copyright © 2012, sas institute inc. all rights reserved. predictive analysis for border management...

Copy r ight © 2012, SAS Ins t i tu te Inc . A l l r ights reserved.

PREDICTIVE ANALYSIS FOR BORDER MANAGEMENTRemoving the hay to find the needles

David Porter, SAS Software, 21st May 2015


BORDER MANAGEMENT

FACTS AND FIGURES FOR 2014

3.3 billion passengers

50 million metric tonnes

of cargo

50,000 routes

149 passengers per hour per lane

Just for air travel…

Source: IATA


BORDER MANAGEMENT

THREATS


SAS FOR BORDER MANAGEMENT

HOT TOPIC!!

“EU ministers discuss jihadist travel to Syria, border security”Al-Monitor

“Denmark plans to use PNR data for increased Schengen border control”Edri.org (European Digital Rights)

“Commission makes €50 million available for the development of "big brother" PNR databases - before legislation has even been agreed”Statewatch.org

“Data sharing, tighter EU outer border, urged at Paris talks”Deutsche Welle (DW)

“Spain to monitor all passenger flight data to identify jihadists”El Pais

PNRPassenger Name Record


Security Vs. Convenience Vs. Cost

Increased Volume: Travellers & Cargo

Reduced Resources

Integrated Borders (Shengenspace)

Reputation

2

1

3

4

5

BORDER MANAGEMENT

KEY CHALLENGES


WHAT IS IT?

• Dynamically identifies potentially low risk passengers or cargo based on

their pattern of activities, profile of shipment, watch lists and other data

automating the smooth movement of legitimate travellers and goods

• By identifying the low risk cases (99%) you immediately reduce the

complexity of finding the high risk (1%)

• Advanced methods such as Social Network Analysis and anomaly detection

then aid the intervention teams to prioritise the highest risk cases for

intervention.



BENEFITS

• Reduce volume of high risk

travellers and cargo entering the

country…

• Help stretched agencies process

travellers and cargo more

efficiently…




A NUMBER OF ELEMENTS

PASSENGER RISK PROFILE (SCORE)

ANALYTICS BASED

PROFILE

RULES BASED

PROFILE

WATCH LIST

MANAGEMENT

DATA MANAGEMENT


PREDICTING LOW RISK CASE STUDY 1 THE VALUE OF AUTOMATION


KEY FUNCTIONALITY OF DATA MANAGEMENTSAS FOR BORDER

MANAGEMENT

Connection to most data sources

Quickly identify and capture input streams or tables

Self-documenting and audit

Evaluation of data quality and relevance

Re-usable jobs in a collaborative environment

Batch and real-time processingIntuitive point-and-click design editor


KEY FUNCTIONALITY OF WATCH LIST MANAGEMENTSAS FOR BORDER

MANAGEMENT

Can use industry provided or home grown watch lists

Identification of data quality and format issues

Flexible scoring, achieved through sensitivity settings

Proven advanced data matching techniques

Flexible match scores = low false positives

Watch list de-confliction managementCountry specific locales


KEY FUNCTIONALITY OF RULES BASED PROFILINGSAS FOR BORDER

MANAGEMENT

Identifies the “Known Known’s”

Uses historical data to identify infringement

Deploy rules

Enables analysts to create data driven scenarios that describe travel patterns

Generate alerts

Explore and report on dataSimulate scenarios against real data


KEY FUNCTIONALITY OF ANALYTICS BASED PROFILINGSAS FOR BORDER

MANAGEMENT

Identifies the “Unknown Unknown’s”

Predictive Analytics and Data MiningIdentifies connections with other entities associated with high risk

Identifies patterns in passenger and freight data most associated with risk

Modelling

Deploys and monitors model performance

Social Network Analysis



SOLUTION FRAMEWORK

Realtime Data

API

PNR

Batch Data

Intelligence

Watch Lists

PNR

Visa

Networked Intelligence Warehouse

Real-time Model Build(Business Rules)VSD

Batch Data IngestDI / DQ

SNA

Watch list consolidation

DQ / single view Link entities

Create discrete

networks

AnalyticsEM/EG/VS/ Text Miner

Intel Management

Report & ExploreVisualAnalytics

Triage / VisualiseSNAVisualAnalytics

Case Management

Real-time Scoring

Watch list matching

Existing BG Interfaces

API

Learn and Improve

Scoring and AlertingBatchHybridAnalytics

Open Source


SIMPLE VIEW

Watch Lists & Criminal Intelligence

Passenger

Flight

Biometrics

Customs


EXPANDED VIEW

Watch Lists & Criminal IntelligenceDeparture History

Border Guards

Passenger

Flight

Biometrics

Customs

Issuing OfficerSponsor

BankAccount

BankAccount

Travel Agent


WITH BEHAVIOURStatistical Anomalies

Route

Departure History

Border Guards

Passenger

Flight

Biometrics

CustomsHistory


BankAccount

BankAccount

Travel Agent

Peers

In the Air


WITH SNA

Coincidences

Route

Departure History

Border Guards

Passenger

Flight

Biometrics

CustomsHistory


BankAccount

BankAccount

Travel Agent

Peers

In the Air


HYBRID

CoincidencesWatch Lists & Criminal Intelligence

Statistical Anomalies

Route

Departure History

Border Guards

Passenger

Flight

Biometrics

CustomsHistory


BankAccount

BankAccount

Travel Agent

Peers

In the Air


INTERDICTION

SAS for Border Management

Coincidences

Watch Lists &Criminal Intelligence

Statistical Anomalies

Border Guards

Customs

Issuing Officer

In the Air

Originating CountryLaw Enforcement

Feedback Results

Air MarshalsPolice

Intel

RulesWorkflowPrioritisationDe-confliction


“Before, our competent staff collected and analysed field

and historical information to sort out risk patterns. As

there may be, however, a blind spot where statistical

risks can escape from detection, we felt the necessity of

a mining technique to sort them out.”

KOREAN CUSTOMS SERVICE

-Implementation of the SAS solution improved detection rates for

important items by over 20%

CASE STUDY 2 – KOREAN CUSTOMS SERVICESAS FOR BORDER MANAGEMENT


CASE STUDY 3 DUAL USE BELGIAN CUSTOMS (TAX AND DUTY EVASION)

• Dual-Use commodities are Goods and technologies considered to be

dual-use when they can be used for both civil and military purposes.

• Under the EU regime, dual-use items may not leave the EU customs territory

without an export authorisation. Additional restrictions are also in place concerning

the provision of brokering services with regard to dual-use items and concerning

the transit of such items through the EU.

• Implementation of Dual-Use Fraud detection at Belgian customs• All exports from Belgium to countries at risk• Identify rules to detect export companies not declaring dual-use items

E.g. Telescope is a dual-use item, an optician might want to declare this item as a

lamp through customs to avoid paper work and fees. How to detect who to control?


DUAL USE FRAUD ANOMALY DETECTION USING CLUSTERING

PROFILE COMPANIES EXPORTING DUAL USE VS. OTHER COMPANIES

• Export in a lot of countries• Export commodities in group 85

(electrical machinery) and 84 (nuclear

reactors)• Big exporters• Mainly road transport• Also export 73 (Iron/Steel), 90

(Optical) and 39 (Plastics)LOOK AT SIMILAR COMPANIES WHICH AREN’T EXPORTING DUAL USE COMMODITIES

• 370 companies with similar profile

Dual use company

No-dual use company

Cluster 1

Cluster 2


DUAL USE FRAUD Anomaly detection Using Market Basket Analysis

• Basket analysis of all

commodities exported by dual-

use companies• Find Associations between dual-

use and other commodities -

Identify strong and interesting

associations • Extrapolate to all export

companies and look at their dual-

use exports

IF 3917 – Tubes, Pipes and Hoses 3926 – Other Plastics

85 - Electrical Machinery

AND OR ( )

THEN

4016930000 - Gaskets

Total Dual Use Export

Total Items Export

Outliers


DUAL USE FRAUD Anomaly detection using Decision Trees

Many countries and Aluminum container

Pumps for liquids

Other plastics articles

Safety Glass

Inorganic Chemicals, Organic/Inorganic Metals

Lots of exports by road


•Provide decisive analysis with high accuracy•Simulate first, limit roll out until provenFocus on results

•Establish super user community•Involve them in strategy, plans and model designInvolve users

•Don’t leave users guessing “Why?”•Where possible get the most out of transparent toolsAvoid black box

•Give users the data they need, make them efficient•Think carefully about delivery mechanismsEnable users

•Start simple, let initiatives bed in•Ramp up sophistication as a programme of workIt’s a journey

•Always gauge reaction and enhance•Structured plan for roll outs, training, etc.Pilot and iterate

•Communicate internally•External communication: preventive effectCommunicate

Border AnalyticsSuccessful Adoption Approach

Copy r ight © 2012, SAS Ins t i tu te Inc . A l l r ights reserved. www.SAS.com

THANK YOU [email protected]

http://www.sas.com/

copyright © 2012, sas institute inc. all rights reserved. predictive analysis for border management...

Documents

sas institute

border management slide

sas software

border management connection

border management threats

border management facts

border management hot

record slide