Glossaries and data models for banking and financial markets
IBM Banking and Financial Markets Data Warehouse is an industry blueprint that provides business vocabularies, data warehouse design models, and analysis templates. The IBM Banking and Financial Markets Data Warehouse models help you to accelerate the development of data architecture, data governance and data warehouse initiatives. The models also provide a comprehensive, scalable and flexible framework for strategic banking data initiatives.
Benefits for banking and financial markets
Accelerate risk and compliance initiatives
Accelerates analysis and design phases of projects to onboard regulations and standards. Provides out-of-the-box building blocks for obligations such as GDPR, CCAR, CCPA, and Basel II/III.
Consolidate meaningful financial data
Enables the consolidation, governance and design of clean, meaningful banking and financial market data across multiple channels and products.
Minimize errors and development costs
Facilitates an incremental approach to integrated reporting, which can reduce risk and minimize development costs. Reduces the time to scope requirements and customization needs.
Address business and regulatory requirements
Customer relationship management
Customer-centric initiatives and comprehensive relationship management and analysis are key to market-leading financial institutions today. The IBM Banking and Financial Markets Data Warehouse models have extensive content describing the characteristics, behavior, interactions, relationships and financial status of customers to support customer relationship management data activities within financial institutions.
Asset liability management and liquidity risk
Given the recent focus on long-term funding requirements for liquidity risk, the IBM Banking and Financial Markets Data Warehouse V8.10 Glossary now includes the specific alignment of the fundamental characteristics of asset liability management (ALM) and liquidity risk information with the Glossary model. This allows customers to isolate and unify the description of the information required by ALM and liquidity risk solutions.
The IBM Banking and Financial Markets Data Warehouse models support analytical capabilities in the area of payments. The models provide extensive descriptions of the elements of payments, with specific analytical requirements to describe the typical reporting patterns of commercial payments. The focus is particularly on commercial payments; however, many aspects of the analytical requirements defined are also relevant to retail payments.
The Foreign Account Tax Compliance Act (FATCA) was introduced to prevent US persons and entities from evading income tax by holding assets through foreign accounts. Based on an in-depth analysis of the FATCA legislation document, related tax forms and documents concerning the Intergovernmental Agreements, the IBM Banking and Financial Markets Data Warehouse models include the critical business data elements that exist within those documents.
Basel II/III framework support
A reliable data warehouse model is key to a successful risk data aggregation and reporting solution. The model must be extensive to cover all the risk aspects of the financial institution, while also allowing for the adaptability of local supervisory and long-term regulatory changes. The IBM Banking and Financial Data Warehouse models are designed to support a consolidated enterprise risk solution, incorporating all aspects of the risk data from credit, market, liquidity and operational risk.
Support for data privacy and data protection (GDPR/CCPA)
IBM Banking and Financial Markets Data Warehouse provides an industry-specific vocabulary that can help discover and govern privacy data. It includes KPI templates for regulatory reporting and a hierarchy of General Data Protection Regulation (GDPR) and California Consumer Privacy Act (CCPA) terminology. The glossary and underlying data warehouse models help ensure the enterprise data architecture can provide the necessary data artifacts to report on data protection issues and help determine and define which personal data types are needed.
Expert resources to help you succeed
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