Præsentation fra IBM Smarter Business 2012

1. © 2012 IBM Corporation

2. Smarter Cities & Public Safety
More Data – Less Criminal Actions
More Data – Less Criminal Actions
Presenter name: Mauritz Gillberg/ Sturt Ison
Job title: i2 Sales Lead Nordics/ i2 Techn Sales North Europe
Company name: IBM i2

3. Public Safety - Today’s Challenges
• Global Instability
• Terrorism and asymetric threats
• Increased crossborder criminality
• Financial fraud, card skimming etc
• More data everywhere

4. The Challenge: Bring Together a Large Volume and Variety of Data
to Find New Insights
Multi-channel customer
sentiment and experience a
analysis
Detect life-threatening
conditions at hospitals in
time to intervene
Predict weather patterns to plan
optimal wind turbine usage, and
optimize capital expenditure on
asset placement
Make risk decisions based on
real-time transactional data
Identify criminals and threats
from disparate video, audio,
and data feeds
4

5. Public Safety is wide
National Law Private
Defense Government
Security Enforcement Sector
Counter Terrorism Establishing Tactical Lead Security Industry Oversight
Counter Intelligence Civilian Structures Generation Investigations & Compliance
Counter Intelligence Counter Terrorism Industry Oversight Cybercrime
Intelligence Analysis
Intelligence Analysis Major & Compliance Securities
Border Security Investigations
Target Analysis Cybercrime Investigations
Cyber Risk and Defense Organized Crime
Risk Management Anti-Money
Peacekeeping Neighborhood/ Laundering
Community Policing Anti-Money
Force Protection
Laundering Fraud Investigation
Pattern of Life Public Order/Major
Analysis Event Management Fraud Investigation
Human Terrain Volume Crime
Mapping Fusion Centers

6. Criminal Activities and Fraud Spans Every Sector
IBM i2 Fraud Intelligence Analysis
Cyber Fraud
Organized Crime

7. IBM’s Solutions around Smarter Cities help ensure the
safety and security of citizens, businesses, and
governments
Predictive analytics Data analytics In Edmonton,
helped slash helped cut crime police respond to
Richmond’s crime crimes more
35% in NYC effectively with near
rate by 40% real-time
in one year NYPD officers have information
mobile access to 120
million criminal complaints,
Madrid reduced arrests CPP increased
emergency response and 911 records fraud detection by
time by 25% 50%

8. Criminal and Fraud analysis across the fraud lifecycle
Investigate Prevent
Case management, Report/ Prevent the issuance of
visualization and Monitor Model the policy if it appears the
analysis tools to aid main purpose of the
investigators in building policy/account is to
a case against Investigate Prevent provide benefit to a
fraudsters. fraudster
Build a case for Stop fraud before it
prosecution or denial is reported
Today: Special of benefits Today: Little is done to
investigations unit with prevent fraud from
manual adjusters occurring
Discover Detect
Continuous comparison
Discover Fraudster
Detect Detect if a claim,
of claim or transaction payment or other
Discover fraud after Detect fraud once it is
data to the data of it occurs transaction is likely a
reported – and react
cases known to be accordingly
willful act to achieve
fraudulent in order to financial gain through
identify fraud that was misrepresentation
not previously detected and/or falsification;
and take steps to stop
or send to Investigation
Today: Not really done Today: Relies heavily
on people to detect
Learn

9. Investigative Challenges

10. Required Capabilities
Visual Analysis & Collaboration
Operational dashboards, workflow, case adjudication
Workflow & Case
Management Visualization &
Operational Link Analysis
Dashboards
Analytics Layer
Intelligence, Descriptive & Predictive Analytics against
structured, semi-structured and unstructured information
Descriptive and Content & Streams
Predictive Sentiment Analytics
Analytics Analytics
Information Sharing
Trusted Information Analysis
Repository
Establish, Manage, Share & Deliver information that
is accurate, complete, in context and insightful
Persistent
Relationship
Awareness
ETL Data on Demand Data Quality Data Delivery
Source Systems
Structured & Unstructured Content

11. How Intelligence Analysis helps Predictive
Analytics
• Delivers more insight into
the relationships between
data points
– Model does not show
correlations between
individuals
 Visualizes connections that
the predictive model cannot
 Allows analysts to be more
effective – ability to receive
deeper insight into
investigation process
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12. Understanding events over time

13. Understand Social Networks – rapid ring leader
discovery

14. Reveal and understand complex relationships

15. Understand patterns of behaviour and focus

16. Examples
• Real world data
• Messy
• Large, really large
• Phone calls
• Transactions

17. If you had a day...

18. IBM Intelligence Analysis, in summary
• Rapidly creates visual and actionable intelligence
• Automates manual analysis methods
• Quickly identifies patterns and relationships in large
complex data that might otherwise be missed
• Skilled resources spend more time investigating and
analyzing – close cases faster
• Uses the customers existing infrastructure