book

Designing Financial Data Architectures

Name: Designing Financial Data Architectures
Author: Tamer Khraisha
ISBN: 9798341627178

by Tamer Khraisha

December 2026

Intermediate to advanced

400 pages

8h 57m

English

O'Reilly Media, Inc.

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Brief Table of Contents (Not Yet Final)
Preface
Who This Book Is ForWho This Book Is Not ForMy Approach to Writing This Book
1. An Introduction to Financial Data
Finance BasicsFinancial Assets, Instruments, and SecuritiesStocks, shares, and equityBonds and fixed-incomeDerivativesSecurities exchangesClearing and SettlementThe Financial Data EcosystemFinancial Data Generation MechanismsFinancial Data SourcesFinancial Data Arrival and Exchange MechanismsFinancial data types, formats, and structuresCharacteristics of Financial DataFinancial Data Value ChainData management challenges in financial servicesData Silos and FragmentationFinancial Data Standardisation Cross-Entity LinkageReference Data ManagementLegacy SystemsData Quality and IntegrityData Security and PrivacyData Integration and AggregationScalability and PerformanceRegulatory ComplianceAI AdoptionSummary
2. Financial Data Architectures
Contextualizing ‘Architecture’ in IT: A Broader PerspectiveDefining financial data architectureWhy is a financial data architecture needed?When is a financial data architecture not needed?Very Small Businesses with Simple Data NeedsStartups in the Very Early StagesShort-Term ProjectsHighly Isolated DataReliance on Third-Party PlatformsData Architecture MaturityComponents of a Financial Data ArchitectureFinancial Data ModelsFinancial Data GovernanceIntegration and InterfacesTechnological InfrastructureProcessing and Transformation LogicPipelines and OrchestrationAccess LayerReference and MetadataMonitoring and ObservabilityConstraints and influences on financial data architecturesBusiness RequirementsTechnology DriversEconomicsBusiness PoliciesRegulatory RequirementsCategorising financial data architecturesClassification by Storage TechnologyDeployment-Based ClassificationClassification by Data Modeling ApproachProcessing-Focused ClassificationBusiness-Focused ClassificationClassification by Data Ownership & GovernanceWhy master the art of financial data architecture?Data is the BusinessDomain-Driven Development is Gaining GroundA Required Human Skill in the Age of AIMarket DemandFinancial InnovationSolve Complex ChallengesCareer LeverageSummary
3. Foundations of Financial Data Modeling
What Is Financial Data Modeling?Diagramming and Visualization of Financial DataCrow’s Foot NotationBarker NotationUnified Modeling LanguageFinancial Data Modeling Life CycleConceptual data modelingLogical data modelingPhysical Data ModelingModeling Financial Data LifecyclesSummary
4. Advanced Financial Data Modeling Techniques
Point-in-Time Modeling of Financial DataUnderstanding the Temporal Dynamics of Financial DataThe Consequences of Non-PIT Financial DataApproaches to Point-in-Time Data ModelingLifecycle-Aware Modeling of Financial DataModeling Financial Market LifecyclesFinancial Event Data ModelingSemantic Modeling of Financial DataControlled Financial VocabulariesFinancial TaxonomiesFinancial OntologiesFinancial Message ModelingWhat Is a Financial Message?What is financial message modelingAnatomy of a financial messageISO20022: The universal financial message standardISO20022: the MetamodelISO20022: The scope levelISO20022: The conceptual levelISO20022: The logical levelISO20022: The Physical levelISO20022: VariantsThe ISO 20022 Repository: The Financial VaultISO20022: A Simplified Illustrative ExampleSummary
5. Financial Reference Data
Financial reference data defined: a conceptual breakdownFinancial InstrumentsFinancial PartiesFinancial ContractsFinancial TransactionsWhere Reference Data Fits in the Financial Data LandscapeReference Data vs. Master Data vs MetadataFinancial Reference Data vs Market data vs Transaction DataFinancial Reference Data vs Company ProfilesThe Critical Role of Reference Data in FinanceInput to financial transactionsData Integration and HarmonisationRegulatory, Risk, and Compliance ReportingValuation, Pricing, and AnalyticsTransaction Cost AnalysisCounterparty and Entity VerificationTypes of Financial Reference DataCountry Reference DataSector Reference DataLegal Entity Reference DataMarket Infrastructure & Venue Reference DataCurrency Reference DataStock Reference DataFixed Income Reference DataDerivative reference dataFund Reference DataCorporate actions dataPayment Reference DataSummary
6. Designing Financial Reference Data Architectures
Step 1: Understand Your Business Needs and WorkflowsFinancial Market lifecyclesEntity Scope & CoverageRegulatory & Compliance RequirementsReference Data Acquisition and SubscriptionsStep 2: Understand the challengesInconsistent Data ModelsLack of a Single Source of TruthLegacy Infrastructure and Technical DebtManual Intervention and Spreadsheet DependencyEvolving Standards and Regulatory RequirementsEntity matchingGovernance and Cultural BarriersData QualityStep 3. Model your Reference Data LifecycleGenerationAcquisition/IngestionCleansing, Normalization and EnrichmentStorageDistributionUsage and MaintenanceUpdateArchivalRetirement/DeletionStep 4. Design a Data Governance FrameworkData QualityData IntegrityData Usage and SpendData ArchivalStep 5. Design your Data Collection StrategyStart with a business discussionIdentify the required reference data elementsIdentify technical requirementsDefine a data provider evaluation frameworkOutline your ingestion layerStep 6: Design your Identification SystemDesired properties of a financial identification systemCreate an internal identifierStep 7: Design your Entity Extraction, Resolution, and Linking capabilitiesEntity ExtractionEntity ResolutionCross-Entity LinkageStep 8: Model your Reference DataGeneral principles for modeling financial reference dataUnderstand your business needsAim for structured data firstAvoid the “one huge table” anti-patternDefine common attributes explicitlyLeverage SemanticsDesign for Point-In-TimeDefine uniqueness rulesAvoid over-normalizationDeep dive: Modeling a Security MasterThe Generalization/Specialization approachThe Product Composition ApproachStep 9: ⁠Design your Reference Data FlowsFlow and Task DefinitionLifecycle-oriented reference data flowsStep 10: Design the Consumption LayerStep 11: Define Technology Selection PrinciplesData storage technologiesData Distribution TechnologiesFlow orchestration technologiesData management technologiesSummary
About the Author

Content preview from Designing Financial Data Architectures

About the Author

Tamer Khraisha is a senior software and data developer, as well as a scientific author, with over a decade of experience in both industry and research. Tamer’s experience combines a solid background in financial markets with substantial expertise in software engin eering. He did his undergraduate studies in finance and economics and earned a PhD in network science. Tamer’s research interests are focused on financial markets, data, and technology. During his professional career, Tamer has worked with various FinTech startups, where he designed and built data-driven cloud platforms for financial research, artificial intelligence, and asset management, as well as international payment systems.

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Designing Financial Data Architectures

by Tamer Khraisha

About the Author

Become an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
and much more.