transaction Set
7. Accept Transaction Set
6. Reach Consensus
1. Create Transaction
E. Interledger Communication
1. Determine Interledger Address 2. Transfer Transaction 3. Convert Transaction
121
1. Design Smart Contract
3. Execute Smart Contract
3.1 Data Sensing
3.2 Execute Business Rule Set
3.3 Trigger Action / Send Event
4. Manage Assets

122. (A)
Distributed
Ledger
Smart
Contracts
NetworkAssets
registers is for a specific
Policy
applies
different
Interledger
Protocol
Roles
PrivacyConsensus
Mechanism
has a degree ofhas ahas a
applies
applies
Building blocks of a distrubuted ledger
122

123. 123
Kluis 1 Kluis 2
Sleutel van
kluis 1
Kluis 3
Sleutel van
kluis 2
Kluis 4
Sleutel van
kluis 3
Kluis 5
Sleutel van
kluis 4
Een keten van kluizen

124. 124
Iedereen zijn eigen Blockchain

125. 125
Iedereen zijn eigen Blockchain

126. 126
Evil Twins

127. 127

128. 128
Een werkende Blockchain

129. 129
Een werkende Blockchain
(A)
Distributed
LedgerMinen
Digitale
Berichten
Blocks
(Gehasthe) verzamelingen van
transacties

130. 130
In welke situaties biedt de Blockchain toegevoegde waarde?

131. (A)
Distributed
Ledger
Smart
Contracts
NetworkAssets
registers is for a specific
Policy
applies
different
Interledger
Protocol
Roles
PrivacyConsensus
Mechanism
has a degree ofhas ahas a
applies
applies
Vraag 1 – De Basis:
Heeft u een database nodig?
(Questions are based on multiple sources: Gideon, 2006; Del Castillo, 2016; Rizzo, 2016; Zoet, 2016)
131

132. (A)
Distributed
Ledger
Smart
Contracts
NetworkAssets
registers is for a specific
Policy
applies
different
Interledger
Protocol
Roles
PrivacyConsensus
Mechanism
has a degree ofhas ahas a
applies
applies
Vraag 2 – Het Netwerk:
Schrijven er meerdere partijen in
het netwerk naar de database?
132

133. (A)
Distributed
Ledger
Smart
Contracts
NetworkAssets
registers is for a specific
Policy
applies
different
Interledger
Protocol
Roles
PrivacyConsensus
Mechanism
has a degree ofhas ahas a
applies
applies
Vraag 3 – Het Netwerk:
Vertrouwen de partijen elkaar?
133

134. (A)
Distributed
Ledger
Smart
Contracts
NetworkAssets
registers is for a specific
Policy
applies
different
Interledger
Protocol
Roles
PrivacyConsensus
Mechanism
has a degree ofhas ahas a
applies
applies
Vraag 3 – Het Netwerk:
Vertrouwen de partijen elkaar?
Is het een database die
onder constante dreiging
van hackers staat?
Is de een grote kans tot vervalsing?
Is er een verhoogde kans op fraude?
134

135. (A)
Distributed
Ledger
Smart
Contracts
NetworkAssets
registers is for a specific
Policy
applies
different
Interledger
Protocol
Roles
PrivacyConsensus
Mechanism
has a degree ofhas ahas a
applies
applies
Vraag 4 – Rollen:
Is er een ‘trusted third party’
135

136. (A)
Distributed
Ledger
Smart
Contracts
NetworkAssets
registers is for a specific
Policy
applies
different
Interledger
Protocol
Roles
PrivacyConsensus
Mechanism
has a degree ofhas ahas a
applies
applies
Vraag 5 – Assets:
Is er ‘samenhang’ tussen de
transacties (assets)?
136

137. 137
Welcome to
Distributed Ledgers

138. (A)
Distributed
Ledger
Smart
Contracts
NetworkAssets
registers is for a specific
Policy
applies
different
Interledger
Protocol
Roles
PrivacyConsensus
Mechanism
has a degree ofhas ahas a
applies
applies
Vraag 6 – Rollen:
Wie valideren de transacties?
138

139. (A)
Distributed
Ledger
Smart
Contracts
NetworkAssets
registers is for a specific
Policy
applies
different
Interledger
Protocol
Roles
PrivacyConsensus
Mechanism
has a degree ofhas ahas a
applies
applies
Vraag 7 – Rollen en Consensus:
Waarom vertrouwen de
personen/organisaties die valideren ?
139

140. (A)
Distributed
Ledger
Smart
Contracts
NetworkAssets
registers is for a specific
Policy
applies
different
Interledger
Protocol
Roles
PrivacyConsensus
Mechanism
has a degree ofhas ahas a
applies
applies
Vraag 8 – Rollen en Assets:
Wie staat er in de ‘echte’ wereld achter
het grootboek?
140

141. www.martijnzoet.com
martijn.zoet@zuyd.nl
martijn.zoet@edm-cc.nl
(@mzoet)
“Working together to develop and spread new insights
and solutions for practical problems.“
141

142. Slide Photo Artist/Contributor
2 Tower Nimishgogri
2 Classroom Edwin11
2 Medical Tubs SNRE
47,48,50,53,56,
57
Decision Icon Icons8 (http://icons8.com)
47,48,50,53,56,
57
Process Icon Icons8 (http://icons8.com)
47,48,50,53,56,
57
Numbers Icon Icons8 (http://icons8.com)
47,48,50,53,56,
57
Sheriff Icon Icons8 (http://icons8.com)
60,61,68,69,76,7
7,81,82,87,88,90,
91,93,
Head Icon Icons8 (http://icons8.com)
63 Taxi Driver Jim Pennucci
80 Baby Kitt Walker
80 Car Damian Moryes
80 Monopoly Rossination
83 Iphone – Routeplanner Karlis Dambrans
84 Go Jaro Larnos
142
This presentation used photos and artwork offered under the creative commons license “attribution generic” . None of the artists /
licensors who created the work have endorsed me or my use of their work. The Creative Commons Photos can be found on
http://www.flickr.com/. Photos and artwork listed with a URL can be found on the specified URL. Photos and artwork not listed are
copyrighted by the author or 3rd parties.

143. Slide Photo Artist/Contributor
84 Chess Plffft
84 Poker Slgckgc
99 Front of a One Dollar Bill Sarah Corriher
100 Front of a one dollar bill Sarah Corriher
100 Back of a one dollar bill Sarah Corriher
101 Lego Block Ben Rimes
102 Kettle Waytru
105 Woman in White Rennesi
105 Woman in Black PumpkinCat
105 Business Man Hamed Saber
105 Elderly Man Roger Blackwell
105 Safe (DesignContest – www.designcontest.com)
106, 107, 108,
110, 111
Woman in White Rennesi
106, 107, 108,
110, 111
Business Man Hamed Saber
106, 107, 108,
110, 111
Elderly Man Roger Blackwell
106, 107, 108,
110, 111
Safe (DesignContest – www.designcontest.com)
143
This presentation used photos and artwork offered under the creative commons license “attribution generic” . None of the artists /
licensors who created the work have endorsed me or my use of their work. The Creative Commons Photos can be found on
http://www.flickr.com/. Photos and artwork listed with a URL can be found on the specified URL. Photos and artwork not listed are
copyrighted by the author or 3rd parties.

144. Slide Photo Artist/Contributor
105,107,108,110,
111
Written Note Dirk Haun
105,
106,108,110,111
Safe Lock Oxygen Team IconSet (http://www.iconarchive.com/)
108,110,111 Calculator Oxygen Team IconSet (http://www.iconarchive.com/)
109 Puzzle Rob Pongsjapan
112 Myst Corin@ 2008
113 Database Oxygen Team IconSet (http://www.iconarchive.com/)
114 Pencils FHG Photo
115 Group of people Joi ITO
116 Group of people Joi ITO
117 Badge/Shield Banspy
118 Birds Sue Cantan
119 Boy in Door Georgie Pauwels
120 Business Woman Victor 1558
121 Business Woman Victor 1558
122 Soldiers Usasoc News Service
123 Tower Nimishgogri
144
This presentation used photos and artwork offered under the creative commons license “attribution generic” . None of the artists /
licensors who created the work have endorsed me or my use of their work. The Creative Commons Photos can be found on
http://www.flickr.com/. Photos and artwork listed with a URL can be found on the specified URL. Photos and artwork not listed are
copyrighted by the author or 3rd parties.

145. Slide Photo Artist/Contributor
123 Classroom Edwin11
123 Medical Tubs SNRE
145
This presentation used photos and artwork offered under the creative commons license “attribution generic” . None of the artists /
licensors who created the work have endorsed me or my use of their work. The Creative Commons Photos can be found on
http://www.flickr.com/. Photos and artwork listed with a URL can be found on the specified URL. Photos and artwork not listed are
copyrighted by the author or 3rd parties.