© 2012 IBM Corporation

Smarter Cities & Public SafetyMore Data – Less Criminal Actions

More Data – Less Criminal Actions

Presenter name: Mauritz Gillberg/ Sturt IsonJob title: i2 Sales Lead Nordics/ i2 Techn Sales North EuropeCompany name: IBM i2

Public Safety - Today’s Challenges

• Global Instability• Terrorism and asymetric threats• Increased crossborder criminality• Financial fraud, card skimming etc• More data everywhere

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The Challenge: Bring Together a Large Volume and Variety of Data to Find New Insights

Identify criminals and threats from disparate video, audio, and data feeds

Make risk decisions based on real-time transactional data

Predict weather patterns to plan optimal wind turbine usage, and optimize capital expenditure on asset placement

Detect life-threatening conditions at hospitals in time to intervene

Multi-channel customer sentiment and experience a analysis

Public Safety is wideGovernment

Law Enforcement

DefensePrivate Sector

National Security

Counter Terrorism

Counter Intelligence

Intelligence Analysis

Border Security

Cyber Risk

Establishing Civilian Structures

Counter Intelligence

Intelligence Analysis

Target Analysis and Defense

Peacekeeping

Force Protection

Pattern of Life Analysis

Human Terrain Mapping

Tactical Lead Generation

Counter Terrorism

Major Investigations

Organized Crime

Neighborhood/ Community Policing

Public Order/Major Event Management

Volume Crime

Fusion Centers

Security Investigations

Industry Oversight & Compliance

Cybercrime

Risk Management

Anti-Money Laundering

Fraud Investigation

Industry Oversight & Compliance

Cybercrime

Securities Investigations

Anti-Money Laundering

Fraud Investigation

Criminal Activities and Fraud Spans Every Sector

IBM i2 Fraud Intelligence Analysis

Cyber FraudCyber Fraud

Organized CrimeOrganized Crime

IBM’s Solutions around Smarter Cities help ensure the safety and security of citizens, businesses, and governments

Madrid reduced emergency response

time by 25%

Predictive analytics helped slash

Richmond’s crime

rate by 40% in one year

CPP increased fraud detection by

50%

In Edmonton, police respond to

crimes more effectively with near

real-time information

Data analytics helped cut crime

35% in NYC

NYPD officers have

mobile access to 120

million criminal complaints, arrests

and 911 records

PreventPrevent the issuance of the policy if it appears the main purpose of the policy/account is to provide benefit to a fraudster

Today: Little is done to prevent fraud from occurring

DetectDetect if a claim, payment or other transaction is likely a willful act to achieve financial gain through misrepresentation and/or falsification; and take steps to stop or send to InvestigationToday: Relies heavily on people to detect

DiscoverContinuous comparison of claim or transaction data to the data of cases known to be fraudulent in order to identify fraud that was not previously detected

Today: Not really done

InvestigateCase management, visualization and analysis tools to aid investigators in building a case against fraudsters.

Today: Special investigations unit with manual adjusters

Criminal and Fraud analysis across the fraud lifecycle

Build a case for prosecution or denial

of benefits

Stop fraud before it is reported

Detect fraud once it is reported – and react accordingly

Discover fraud after it occurs

PreventInvestigate

Discover DetectFraudster

Report/MonitorReport/Monitor ModelModel

LearnLearn

Investigative Challenges

Source SystemsSource Systems

Structured & Unstructured ContentStructured & Unstructured Content

Data QualityData Quality Data DeliveryData DeliveryETLETL Data on Data on DemandDemand

Information SharingInformation Sharing

Descriptive and Predictive Analytics

Streams Analytics

Persistent Relationship Awareness

Content & SentimentAnalytics

AnalysisRepository

Workflow & Case Management Visualization &

Link Analysis

Trusted InformationEstablish, Manage, Share & Deliver information that is accurate, complete, in context and insightful

Trusted InformationEstablish, Manage, Share & Deliver information that is accurate, complete, in context and insightful

Analytics LayerIntelligence, Descriptive & Predictive Analytics against structured, semi-structured and unstructured information

Analytics LayerIntelligence, Descriptive & Predictive Analytics against structured, semi-structured and unstructured information

Visual Analysis & CollaborationOperational dashboards, workflow, case adjudication

Visual Analysis & CollaborationOperational dashboards, workflow, case adjudication

Operational Dashboards

Required Capabilities

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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Understanding events over time

Understand Social Networks – rapid ring leader discovery

Reveal and understand complex relationships

Understand patterns of behaviour and focus

Examples

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

If you had a day...

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