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Gain insight into customer trends and historical data – optimize discounting, improve retention and segment your customer base to effectively acquire new customers. Data warehouse provides the basis for quality analysis of available data by deriving accurate information.
In recent years, banks have accumulated large amounts of data from business and now it is time to turn data into money. Such great amount of data provides a big opportunity for analysis. Simplify the way you gather data, have a single point of truth and ensure data quality, consistency, accuracy, complexity and the right timing.
Banking Data Warehouse model is business oriented, designed to support different business needs from regulatory and daily / weekly / decade / monthly operational and management reporting to very complex ad hoc analysis and simulations. Our Data Warehouse model is based on industry standards and implementation best practices.
Banking DWH model
®
Highlights
Based on industry best practices and open for all necessary modifications to adjust to individual customer needs
Business oriented, designed to support different business needs from regulatory and daily / weekly / decade / monthly operational and management reporting to very complex ad hoc analysis and simulations
Consists of more than 500 Entities (Tables) grouped in 31 Subject areas, with more than 5.800 attributes, and more than 1.500 keys
Possibility to integrate data between bank and leasing company or bank and insurance company in one common data warehouse model enabling 360 customer view
Work on the model is a continuous endeavor, in respect to banking regulations, IFRS standards, New Analytical requirements, New markets, Data modelling standards
Banking DWH model
®
Benefits
Enables business users to generate quickly actionable insights and easily customize or extend DWH capabilities
Implementation can be done incrementally delivering fully functional phases that will result in integrated management information system
Minimizes development costs
Reduces the risk of failure by facilitating an incremental approach to delivering integrated ODS and data warehouse solution
Fosters collaboration and approval between business and IT, as necessary, to turn business requirements into actionable solutions
Provides a solid basis for regulatory reporting as well as decision support and executive KPIs
Enables organizations to achieve modern DWH architecture, logical model with clean relationships between entities and future proof DWH to deal with upcoming requirements
Banking DWH model
®
Details
We are FIBO compliant!
The Financial Industry Business Ontology (FIBO) is a business conceptual model that describes how all financial instruments, business entities and processes work in the financial industry and Banking DWH model follows the logic of FIBO and shares the same ontologies as FIBO and use same business glossary (Customer, Party, Location, Account, Collateral etc.)
- Common business functional group subject areas, except for locations
- Customer
- Reporting, business items and KPI's
- Location
- Customer account
- Operational risks
- Product, rates
- Credit protection
- Classification, segmentations
- HR
- Financial subject areas (GL, reporting, OPEX, CAPEX, transactions)
- ETL execution
- Party (individual, legal, entity, OU)
Petrol is a company that operates in several industries; Oil and Gas, Retail and Utility. Different business requirements are challenging to fit to same reporting structures. Retail DWH model is covering most of our important business areas. It is flexible, easy to use and modify so implementation of selected Subject area is quite fast. Subject areas designed in the model are also great reference for Business Analysts when elicitating and structuring business requirements.
– Andreja Štirn, Director business intelligence
Telco DWH model has been proven to be flexible and easy to use which enabled faster time to the market of CT products and significantly easier maintenance. It did not require any changes since the implementation few years ago, besides integration with new systems, which is the best indication of its quality.
– Jovana Mihajlovac, Head of Enterprise IT solutions
We are producing and collecting anenormous amount of data. Implementation of Telco DWH model enabled us to achieve competitive advantage by allowing clean data consolidation across multiple systems, minimized our development cost and helped us transform our business requirements into solution that works best for us.
– Andrija Derežić, CIO at United Group
We are member of the one of the world’s largest mobile telecommunications companies, with over 133 million customers across 12 markets, which speaks a lot about extent of our needs when it comes to managing our collected data. Ooredoo Algeria recognized Telco DWH model as a model that allowed us to reduce the risk of failure, manage our data better and minimize development cost while at the same allowing modifications that we need when we need them.
– Badredine Allouche, Chef de service DWH
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Banking DWH model
®
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The Financial Industry Business Ontology (FIBO) is a business conceptual model that describes how all financial instruments, business entities and processes work in the financial industry and Banking DWH model follows the logic of FIBO and shares the same ontologies as FIBO and use same business glossary (Customer, Party, Location, Account, Collateral etc.)
Banking DWH model® is an exclusive intellectual property of Poslovna Inteligencija. PI grants a nontransferable and nonexclusive right to use the Banking DWH model®, with delivered customizations and extensions to its Customers who purchased the model.
Simplify the way you gather data, have a single point of truth and ensure data quality, consistency, accuracy, complexity and the right timing.
Data warehouse models
Improve your decision-making process based on quality data using advanced analytics and be a part of digital transformation. Extract consumer insights to learn more about their preferences and reinvent the customer experience.
Gain insight into customer trends and historical data – optimize discounting, improve retention and segment your customer base to effectively acquire new customers. Data warehouse provides the basis for quality analysis of available data by deriving accurate information.
Make informed and data-driven decisions and transform information into meaningful actions. Turbulent times of saturated markets and new regulations, highlight the importance of the availability of the right information at the right time for the (re)insurance industry.
Retail DWH model ® is standard industry data warehouse model applicable for retailers and wholesalers, covering traditional Business Intelligence requirements, regulatory requirements and Big Data Analytics requirements.
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