Presentation given by Chris Taggart of OpenCorporates at the Open Knowledge Festival, September 2012, on the importance of open data and corporate transparency in the fight against corruption, fraud, money laundering and organised crime

1. Corruption,
& Open Data
Corporate Transparency
http://www.flickr.com/photos/zomgitsbrian/4042100914

2. We live in a highly complex,
massively interconnected,
corporate world

5. Companies no
longer look like this

6. Companies no
longer look like this

7. Companies no
longer look like this
nor even like this

9. But
like
this

10. But
like
this
or like this

11. But
like
this
or like this

12. And they are more complex
by the day

13. And they are more complex
by the day
Growing in scale – not 10s of legal entities but 1000s

14. And they are more complex
by the day
Growing in scale – not 10s of legal entities but 1000s
Growing in speed – we are seeing the beginnings of
high-frequency company formation

15. And they are more complex
by the day
Growing in scale – not 10s of legal entities but 1000s
Growing in speed – we are seeing the beginnings of
high-frequency company formation
Growing in opacity – use of secrecy jurisdictions and
off-register entities to provide firewalls to tax, regulation,
information

16. And they are more complex
by the day
Growing in scale – not 10s of legal entities but 1000s
Growing in speed – we are seeing the beginnings of
high-frequency company formation
Growing in opacity – use of secrecy jurisdictions and
off-register entities to provide firewalls to tax, regulation,
information
Growing in complexity – not a hierarchy but a complex,
sometimes even circular network of entities

17. And they are more complex
by the day
Growing in scale – not 10s of legal entities but 1000s

18. And they are more complex
by the day
Growing in scale – not 10s of legal entities but 1000s
Growing in speed – we are seeing the beginnings of
high-frequency company formation

19. And they are more complex
by the day
Growing in scale – not 10s of legal entities but 1000s
Growing in speed – we are seeing the beginnings of
high-frequency company formation
Growing in opacity – use of secrecy jurisdictions and
off-register entities to provide firewalls to tax, regulation,
information

20. And they are more complex
by the day
Growing in scale – not 10s of legal entities but 1000s
Growing in speed – we are seeing the beginnings of
high-frequency company formation
Growing in opacity – use of secrecy jurisdictions and
off-register entities to provide firewalls to tax, regulation,
information
Growing in complexity – not a hierarchy but a complex,
sometimes even circular network of entities

21. guys...
Which is great for the bad
http://www.flickr.com/photos/vincentsl/3543888150

22. ...because
criminal
activity is
a result of
http://www.flickr.com/photos/sepehrehsani/5766453552
cost-
benefit
analysis

23. http://www.cbp.gov/xp/cgov/newsroom/news_releases/archives/
2009_news_releases/september_2009/09122009.xml
How much can we make?

24. Will we get caught?
http://en.wikipedia.org/wiki/File:Viktor_Bout_Extradited_to_US.jpg

25. What’s the downside?
http://www.flickr.com/photos/timpearcelosgatos/3558607900

26. This matters
http://www.flickr.com/photos/propagandatimes/5242113537

27. Corruption
This matters
http://www.flickr.com/photos/propagandatimes/5242113537

28. Corruption
This matters
http://www.flickr.com/photos/propagandatimes/5242113537

29. Fraud
Corruption
This matters
http://www.flickr.com/photos/propagandatimes/5242113537

30. Fraud
Corruption
Money laundering
This matters
http://www.flickr.com/photos/propagandatimes/5242113537

31. Fraud
Corruption
Money laundering
This matters
http://www.flickr.com/photos/propagandatimes/5242113537

32. This matters
Corruption
Fraud
Money laundering
Organised crime
http://www.flickr.com/photos/propagandatimes/5242113537

33. “Out of 150
large-scale
corruption
cases the
majority used
companies to
hide the
money trail”

34. So what has open data got
to do with it?

35. Complexity is good (if you
want to avoid detection)
http://www.flickr.com/photos/jamescridland/613445810
It’s easy for the bad guys
to get lost in the crowd

36. “While bad behaviour does
follow the shadows, there’s
a huge difference between
huddling in corners and
having a riot in the darkened
streets” – John Wonderlich, Sunlight Foundation

37. A concrete example
AsiaUniversalBank –
Kyrgystan’s largest bank
Not just a small bank in
a far off country
Fully connected to the
world’s financial system
3 US senators on the
board

38. A concrete example
Leaks & accusations of
insolvency & money-
laundering, following a
revolution
A superb investigation
by Global Witness led to
companies in New
Zealand, UK, etc...
Companies with
shareholders who had
been dead even before
the formation

39. The lesson (for criminals)
Absent of...
...a revolution
...leaks
...a long-running
investigation by a
well-resourced NGO
you’re safe!

40. We’re looking for needles in
a haystack, and need open
data to reduce the problem
to manageable proportions

41. This is where the watchdogs
(are supposed to) come in?

42. This is where the watchdogs
(are supposed to) come in?
NGOs? Don’t get data

43. This is where the watchdogs
(are supposed to) come in?
NGOs? Don’t get data
Government? Limited by jurisdiction and mindset

44. This is where the watchdogs
(are supposed to) come in?
NGOs? Don’t get data
Government? Limited by jurisdiction and mindset
Data journalists? Not enough of them and don’t
understand the subject

45. This is where the watchdogs
(are supposed to) come in?
NGOs? Don’t get data
Government? Limited by jurisdiction and mindset
Data journalists? Not enough of them and don’t
understand the subject
Citizens/good business? Don’t have the tools/
resources

46. This is where the watchdogs
(are supposed to) come in?
NGOs? Don’t get data
Government? Limited by jurisdiction and mindset
Data journalists? Not enough of them and don’t
understand the subject
Citizens/good business? Don’t have the tools/
resources
And all have a problem getting the
data (especially in a usable form)

48. So open data is not alone
enough

49. So open data is not alone
enough

50. So open data is not alone
enough
We need skills,
understanding, incentives

51. So open data is not alone
enough
We need skills,
understanding, incentives

52. So open data is not alone
enough
We need skills,
understanding, incentives
But without it we are sunk

53. We also need to make a
distinction between the
transparent corporate world
and the opaque one – the
‘dark corporate web’

54. So how do the Open
Government Partnership
countries score for access
to company data?

55. So how do the Open
Government Partnership
FA IL!for access
countries score
to company data?

56. 4 key measures

57. 4 key measures
Basic search: can you search the company register
freely, without charge and without registration
Licence: Is there a licence that allows open reuse of
the information
Data: Is the information available as open data as a
data dump or an API
Depth: Is there sufficient information to get a true
picture of the company and those who control it –
directors, significant shareholdings, and statutory filings

58. The results were not good...

59. The results were not good...

60. OpenCorporates

61. A simple (huge) goal: an entry (and URI) for
every corporate legal entity in the world

62. A simple (huge) goal: an entry (and URI) for
every corporate legal entity in the world
URI is based on the company register
ID, meaning it’s open and IP-free

63. A simple (huge) goal: an entry (and URI) for
every corporate legal entity in the world
URI is based on the company register
ID, meaning it’s open and IP-free

64. A simple (huge) goal: an entry (and URI) for
every corporate legal entity in the world
URI is based on the company register
ID, meaning it’s open and IP-free

65. A simple (huge) goal: an entry (and URI) for
every corporate legal entity in the world
URI is based on the company register
ID, meaning it’s open and IP-free

66. A simple (huge) goal: an entry (and URI) for
every corporate legal entity in the world
URI is based on the company register
ID, meaning it’s open and IP-free
Also i
trade mpor
marks ting p
officia , gove ublic data
l regis rnme
ters & nt spe –
gazet nding
te not ,
ices..
.

70. All Op
enly L
free re icens
use, e ed, al
ven c lowin
omm g
ercial
ly

71. 5 core uses

72. 1. An open identifying system

73. 1. An open identifying system
URIs can be used as common identifiers among a
variety of organisations

74. 1. An open identifying system
URIs can be used as common identifiers among a
variety of organisations
Can be used without reference to OpenCorporates

75. 1. An open identifying system
URIs can be used as common identifiers among a
variety of organisations
Can be used without reference to OpenCorporates
Because they map to the id issued by the company
register the corresponding entry in the registry (and
associated info) can be found, and vice versa

76. 1. An open identifying system
URIs can be used as common identifiers among a
variety of organisations
Can be used without reference to OpenCorporates
Because they map to the id issued by the company
register the corresponding entry in the registry (and
associated info) can be found, and vice versa
Fits the new EU Business Vocabulary

77. 1. An open identifying system
URIs can be used as common identifiers among a
variety of organisations
Can be used without reference to OpenCorporates
Because they map to the id issued by the company
register the corresponding entry in the registry (and
associated info) can be found, and vice versa
Fits the new EU Business Vocabulary
Can even by used for companies in jurisdiction we
haven’t yet imported

78. 2. The simple search

79. 2. The simple search
Not to be underestimated

80. 2. The simple search
Not to be underestimated

81. 2. The simple search
Not to be underestimated
Massively reduces friction
(how long will it take you
to find and search
multiple jurisdictions)

82. 2. The simple search
Not to be underestimated
Massively reduces friction
(how long will it take you
to find and search
multiple jurisdictions)

83. 2. The simple search
Not to be underestimated
Massively reduces friction
(how long will it take you
to find and search
multiple jurisdictions)
Allows what if questions

84. 2. The simple search
Not to be underestimated
Massively reduces friction
(how long will it take you
to find and search
multiple jurisdictions)
Allows what if questions
Potentially generates
stories in its own right

85. 2. The simple search
Not to be underestimated
Massively reduces friction
(how long will it take you
to find and search
multiple jurisdictions)
Allows what if questions
Potentially generates
stories in its own right

86. 3. Source for additional info

87. 3. Source for additional info
Addresses, filings,
status, websites...

88. 3. Source for additional info
Addresses, filings,
status, websites...

89. 3. Source for additional info
Addresses, filings,
status, websites...
Intl trademarks, UK
govt spending, official
notices, health & safety
violations...

90. 3. Source for additional info
Addresses, filings,
status, websites...
Intl trademarks, UK
govt spending, official
notices, health & safety
violations...

91. 3. Source for additional info
Addresses, filings,
status, websites...
Intl trademarks, UK
govt spending, official
notices, health & safety
violations...
Other IDs: SEC, CAGE,
etc – allows reverse
mapping queries, e.g.
show me legal entitity
mapped to a CIK code

92. 4. Reconciliation
(matching names to legal entities)
Clean up messy
company names
(& prev names)
to legal entity,
and from there
to other data
Google Refine
reconciliation
service (specific
to jurisdiction)

93. 5. The platform

94. 5. The platform
API: allows all
information to be
retrieved as data,
even searches

95. 5. The platform
API: allows all
information to be
retrieved as data,
even searches

96. 5. The platform
API: allows all
information to be
retrieved as data,
even searches
Users can now
add data too

97. 5. The platform
API: allows all
information to be
retrieved as data,
even searches
Users can now
add data too

98. 5. The platform
API: allows all
information to be
retrieved as data,
even searches
Users can now
add data too

99. 5. The platform
API: allows all
information to be
retrieved as data,
even searches
Users can now
add data too
Coming soon: the
option to match
data to
companies

100. 5. The platform
API: allows all
information to be
retrieved as data,
even searches
Users can now
add data too
Coming soon: the
option to match
data to
companies

101. New feature: directors/officers
We’ve just
started
importing &
indexing
company
directors &
officers,
allowing search
by name, &
finding links
between them
and other
companies

102. New feature: directors/officers
We’ve just
started
importing &
indexing
company
directors &
officers,
allowing search
by name, &
finding links
between them
and other
companies

103. New feature: directors/officers
We’ve just
started
importing &
indexing
company
directors &
officers,
allowing search
by name, &
finding links
between them
and other similarly named
companies

104. New feature: directors/officers
We’ve just
started
importing &
indexing
company
directors &
officers,
allowing search
by name, &
other resources
finding links
between them
and other similarly named
companies

105. New feature: shareholdings
First stage in
mapping out
corporate
‘hierarchies’
A highly
complex
subject and one
not well
understood
even by many
regulators

106. New feature: shareholdings
First stage in
mapping out
corporate
‘hierarchies’
A highly
complex
subject and one
not well
understood shareholders
even by many
regulators

108. tions
isdic tes
0 jur
nies in 5 26 US sta
compa clud ing
5million In
wov er 4
No