SlideShare une entreprise Scribd logo
1  sur  7
State Street FIBO Proof-of-Concept
Marty Loughlin, Vice President, Financial Services Sales
©2018 Cambridge Semantics Inc. All rights reserved.
• Purpose: Demonstrate
- The practicality of using FIBO to harmonize diverse derivative and entity data
- The usefulness of FIBO for comprehensive reporting and analytics, both traditional and innovative
• PoC approach:
- Apply FIBO to operational, “in the wild” data
- Implement using a state-of-the-art semantics platform
• Rapid implementation, no coding required
• Project Participants:
1
State Street Business requirements and operational data
EDM Council FIBO mode and recommended reports/analytics
Cambridge Semantics Operational platform and implementation services
dun & bradstreet Business Entity and Corporate Hierarchy data
Wells Fargo FIBO consultation
State Street FIBO Proof-of-Concept
©2018 Cambridge Semantics Inc. All rights reserved.
FIBO PoC Solution Architecture
Front
Arena
Data
Dun &
Bradstreet
Data
Internal Data Sources
Map & Load (QA) Link & Query (Classification, inference, analytics)
External Data Sources
Derivatives Data
Entity &
Corp. Hierarchy
Data
Reports & Analytics
Pilot Solution Architecture
©2018 Cambridge Semantics Inc. All rights reserved.
Project Approach
Load & operationalize FIBO in Anzo
Map data sources onto FIBO
Load, harmonize, QA and classify data
Configure analytic dashboards
1
2
3
4
Project Approach
©2018 Cambridge Semantics Inc. All rights reserved.
Risk Analytics
©2018 Cambridge Semantics Inc. All rights reserved.
PoC Findings: Business Value
• Rapid data harmonization across disparate sources
• Open standards approach means model (FIBO) and tools (Anzo) work together
seamlessly
• Data mapping, loading, harmonizing and analytics required no coding
• Business friendly
• Models and tools are designed for business users – dashboards
• Provide common view of data in business terms
• Sophisticated reporting and analytics
• Easily ask questions of the data not anticipated in advance
• Visualize and calculate transitive exposures which would require custom coding
with traditional approaches
• Business agility
• Rapidly add new sources (internal or external) and analytics
PoC Findings: Business Value
©2018 Cambridge Semantics Inc. All rights reserved.
PoC Findings: Lessons Learned
• The FIBO model works and delivers unique data insight capabilities
• The Anzo tools work well and deliver value
• Traditional problems: availability of people, access to data and good IT
resources drive the adoption timeline.
• FIBO model is comprehensive, but comes with some complexity
• Not intuitive; Use requires learning
• FIBO facilitates construction of simplified operational ontologies
• Models and tools are standards based, but implementation required some
adaptations and workarounds
PoC Findings: Lessons Learned

Contenu connexe

Tendances

Random Forest Algorithm - Random Forest Explained | Random Forest In Machine ...
Random Forest Algorithm - Random Forest Explained | Random Forest In Machine ...Random Forest Algorithm - Random Forest Explained | Random Forest In Machine ...
Random Forest Algorithm - Random Forest Explained | Random Forest In Machine ...Simplilearn
 
Explainable AI in Industry (WWW 2020 Tutorial)
Explainable AI in Industry (WWW 2020 Tutorial)Explainable AI in Industry (WWW 2020 Tutorial)
Explainable AI in Industry (WWW 2020 Tutorial)Krishnaram Kenthapadi
 
Stream and Batch Processing in the Cloud with Data Microservices
Stream and Batch Processing in the Cloud with Data MicroservicesStream and Batch Processing in the Cloud with Data Microservices
Stream and Batch Processing in the Cloud with Data Microservicesmarius_bogoevici
 
Introduction of Knowledge Graphs
Introduction of Knowledge GraphsIntroduction of Knowledge Graphs
Introduction of Knowledge GraphsJeff Z. Pan
 
007 20151214 Deep Unsupervised Learning using Nonequlibrium Thermodynamics
007 20151214 Deep Unsupervised Learning using Nonequlibrium Thermodynamics007 20151214 Deep Unsupervised Learning using Nonequlibrium Thermodynamics
007 20151214 Deep Unsupervised Learning using Nonequlibrium ThermodynamicsHa Phuong
 
SVD and the Netflix Dataset
SVD and the Netflix DatasetSVD and the Netflix Dataset
SVD and the Netflix DatasetBen Mabey
 
MapReduce Paradigm
MapReduce ParadigmMapReduce Paradigm
MapReduce ParadigmDilip Reddy
 
Learning to Rank for Recommender Systems - ACM RecSys 2013 tutorial
Learning to Rank for Recommender Systems -  ACM RecSys 2013 tutorialLearning to Rank for Recommender Systems -  ACM RecSys 2013 tutorial
Learning to Rank for Recommender Systems - ACM RecSys 2013 tutorialAlexandros Karatzoglou
 
구글의 새로운 타겟팅 솔루션, FLoC란?
구글의 새로운 타겟팅 솔루션, FLoC란?구글의 새로운 타겟팅 솔루션, FLoC란?
구글의 새로운 타겟팅 솔루션, FLoC란?JunsooJang
 
Recommender system introduction
Recommender system   introductionRecommender system   introduction
Recommender system introductionLiang Xiang
 
Service innovation and performance-based evaluation of university libraries i...
Service innovation and performance-based evaluation of university libraries i...Service innovation and performance-based evaluation of university libraries i...
Service innovation and performance-based evaluation of university libraries i...Muhammad Yousuf Ali
 
내가 이해하는 SVM(왜, 어떻게를 중심으로)
내가 이해하는 SVM(왜, 어떻게를 중심으로)내가 이해하는 SVM(왜, 어떻게를 중심으로)
내가 이해하는 SVM(왜, 어떻게를 중심으로)SANG WON PARK
 
Review: Incremental Few-shot Instance Segmentation [CDM]
Review: Incremental Few-shot Instance Segmentation [CDM]Review: Incremental Few-shot Instance Segmentation [CDM]
Review: Incremental Few-shot Instance Segmentation [CDM]Dongmin Choi
 
Unsupervised learning (clustering)
Unsupervised learning (clustering)Unsupervised learning (clustering)
Unsupervised learning (clustering)Pravinkumar Landge
 
Introduction to Big Data and Data Science
Introduction to Big Data and Data ScienceIntroduction to Big Data and Data Science
Introduction to Big Data and Data ScienceFeyzi R. Bagirov
 
Lecture 3 - DS-based Impedance/Force Control
Lecture 3 - DS-based Impedance/Force ControlLecture 3 - DS-based Impedance/Force Control
Lecture 3 - DS-based Impedance/Force ControlNadia Barbara
 

Tendances (20)

Cmmi high maturity handbook
Cmmi high maturity handbookCmmi high maturity handbook
Cmmi high maturity handbook
 
Random Forest Algorithm - Random Forest Explained | Random Forest In Machine ...
Random Forest Algorithm - Random Forest Explained | Random Forest In Machine ...Random Forest Algorithm - Random Forest Explained | Random Forest In Machine ...
Random Forest Algorithm - Random Forest Explained | Random Forest In Machine ...
 
Explainable AI in Industry (WWW 2020 Tutorial)
Explainable AI in Industry (WWW 2020 Tutorial)Explainable AI in Industry (WWW 2020 Tutorial)
Explainable AI in Industry (WWW 2020 Tutorial)
 
Stream and Batch Processing in the Cloud with Data Microservices
Stream and Batch Processing in the Cloud with Data MicroservicesStream and Batch Processing in the Cloud with Data Microservices
Stream and Batch Processing in the Cloud with Data Microservices
 
Introduction of Knowledge Graphs
Introduction of Knowledge GraphsIntroduction of Knowledge Graphs
Introduction of Knowledge Graphs
 
Python for Data Science
Python for Data SciencePython for Data Science
Python for Data Science
 
Regularization
RegularizationRegularization
Regularization
 
007 20151214 Deep Unsupervised Learning using Nonequlibrium Thermodynamics
007 20151214 Deep Unsupervised Learning using Nonequlibrium Thermodynamics007 20151214 Deep Unsupervised Learning using Nonequlibrium Thermodynamics
007 20151214 Deep Unsupervised Learning using Nonequlibrium Thermodynamics
 
SVD and the Netflix Dataset
SVD and the Netflix DatasetSVD and the Netflix Dataset
SVD and the Netflix Dataset
 
MapReduce Paradigm
MapReduce ParadigmMapReduce Paradigm
MapReduce Paradigm
 
Learning to Rank for Recommender Systems - ACM RecSys 2013 tutorial
Learning to Rank for Recommender Systems -  ACM RecSys 2013 tutorialLearning to Rank for Recommender Systems -  ACM RecSys 2013 tutorial
Learning to Rank for Recommender Systems - ACM RecSys 2013 tutorial
 
Recent Trends in Personalization at Netflix
Recent Trends in Personalization at NetflixRecent Trends in Personalization at Netflix
Recent Trends in Personalization at Netflix
 
구글의 새로운 타겟팅 솔루션, FLoC란?
구글의 새로운 타겟팅 솔루션, FLoC란?구글의 새로운 타겟팅 솔루션, FLoC란?
구글의 새로운 타겟팅 솔루션, FLoC란?
 
Recommender system introduction
Recommender system   introductionRecommender system   introduction
Recommender system introduction
 
Service innovation and performance-based evaluation of university libraries i...
Service innovation and performance-based evaluation of university libraries i...Service innovation and performance-based evaluation of university libraries i...
Service innovation and performance-based evaluation of university libraries i...
 
내가 이해하는 SVM(왜, 어떻게를 중심으로)
내가 이해하는 SVM(왜, 어떻게를 중심으로)내가 이해하는 SVM(왜, 어떻게를 중심으로)
내가 이해하는 SVM(왜, 어떻게를 중심으로)
 
Review: Incremental Few-shot Instance Segmentation [CDM]
Review: Incremental Few-shot Instance Segmentation [CDM]Review: Incremental Few-shot Instance Segmentation [CDM]
Review: Incremental Few-shot Instance Segmentation [CDM]
 
Unsupervised learning (clustering)
Unsupervised learning (clustering)Unsupervised learning (clustering)
Unsupervised learning (clustering)
 
Introduction to Big Data and Data Science
Introduction to Big Data and Data ScienceIntroduction to Big Data and Data Science
Introduction to Big Data and Data Science
 
Lecture 3 - DS-based Impedance/Force Control
Lecture 3 - DS-based Impedance/Force ControlLecture 3 - DS-based Impedance/Force Control
Lecture 3 - DS-based Impedance/Force Control
 

Similaire à State street edmc swaps pilot

Smart Data Webinar: A semantic solution for financial regulatory compliance
Smart Data Webinar: A semantic solution for financial regulatory complianceSmart Data Webinar: A semantic solution for financial regulatory compliance
Smart Data Webinar: A semantic solution for financial regulatory complianceDATAVERSITY
 
Agile Data Warehouse Design for Big Data Presentation
Agile Data Warehouse Design for Big Data PresentationAgile Data Warehouse Design for Big Data Presentation
Agile Data Warehouse Design for Big Data PresentationVishal Kumar
 
What Does Artificial Intelligence Have to Do with IT Operations?
What Does Artificial Intelligence Have to Do with IT Operations?What Does Artificial Intelligence Have to Do with IT Operations?
What Does Artificial Intelligence Have to Do with IT Operations?Precisely
 
BizTrans SysTech_Analytics_Serv_SAP_v1.0
BizTrans SysTech_Analytics_Serv_SAP_v1.0BizTrans SysTech_Analytics_Serv_SAP_v1.0
BizTrans SysTech_Analytics_Serv_SAP_v1.0BizTrans SysTech
 
Product Management 101 for Data and Analytics
Product Management 101 for Data and Analytics Product Management 101 for Data and Analytics
Product Management 101 for Data and Analytics Ravi Padaki
 
Moving Up the PVC Maturity Curve in Industrial Manufacturing
Moving Up the PVC Maturity Curve in Industrial ManufacturingMoving Up the PVC Maturity Curve in Industrial Manufacturing
Moving Up the PVC Maturity Curve in Industrial ManufacturingZero Wait-State
 
SharePoint as a Business Platform Why, What and How? – No Code
SharePoint as a Business Platform Why, What and How? – No CodeSharePoint as a Business Platform Why, What and How? – No Code
SharePoint as a Business Platform Why, What and How? – No Codedox42
 
What You Need to Know Before Upgrading to SharePoint 2013
What You Need to Know Before Upgrading to SharePoint 2013What You Need to Know Before Upgrading to SharePoint 2013
What You Need to Know Before Upgrading to SharePoint 2013Perficient, Inc.
 
Building a 360 Degree View of Your Customers on BICS
Building a 360 Degree View of Your Customers on BICSBuilding a 360 Degree View of Your Customers on BICS
Building a 360 Degree View of Your Customers on BICSPerficient, Inc.
 
Big Data LDN 2017: How Big Data Insights Become Easily Accessible With Workfl...
Big Data LDN 2017: How Big Data Insights Become Easily Accessible With Workfl...Big Data LDN 2017: How Big Data Insights Become Easily Accessible With Workfl...
Big Data LDN 2017: How Big Data Insights Become Easily Accessible With Workfl...Matt Stubbs
 
Self-Service Analytics with Guard Rails
Self-Service Analytics with Guard RailsSelf-Service Analytics with Guard Rails
Self-Service Analytics with Guard RailsDenodo
 
Applying the R Language to BI and Real Time Applications
Applying the R Language to BI and Real Time ApplicationsApplying the R Language to BI and Real Time Applications
Applying the R Language to BI and Real Time ApplicationsLou Bajuk
 
EMA Presentation: Driving Business Value with Continuous Operational Intellig...
EMA Presentation: Driving Business Value with Continuous Operational Intellig...EMA Presentation: Driving Business Value with Continuous Operational Intellig...
EMA Presentation: Driving Business Value with Continuous Operational Intellig...ExtraHop Networks
 
AU 2015: Enterprise, Beam Me Up: Inphi's Enterprise PLM Solution (PPT)
AU 2015: Enterprise, Beam Me Up: Inphi's Enterprise PLM Solution (PPT)AU 2015: Enterprise, Beam Me Up: Inphi's Enterprise PLM Solution (PPT)
AU 2015: Enterprise, Beam Me Up: Inphi's Enterprise PLM Solution (PPT)Razorleaf Corporation
 
otbioverviewow13-141008094532-conversion-gate01-converted.pptx
otbioverviewow13-141008094532-conversion-gate01-converted.pptxotbioverviewow13-141008094532-conversion-gate01-converted.pptx
otbioverviewow13-141008094532-conversion-gate01-converted.pptxSreekumarSasikumar
 
Best Practices for BI Implementations
Best Practices for BI ImplementationsBest Practices for BI Implementations
Best Practices for BI Implementationsalero546
 

Similaire à State street edmc swaps pilot (20)

Smart Data Webinar: A semantic solution for financial regulatory compliance
Smart Data Webinar: A semantic solution for financial regulatory complianceSmart Data Webinar: A semantic solution for financial regulatory compliance
Smart Data Webinar: A semantic solution for financial regulatory compliance
 
Agile Data Warehouse Design for Big Data Presentation
Agile Data Warehouse Design for Big Data PresentationAgile Data Warehouse Design for Big Data Presentation
Agile Data Warehouse Design for Big Data Presentation
 
What Does Artificial Intelligence Have to Do with IT Operations?
What Does Artificial Intelligence Have to Do with IT Operations?What Does Artificial Intelligence Have to Do with IT Operations?
What Does Artificial Intelligence Have to Do with IT Operations?
 
BizTrans SysTech_Analytics_Serv_SAP_v1.0
BizTrans SysTech_Analytics_Serv_SAP_v1.0BizTrans SysTech_Analytics_Serv_SAP_v1.0
BizTrans SysTech_Analytics_Serv_SAP_v1.0
 
Product Management 101 for Data and Analytics
Product Management 101 for Data and Analytics Product Management 101 for Data and Analytics
Product Management 101 for Data and Analytics
 
Moving Up the PVC Maturity Curve in Industrial Manufacturing
Moving Up the PVC Maturity Curve in Industrial ManufacturingMoving Up the PVC Maturity Curve in Industrial Manufacturing
Moving Up the PVC Maturity Curve in Industrial Manufacturing
 
SharePoint as a Business Platform Why, What and How? – No Code
SharePoint as a Business Platform Why, What and How? – No CodeSharePoint as a Business Platform Why, What and How? – No Code
SharePoint as a Business Platform Why, What and How? – No Code
 
What You Need to Know Before Upgrading to SharePoint 2013
What You Need to Know Before Upgrading to SharePoint 2013What You Need to Know Before Upgrading to SharePoint 2013
What You Need to Know Before Upgrading to SharePoint 2013
 
Building a 360 Degree View of Your Customers on BICS
Building a 360 Degree View of Your Customers on BICSBuilding a 360 Degree View of Your Customers on BICS
Building a 360 Degree View of Your Customers on BICS
 
Chapter01
Chapter01Chapter01
Chapter01
 
Big Data LDN 2017: How Big Data Insights Become Easily Accessible With Workfl...
Big Data LDN 2017: How Big Data Insights Become Easily Accessible With Workfl...Big Data LDN 2017: How Big Data Insights Become Easily Accessible With Workfl...
Big Data LDN 2017: How Big Data Insights Become Easily Accessible With Workfl...
 
Self-Service Analytics with Guard Rails
Self-Service Analytics with Guard RailsSelf-Service Analytics with Guard Rails
Self-Service Analytics with Guard Rails
 
Chapter01
Chapter01Chapter01
Chapter01
 
Applying the R Language to BI and Real Time Applications
Applying the R Language to BI and Real Time ApplicationsApplying the R Language to BI and Real Time Applications
Applying the R Language to BI and Real Time Applications
 
EMA Presentation: Driving Business Value with Continuous Operational Intellig...
EMA Presentation: Driving Business Value with Continuous Operational Intellig...EMA Presentation: Driving Business Value with Continuous Operational Intellig...
EMA Presentation: Driving Business Value with Continuous Operational Intellig...
 
AU 2015: Enterprise, Beam Me Up: Inphi's Enterprise PLM Solution (PPT)
AU 2015: Enterprise, Beam Me Up: Inphi's Enterprise PLM Solution (PPT)AU 2015: Enterprise, Beam Me Up: Inphi's Enterprise PLM Solution (PPT)
AU 2015: Enterprise, Beam Me Up: Inphi's Enterprise PLM Solution (PPT)
 
otbioverviewow13-141008094532-conversion-gate01-converted.pptx
otbioverviewow13-141008094532-conversion-gate01-converted.pptxotbioverviewow13-141008094532-conversion-gate01-converted.pptx
otbioverviewow13-141008094532-conversion-gate01-converted.pptx
 
Webinar: The Slippery Slope of Migrating to SharePoint Online or On-Premise
Webinar: The Slippery Slope of Migrating to SharePoint Online or On-PremiseWebinar: The Slippery Slope of Migrating to SharePoint Online or On-Premise
Webinar: The Slippery Slope of Migrating to SharePoint Online or On-Premise
 
Chapter01.ppt
Chapter01.pptChapter01.ppt
Chapter01.ppt
 
Best Practices for BI Implementations
Best Practices for BI ImplementationsBest Practices for BI Implementations
Best Practices for BI Implementations
 

Dernier

Pigging Solutions in Pet Food Manufacturing
Pigging Solutions in Pet Food ManufacturingPigging Solutions in Pet Food Manufacturing
Pigging Solutions in Pet Food ManufacturingPigging Solutions
 
FULL ENJOY 🔝 8264348440 🔝 Call Girls in Diplomatic Enclave | Delhi
FULL ENJOY 🔝 8264348440 🔝 Call Girls in Diplomatic Enclave | DelhiFULL ENJOY 🔝 8264348440 🔝 Call Girls in Diplomatic Enclave | Delhi
FULL ENJOY 🔝 8264348440 🔝 Call Girls in Diplomatic Enclave | Delhisoniya singh
 
Handwritten Text Recognition for manuscripts and early printed texts
Handwritten Text Recognition for manuscripts and early printed textsHandwritten Text Recognition for manuscripts and early printed texts
Handwritten Text Recognition for manuscripts and early printed textsMaria Levchenko
 
How to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected WorkerHow to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected WorkerThousandEyes
 
Enhancing Worker Digital Experience: A Hands-on Workshop for Partners
Enhancing Worker Digital Experience: A Hands-on Workshop for PartnersEnhancing Worker Digital Experience: A Hands-on Workshop for Partners
Enhancing Worker Digital Experience: A Hands-on Workshop for PartnersThousandEyes
 
Install Stable Diffusion in windows machine
Install Stable Diffusion in windows machineInstall Stable Diffusion in windows machine
Install Stable Diffusion in windows machinePadma Pradeep
 
Transcript: #StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024
Transcript: #StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024Transcript: #StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024
Transcript: #StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024BookNet Canada
 
Benefits Of Flutter Compared To Other Frameworks
Benefits Of Flutter Compared To Other FrameworksBenefits Of Flutter Compared To Other Frameworks
Benefits Of Flutter Compared To Other FrameworksSoftradix Technologies
 
Presentation on how to chat with PDF using ChatGPT code interpreter
Presentation on how to chat with PDF using ChatGPT code interpreterPresentation on how to chat with PDF using ChatGPT code interpreter
Presentation on how to chat with PDF using ChatGPT code interpreternaman860154
 
WhatsApp 9892124323 ✓Call Girls In Kalyan ( Mumbai ) secure service
WhatsApp 9892124323 ✓Call Girls In Kalyan ( Mumbai ) secure serviceWhatsApp 9892124323 ✓Call Girls In Kalyan ( Mumbai ) secure service
WhatsApp 9892124323 ✓Call Girls In Kalyan ( Mumbai ) secure servicePooja Nehwal
 
Salesforce Community Group Quito, Salesforce 101
Salesforce Community Group Quito, Salesforce 101Salesforce Community Group Quito, Salesforce 101
Salesforce Community Group Quito, Salesforce 101Paola De la Torre
 
From Event to Action: Accelerate Your Decision Making with Real-Time Automation
From Event to Action: Accelerate Your Decision Making with Real-Time AutomationFrom Event to Action: Accelerate Your Decision Making with Real-Time Automation
From Event to Action: Accelerate Your Decision Making with Real-Time AutomationSafe Software
 
AI as an Interface for Commercial Buildings
AI as an Interface for Commercial BuildingsAI as an Interface for Commercial Buildings
AI as an Interface for Commercial BuildingsMemoori
 
08448380779 Call Girls In Diplomatic Enclave Women Seeking Men
08448380779 Call Girls In Diplomatic Enclave Women Seeking Men08448380779 Call Girls In Diplomatic Enclave Women Seeking Men
08448380779 Call Girls In Diplomatic Enclave Women Seeking MenDelhi Call girls
 
04-2024-HHUG-Sales-and-Marketing-Alignment.pptx
04-2024-HHUG-Sales-and-Marketing-Alignment.pptx04-2024-HHUG-Sales-and-Marketing-Alignment.pptx
04-2024-HHUG-Sales-and-Marketing-Alignment.pptxHampshireHUG
 
Azure Monitor & Application Insight to monitor Infrastructure & Application
Azure Monitor & Application Insight to monitor Infrastructure & ApplicationAzure Monitor & Application Insight to monitor Infrastructure & Application
Azure Monitor & Application Insight to monitor Infrastructure & ApplicationAndikSusilo4
 
Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...
Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...
Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...Neo4j
 
Automating Business Process via MuleSoft Composer | Bangalore MuleSoft Meetup...
Automating Business Process via MuleSoft Composer | Bangalore MuleSoft Meetup...Automating Business Process via MuleSoft Composer | Bangalore MuleSoft Meetup...
Automating Business Process via MuleSoft Composer | Bangalore MuleSoft Meetup...shyamraj55
 
How to Remove Document Management Hurdles with X-Docs?
How to Remove Document Management Hurdles with X-Docs?How to Remove Document Management Hurdles with X-Docs?
How to Remove Document Management Hurdles with X-Docs?XfilesPro
 
IAC 2024 - IA Fast Track to Search Focused AI Solutions
IAC 2024 - IA Fast Track to Search Focused AI SolutionsIAC 2024 - IA Fast Track to Search Focused AI Solutions
IAC 2024 - IA Fast Track to Search Focused AI SolutionsEnterprise Knowledge
 

Dernier (20)

Pigging Solutions in Pet Food Manufacturing
Pigging Solutions in Pet Food ManufacturingPigging Solutions in Pet Food Manufacturing
Pigging Solutions in Pet Food Manufacturing
 
FULL ENJOY 🔝 8264348440 🔝 Call Girls in Diplomatic Enclave | Delhi
FULL ENJOY 🔝 8264348440 🔝 Call Girls in Diplomatic Enclave | DelhiFULL ENJOY 🔝 8264348440 🔝 Call Girls in Diplomatic Enclave | Delhi
FULL ENJOY 🔝 8264348440 🔝 Call Girls in Diplomatic Enclave | Delhi
 
Handwritten Text Recognition for manuscripts and early printed texts
Handwritten Text Recognition for manuscripts and early printed textsHandwritten Text Recognition for manuscripts and early printed texts
Handwritten Text Recognition for manuscripts and early printed texts
 
How to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected WorkerHow to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected Worker
 
Enhancing Worker Digital Experience: A Hands-on Workshop for Partners
Enhancing Worker Digital Experience: A Hands-on Workshop for PartnersEnhancing Worker Digital Experience: A Hands-on Workshop for Partners
Enhancing Worker Digital Experience: A Hands-on Workshop for Partners
 
Install Stable Diffusion in windows machine
Install Stable Diffusion in windows machineInstall Stable Diffusion in windows machine
Install Stable Diffusion in windows machine
 
Transcript: #StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024
Transcript: #StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024Transcript: #StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024
Transcript: #StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024
 
Benefits Of Flutter Compared To Other Frameworks
Benefits Of Flutter Compared To Other FrameworksBenefits Of Flutter Compared To Other Frameworks
Benefits Of Flutter Compared To Other Frameworks
 
Presentation on how to chat with PDF using ChatGPT code interpreter
Presentation on how to chat with PDF using ChatGPT code interpreterPresentation on how to chat with PDF using ChatGPT code interpreter
Presentation on how to chat with PDF using ChatGPT code interpreter
 
WhatsApp 9892124323 ✓Call Girls In Kalyan ( Mumbai ) secure service
WhatsApp 9892124323 ✓Call Girls In Kalyan ( Mumbai ) secure serviceWhatsApp 9892124323 ✓Call Girls In Kalyan ( Mumbai ) secure service
WhatsApp 9892124323 ✓Call Girls In Kalyan ( Mumbai ) secure service
 
Salesforce Community Group Quito, Salesforce 101
Salesforce Community Group Quito, Salesforce 101Salesforce Community Group Quito, Salesforce 101
Salesforce Community Group Quito, Salesforce 101
 
From Event to Action: Accelerate Your Decision Making with Real-Time Automation
From Event to Action: Accelerate Your Decision Making with Real-Time AutomationFrom Event to Action: Accelerate Your Decision Making with Real-Time Automation
From Event to Action: Accelerate Your Decision Making with Real-Time Automation
 
AI as an Interface for Commercial Buildings
AI as an Interface for Commercial BuildingsAI as an Interface for Commercial Buildings
AI as an Interface for Commercial Buildings
 
08448380779 Call Girls In Diplomatic Enclave Women Seeking Men
08448380779 Call Girls In Diplomatic Enclave Women Seeking Men08448380779 Call Girls In Diplomatic Enclave Women Seeking Men
08448380779 Call Girls In Diplomatic Enclave Women Seeking Men
 
04-2024-HHUG-Sales-and-Marketing-Alignment.pptx
04-2024-HHUG-Sales-and-Marketing-Alignment.pptx04-2024-HHUG-Sales-and-Marketing-Alignment.pptx
04-2024-HHUG-Sales-and-Marketing-Alignment.pptx
 
Azure Monitor & Application Insight to monitor Infrastructure & Application
Azure Monitor & Application Insight to monitor Infrastructure & ApplicationAzure Monitor & Application Insight to monitor Infrastructure & Application
Azure Monitor & Application Insight to monitor Infrastructure & Application
 
Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...
Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...
Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...
 
Automating Business Process via MuleSoft Composer | Bangalore MuleSoft Meetup...
Automating Business Process via MuleSoft Composer | Bangalore MuleSoft Meetup...Automating Business Process via MuleSoft Composer | Bangalore MuleSoft Meetup...
Automating Business Process via MuleSoft Composer | Bangalore MuleSoft Meetup...
 
How to Remove Document Management Hurdles with X-Docs?
How to Remove Document Management Hurdles with X-Docs?How to Remove Document Management Hurdles with X-Docs?
How to Remove Document Management Hurdles with X-Docs?
 
IAC 2024 - IA Fast Track to Search Focused AI Solutions
IAC 2024 - IA Fast Track to Search Focused AI SolutionsIAC 2024 - IA Fast Track to Search Focused AI Solutions
IAC 2024 - IA Fast Track to Search Focused AI Solutions
 

State street edmc swaps pilot

  • 1. State Street FIBO Proof-of-Concept Marty Loughlin, Vice President, Financial Services Sales
  • 2. ©2018 Cambridge Semantics Inc. All rights reserved. • Purpose: Demonstrate - The practicality of using FIBO to harmonize diverse derivative and entity data - The usefulness of FIBO for comprehensive reporting and analytics, both traditional and innovative • PoC approach: - Apply FIBO to operational, “in the wild” data - Implement using a state-of-the-art semantics platform • Rapid implementation, no coding required • Project Participants: 1 State Street Business requirements and operational data EDM Council FIBO mode and recommended reports/analytics Cambridge Semantics Operational platform and implementation services dun & bradstreet Business Entity and Corporate Hierarchy data Wells Fargo FIBO consultation State Street FIBO Proof-of-Concept
  • 3. ©2018 Cambridge Semantics Inc. All rights reserved. FIBO PoC Solution Architecture Front Arena Data Dun & Bradstreet Data Internal Data Sources Map & Load (QA) Link & Query (Classification, inference, analytics) External Data Sources Derivatives Data Entity & Corp. Hierarchy Data Reports & Analytics Pilot Solution Architecture
  • 4. ©2018 Cambridge Semantics Inc. All rights reserved. Project Approach Load & operationalize FIBO in Anzo Map data sources onto FIBO Load, harmonize, QA and classify data Configure analytic dashboards 1 2 3 4 Project Approach
  • 5. ©2018 Cambridge Semantics Inc. All rights reserved. Risk Analytics
  • 6. ©2018 Cambridge Semantics Inc. All rights reserved. PoC Findings: Business Value • Rapid data harmonization across disparate sources • Open standards approach means model (FIBO) and tools (Anzo) work together seamlessly • Data mapping, loading, harmonizing and analytics required no coding • Business friendly • Models and tools are designed for business users – dashboards • Provide common view of data in business terms • Sophisticated reporting and analytics • Easily ask questions of the data not anticipated in advance • Visualize and calculate transitive exposures which would require custom coding with traditional approaches • Business agility • Rapidly add new sources (internal or external) and analytics PoC Findings: Business Value
  • 7. ©2018 Cambridge Semantics Inc. All rights reserved. PoC Findings: Lessons Learned • The FIBO model works and delivers unique data insight capabilities • The Anzo tools work well and deliver value • Traditional problems: availability of people, access to data and good IT resources drive the adoption timeline. • FIBO model is comprehensive, but comes with some complexity • Not intuitive; Use requires learning • FIBO facilitates construction of simplified operational ontologies • Models and tools are standards based, but implementation required some adaptations and workarounds PoC Findings: Lessons Learned