FIB-DM website, March 29, 2021, Jurgen Ziemer
The underlying list compiles from the form submission email or company field:
ABN AMRO, AK BARS Bank, APS Bank, Absa, Abu Dhabi Islamic Bank, Affinity Federal Credit Union, Akbank, Al-Rajhi Bank, Allianz Bank Malaysia Bernard, Allica Bank, Alpha Bank, AmeriCU, American AgCredit, Arab Bank, Arab bank, Arion Bank, Asian Infrastructure Investment Bank, BBVA, BMO, BNP Paribas, BNY Mellon, BOK Financial, BanBajio, Banco Caja Social, Banco Supervielle, Banco del Progreso, Banco del Sur, Bank AL Habib, Bank Indonesia, Bank Maskan, Bank Muscat, Bank Nationale Canada, Bank OZK, Bank Of America, Bank al Etihad, Bank of China, Banque Du Caire , Barclays Wealth, Borner Banca, Brown Brothers Harriman, CAF, CDG Capital, CIBC, CaixaBank, Capitec, China International Capital Corporation, Circulo de Credito, Citi, Citizens Bank, Coast Capital Savings, Commonwealth Bank of Australia, Community Preservation Corporation, Conexus Credit Union, Coppel, Cornèr Banca, Credicomer, Credit Suisse, Cross River Bank, DBS, DIGIPAY, DMCard, DNB, Danske Bank, Davivienda, Deutsche Bank, Digipay, Discover, EMPAYS PAYMENTS SYSTEM PVT LTD, ETHD, Earnest, Ecobank, Emirates NBD, European Investment Bank, Export–Import Bank of the US, FE Credit, FHL Bank of San Francisco, FMO, Fannie Mae, First Citizens Bank, First National Bank, First National Bank of Pennsylvania, First Rand, Fulton Bank, Fulton Financial Corporation, GMF, Gazprombank, HDFC Bank, HSBC, HawaiiUSA Federal Credit Union, Holm Bank AS, IADB , ING, IOM, Illimity, Innovation Credit Union, Itau Unibanco, Itaú Unibanco, JPM Chase, Jyske Bank, Karnataka Vikas Grameena Bank, Kiwibank, Kleinwort Hambros, Komplett Bank ASA, Liberis, Liberis Finance, Lloyds Banking Group, MTS, Macquarie, Mashreq, Metro Bank, Minbank, MoneyExpress, Morgan Stanley, National Bank of Canada, Nedbank, Nomura, Northern Trust, OCCU, OTP Bank, OceanFirst Bank, Oldmutual, PayMaya, PayPal, Peleman, People's United Bank, Qatar National Bank, Quicken Loans, RBC, RSLFC, Raseedy, Reserve Bank of Australia, Rightvi, Rivermark Community Credit Union, Royal Bank of Canada, SBL, SEB, SVB, Sagicor Group Jamaica, Sallie Mae, Santander, Saturn Bank, Saxo Bank, Sbanken, Sberbank, Scotiabank, Sicredi, South African Reserve Bank, Standard Bank, Standard Chartered, TP Bank, Tejarat Bank, Toyota Financial Services, U.S. Bank, UAP/OM, UBS, UCPB, UOB, Union Bank, United Amara Bank, VBT, VIB, VTB, VUB, Vietnam International Bank, WLB, Webster Bank, Wells Fargo, WesBank, Westpac, Wintrust Financial, Worldpay, Zürcher Kantonalbank
FIB-DM website, January 25, 2021, Jurgen Ziemer
The FIB-DM NORM January 2021 version is available. The 2048-entity normative data model derived from the FIBO 2020/Q4 Production release.
Ontotext blog, January 22, 2021, Kevin Tyson
In this post, I will present a technique employing GraphDB’s similarity indexes, which helps demonstrate the alignment of FIBO with other vocabularies in specific business contexts.
October 21, 2020, Greg Steck, FI Consulting, Thomas Cook, Cambridge Semantics, Inc.
Gartner reported that close to 50% of AI and machine learning projects fail in part due to challenges with "data complexity and systems integration". In the context of risk analytics, combining macroeconomic data with internal risk data, tracking data provenance, and staging analytics-ready data for constantly changing business requirements illustrate several of those data challenges. Using publicly available data for 40 million mortgage loans over 20 years, we built a knowledge graph leveraging the FIBO ontology to demonstrate a next-generation analytics platform that:
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Reduces time spent on data engineering tasks by over 50%
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Natively captures detailed data lineage for each reported output metric
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Rapidly and flexibly generates input data for deep learning models
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Increases speed to delivery of sensitivity analysis and stress testing by generating model predictions directly in the graph database
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Enables a more holistic capture of model risk management data
This webinar explores:
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Challenges common to a risk analytics pipeline
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Comparison of relational data model and graph approaches
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Application of graph analytics to mortgage loan data
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Deep neural networks and graph convolutional networks
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Scalable graph computation with TensorFlow
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Use cases in adjacent areas including customer service, collections, fraud and AML
Ontotext blog, October 15, 2020, Kevin Tyson
This article describes the utility provided by property paths and reasoning for exploring and understanding the Financial Industry Business Ontology (FIBO) - a big OWL-based ontology of more than 1000 classes and its accompanying SKOS-based vocabulary. We use GraphDB’s Workbench to load FIBO, experiment with different reasoning profiles (OWL 2 RL proves more useful than RDFS), comprehend its structure using the Class Hierarchy diagram and explore it with the Visual Graph facility. Finally, we demonstrate how GraphDB can be used to combine OWL 2 RL reasoning and property paths combined to check the structural integrity of FIBO.
March 15, 2020, EDMC Team
This article describes the utility provided by property paths and reasoning for exploring and understanding the Financial Industry Business Ontology (FIBO) - a big OWL-based ontology of more than 1000 classes and its accompanying SKOS-based vocabulary. We use GraphDB’s Workbench to load FIBO, experiment with different reasoning profiles (OWL 2 RL proves more useful than RDFS), comprehend its structure using the Class Hierarchy diagram and explore it with the Visual Graph facility. Finally, we demonstrate how GraphDB can be used to combine OWL 2 RL reasoning and property paths combined to check the structural integrity of FIBO.
Cambridge Semantics blog, Jan 6, 2019, Marty Loughlin
... we can use the conceptual model to harmonize data from diverse sources and to create governed data sets for business use case consumption. At Cambridge Semantics, our Anzo platform makes this approach operational at enterprise scale. And, since it is based on W3C open graph standards, it natively supports industry models like FIBO ...
Neo4j blog, Aug 13, 2018, Navneet Mathur
Neo4j Is FIBO-Ready - The FIBO ontology is now available as add-on to the Neo4j platform, so you can create an enterprise canonical data model that:
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Uses the same infrastructure to store risk data lineage as well as governance metadata such as definitions, related terms, etc.
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Provides a unified access layer that spans data silos
As a result, by using Neo4j, you can integrate data governance, compliance reporting and real-time data movement into a single solution that guarantees data consistency across operational and regulatory systems.