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Accelerating AI with Trusted Data Models
Regulatory-ready, enterprise-wide Reference Model for Banks & Insurers. Designed to accelerate data platform modernization, analytics, and AI enablement with conformed data foundation for every insight, decision, and is powered by trusted, well-governed data.
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BigTapp’s Reference Data Models unify core concepts (Party/Customer, Product, Account/Policy, Transaction/Event, Risk, Pricing, GL linkage) with governance and time-variance built in. The models are AI-ready (semantically consistent, retrieval-friendly) and ship with mapping templates and validation packs so you can move from source discovery → conformed model → governed analytics fast and make retrieval-augmented workflows and agent skills more accurate.
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With the structures aligned to FSI obligations (e.g., Basel III/credit risk, AML/KYC, IFRS), the Reference Data Model is governed by Design for lineage, audit trails, data quality anchors, SCD2/time-series snapshots.
Subject Areas: Party & Relationship, Product & Pricing, Accounts & Facilities, Transactions & Events, Risk & Regulatory, Channels & Interaction, GL & Posting
The master data blueprint for next-generation insurers, connects customer, policy, claim, and risk data — accelerating underwriting intelligence, claims automation, and AI-driven personalization at enterprise scale — ensuring compliance and readiness for AI, IFRS 17, and solvency analytics.
Subject Areas: Party & Roles, Products & Coverage, Policy & Billing, Claims, Risk & Underwriting, Reinsurance, GL & Posting
B2C/B2B, unlimited hierarchy depth
Accounts/Transactions/Products (clean extensibility)
Lifecycle events, auditability, reversals, corrections
As-was history and point-in-time analyses
Products, channels, geography, legal entity, calendar
Trace from business transaction to accounting impact.
Typical platform design/build reduced significantly with reusable patterns and DDL starters.
Regulatory-relevant fields and lineage reduce rework during audits/exams.
KPI/semantic starters shorten time to dashboards and models.
Synergised various data sources across Life, P&C and Group into a unified data structure enabling analytical initiatives, reduced dependency on data availability and ensuring cleansed data to drive decision making faster.
Data extraction from different systems, ensuring geo specific attributes are available in a unified structure. Providing the ability to build the curated with ease.
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