1 1 Increasing Collaboration to Maximise the use of Financial Intelligence and Disable Terrorism Dr Maria Milosavljevic Chief Innovation Officer
Maria Milosavljevic, AUSTRAC, Presentation at Chief Data & Analytics Officer Forum, Melbourne
Apr 14, 2017
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1 1
Increasing Collaboration to Maximise the use of Financial Intelligence
and Disable Terrorism
Dr Maria Milosavljevic Chief Innovation Officer
2 2
OUR MISSION
Detect, deter and disrupt money laundering and
terrorism financing risks and threats that affect
Australia’s financial system, and contribute to the growth of Australia’s
economy
3 3
14,058
About AUSTRAC
300% Growth in TF SMRs
83 International Exchange
Agreements
$2.5 billion
Additional
Tax
Assessments
over 5 years
FATF
EGMONT GROUP
Asia Pacific Group
Regional CTF
Summit
Reporting entities
AML/CTF
Review
84 Recommendations
Public
Private
NFP
Academia
4 4
Where are we?
5 5
Our global environment is changing at an unprecedented rate
NATIONAL AND GLOBAL SECURITY
300% AUSTRAC – RECEIPT OF TERRORISM
REPORTING 2015
ORGANISED CRIME $36b COST TO AUSTRALIA ANNUALLY
200 + COUNTRIES INVOLVED
IN PANAMA PAPERS
CORRUPTION
1st NUMBER ONE ECONOMIC CRIME IN
AUSTRALIA 2016
CYBER CRIME
6 6
GLOBALISATION 3.2b PEOPLE WITH
INTERNET ACCESS 2015
DIGITAL TRANSFORMATION 115k
AVG. BITCOIN TRANSACTIONS PER DAY 2015
GROWING REPORTING VOLUMES
100m AVG. AUSTRAC REPORTS
PER YEAR
TECHNOLOGY DISRUPTION $12b
INVESTED GLOBALLY in FINTECHS 2015
7 7
Where do we want to be?
8 8
Collaboration and information-sharing with the private sector is also critical to effectively combat serious and organised crime.
Foster and enhance international co-operation and collaboration.
…a simpler and streamlined AML/CTF regime that makes better-use of the risk-based approach to regulatory relief.
…AML/CTF regime that recognises the pivotal role of the private sector in the detection and prevention of criminality and seeks to leverage this expertise by building trusted partnerships for the sharing of financial intelligence.
Statutory Review of the Act
9 9
Our Vision
Building the Financial Intelligence
Picture together - law enforcement,
national security, regulators, private
sector in partnership
Increased efficiency and effectiveness
at detecting, preventing and
disrupting financial crime
Timely sharing of actionable
intelligence
Targeting risks on a global scale.
“
”
“What binds us is countering
financial crime. This is our
collaboration touch point” -- Paul Jevtovic, CEO
10 10
Benefits sought
Improved risk prevention, detection & response globally
Actionable intelligence
Rapid data fusion
Resilient systems
Smart systems
Sustainability
Shared outcomes
11 11
The way we work needs to fundamentally transform
Disrupt
Discover Understand
12 12
What do we need to get there?
13 13
Transformative Relationships
Whole of government
Public-private partnerships
14 14
Sustainable
business model
Investment channels
Public, private, NFP, academic
15 15 Centre of Excellence
16 16
How do we design & build
this?
17 17
Rate of change
Ava
ila
bility
Feedback loops
Automated unit tests
Automated acceptance tests
Automated capacity tests
Co-design with users
Exploring
Showcase
Production behavior analysis
Users
Our Program Transforming AUSTRAC’s delivery capability
Continuous delivery
Increasing delivery velocity
Delivering value to users quickly
Improving ROI
Earlier feedback
Feedback loops
Shifting the quality curve
allowing experimentation while
maintaining service level
objectives.
18 18
Security
Privacy
Sovereignty Commercial
in confidence
Open data
The world we live in
19 19 Global problems need global solutions
20 20
Deep Collaboration
21 21
Share with intent
22 22
Disruptive Innovation
23 23
App Store Marketplace
Business Architecture Concept
24 24
You can also
add quotes to
your images…
25 25
“Whatever system we design will already be imperfect, and it will
become out of date in 3 years’ time. We need to build systems that
rely on inexpensive, loosely coupled small components with
standard interfaces that can be easily swapped in and out.”
26 26
Data lake inflows
Customers
Data marts
Visualisation
Network discovery
raw data
automatic data extraction and fusion Dive in and play
Machine learning
Advanced Analytics Concept
knowledge generated by human-machine interaction
27 27
More… with less
Faster processes
Direct access
Eliminating frustration
Messages not lost in
translation
28 28
What does this look like?
29 29
Success factors
Collaboratively align the goals across the business
User-experience first
Co-design
Fail fast & forward
Get out of the way
Break down silos
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