supply chain risks - docuride.cz · • defense & security • automotive industry •...
TRANSCRIPT
© 2015 Semantic Visions. All rights reserved. 1
Docuride 2015
© 2015 Semantic Visions. All rights reserved. 1
Supply Chain RisksBig Data Semantics24-Sep-2015
© 2015 Semantic Visions. All rights reserved. 2
• Most sophisticated semantic engine
• Unrivalled web mining system
• Own internet content database (60+ TB of metadata)
• Innovative solutions in risk assessment:
• GLORIA: geolocation-centric risk early warning system
• VEGA: company-centric early warning system
• Projects above and beyond traditional sentiment analysis:
• Defense & Security
• Automotive Industry
• Long-term experience in big data & semantic analysis (since 2004)
• Proven track record in defense & security
• Global award winning technology
WORLD LEADER IN COLLECTION AND ANALYSIS
OF BIG DATA FROM THE INTERNET
© 2015 Semantic Visions. All rights reserved. 3
Combination of three basic elements resulting in unmatched scope, speed & precision
KEY DIFFERENTIATOR
© 2015 Semantic Visions. All rights reserved. 4
Change of mind set in utilizing publicly available data
TWO MODELS OF INFORMATION EXPLOITATION
© 2015 Semantic Visions. All rights reserved. 5
Strategy in collecting valuable pieces of information
THE LONG TAIL
© 2015 Semantic Visions. All rights reserved. 6
Only a fraction of available data is in English
Content
English
GDP
English
Actionable Intelligence
English
More Big Data = More Knowledge
Across Languages Across Geographies Truly Global
World
WHY CROSS-LANGUAGE IS IMPORTANT
© 2015 Semantic Visions. All rights reserved. 7
VEGA allows risk managers to track their suppliers network around the globe and detect supply chain
threats – in real time –before they disrupt production lines and impact costs. VEGA analyzes 90% of the
world’s news content, millions of signals in the world’s top 10 languages. VEGA distinguishes critical
signals from irrelevant noise and gives our customers the situational intelligence they need in order to
respond appropriately.
• Real-time prediction analysis of supply chain disruptions.
• Unparalleled in its collection, processing and analytic capabilities
• Designed for large companies with 1,000 – 1,000,000 suppliers worldwide.
• Customized and secured solution under customer’s control.
• On-premise and cloud deployment.
VEGA – SUPPLY CHAIN EARLY WARNING SYSTEM
© 2015 Semantic Visions. All rights reserved. 8
• REAL-TIME RISK
ASSESSMENT OF UP TO 1
MILLION+ COMPANIES
• KEEPING AN EYE ON:
• SUPPLIERS
• CUSTOMERS
• COMPETITORS
• TARGET INDUSTRIES:
• AEROSPACE & DEFENSE
• AUTOMOTIVE
• HIGH-TECH
• OIL & GAS
• MINING
• BANKING
• INSURANCE
• CAPITAL MARKETS
• GOVERNMENT
• DELIVERY MODEL
• SaaS - UI or API
• On premise
COMPANY-CENTRIC EARLY WARNING SYSTEM
© 2015 Semantic Visions. All rights reserved. 9
• TARGET INDUSTRIES:
• INSURANCE
• BANKING
• CAPITAL MARKETS
• OIL & GAS
• MINING
• LOGISTICS
• GOVERNMENT
• DELIVERY MODEL
• SaaS - UI or API
• On premise
• BENEFITS
• GREATLY ENHANCES
EXISTING 3RD PARTY
RISK MANAGEMENT
APPLICATIONS
REAL-TIME DETECTION AND RISK ASSESSMENT
BASED ON BIG DATA FROM THE INTERNET
© 2015 Semantic Visions. All rights reserved. 10
EASY SIGNAL VERIFICATION
© 2015 Semantic Visions. All rights reserved. 11
KEY ROLE OF SAP HANA
Distinguishing the critical signals from irrelevant noise
© 2015 Semantic Visions. All rights reserved. 12
Semantic Visions detects over 200 threats
NATURALNatural Disasters | Earthquake | Volcanic Eruptions |
Tsunami | Flood | Landslide | Avalanche | Forest Fire |
Drought & Heat Wave | Snowstorm | Tornado | Hurricane |
Sandstorm | Thunderstorms | Geomagnetic Storm
CORPORATERegulatory Compliance | Corporate Crime | Fraud & Forgery
| Corruption | Insider Trading | Money Laundering | Financial
Reporting Fraud | Conflict of Interest | Unethical Practice |
Waste Management Issues | Workplace Discrimination |
Neglect of Workplace Safety | Child Labor | Illegal Trade |
Sanctions Violations | IP Infringement | Patent & Trademark
Infringement | Copyright Infringement | Anticompetitive
Behavior | Corporate Lawsuits | Bankruptcy | Insolvency |
Plants Shutdown & Relocation | Plant Disruption | Senior
Management Changes | Ownership Changes | Quality
Issues | Divestment | Product Recall | Project Failure
HEALTHPandemic | Ebola | Bird Flu | SARS | Swine Flu | Cholera |
Plague | Smallpox | Polio | Dengue Fever | Malaria Outbreak
| Deadly Epidemic | Infections | Food Safety | Food
Poisoning | Dangerous Gene Mutations
GEOPOLITICALInter-state Conflicts | Intra-state Conflicts | Guerrilla Warfare
| Civil War | Ethnic War | Military Invasion & Occupation |
Border Issues | Militant Incident | Immigration Flows |
International Sanctions | General Strike | Political Crisis |
Economy Crisis | Credit Rating Downgrade | Country DefaultSECURITYTerrorist Incident | Air Traffic Security | Maritime Security |
Civil Disobedience | Rioting & Looting | Kidnapping |
Ransom | Extortion
CYBER SECURITYCyberterrorism | Computer Crime | Spyware | Malware |
Buffer Overflow Attack | DDOS Attack | DNS Hijack | DNS
Spoof | SQL Injection | TCP Flood Attack | UDP Flood
Attack | VOIP Hole | VOIP Vulnerability | Identity Theft |
Social Engineering Attack | Cyber Squatting | Phishing |
Web Server Compromise | Backdoor Vulnerability
INDUSTRIALEnvironmental Disasters | Chemical & Oil Spill | Industrial
Accidents | Explosion Accidents | Fire Accidents | Mining
Accidents | Maritime Accidents | Railway Accidents |
Aviation Accidents | Transportation Delays | Radioactive
Contamination | Critical Infrastructure Failure
SELECTED THREATS
© 2015 Semantic Visions. All rights reserved. 13
kB
MB
GB
TB
10 x TB
Existing SV’s use of
SAP HANA for:
- Faster iterations
- Deep data mining
ROADMAP:
Integration of SV
Semantic Engine
to SAP HANA
Visualization
Final Data Model
Aggregation
Predictive Analysis
Big Data Semantics
Sentiment Analysis
Text Semantics
Text Cleaning
Data Collection
Data sets ready
for making charts
Final Quantitative
Data
Quantitative Data
w/ Semantic
Dimensions
Text Data Ready
for Processing
Level of Detail
Time Frame
Data Volume
Decrease
Increase
What takes traditional methods weeks, takes SAP HANA supported Semantic Visions minutes to hours
BIG DATA COMPLEXITY
© 2015 Semantic Visions. All rights reserved. 14
EXAMPLE 1: ABOVE AND BEYOND TRADITIONAL OSINT
"Semantic Visions Found That Consensus-model Terms Outnumbered Conflict-
model Terms Both Before And After The Paris Attacks, Across All The Media
Languages Studied."
MIT TECHNOLOGY REVIEW, 3/17/2015
- 50 million articles analyzed
© 2015 Semantic Visions. All rights reserved. 15
EXAMPLE 2: CZECH BANKS COMPARISON
ČSOBAir Bank
ČS Equa Bank
FIO banka
GE Money
KB
mBank
Raiffeisenbank
Sberbank
Unicredit Bank
ZUNO Bank
© 2015 Semantic Visions. All rights reserved. 16
THANK YOU !
Julius Rusnák
CTO
Semantic Visions, s.r.o.
Mezibranská 1579/4110 00 Praha 1
M +420 731 576 623