Corporate Data Warehouse for BelVEB Bank

The project on implementation of corporate data warehouse software based on a standard industrial model IBM BDW and the following IBM software platforms: InfoSphere Information Server (DataStage, Business Glossary), DB2, and Cognos BI.

The project was implemented to meet the following challenges:

  • Design and implement a unified data warehouse based on the standard industrial model with a degree of customization up to 30 percent.
  • Implement the algorithms of data upload from the accounting systems of the bank and external sources to the corporate data warehouse in line with the methodology of managerial accounting. To provide a possibility of performing adjustments.
  • Implement the approaches of data cleansing and quality control, as well as business rule verification
  • Build theme–based data marts designed to analyze general ledger data, loan portfolio, managerial accounting, and performance of the network of self–service banking equipment
  • Implement a business glossary of banking terms
  • Develop more than 90 scheduled reports covering the tasks of management reporting and reporting to the parent company and regulators.

IBA created a unified data warehouse based on the standard industrial data model IBM Banking Data Warehouse that covers the full range of analytical tasks of a commercial bank. Thus, IBA avoided typical mistakes and saved time when performing the project while using best global practices and the experience of over 200 banks worldwide.

In addition, the use of the standard industrial model will allow for avoiding extra expenses for the development of the system. The manufacturer makes ongoing efforts to improve the models while considering the future development of requirements by market regulators (Basel II / III, IAS, Sarbanes Oxley, AML).

The project on the implementation of the corporate data warehouse was successfully completed in 2014. Currently, IBA performs the maintenance and enhancement of the solution.

For the bank, the project resulted in a possibility of efficient and convenient analysis of various indicators and business areas, such as the calculation of marginal profitability of banking products, customers, or the center of financial responsibility.

In addition, the implementation of the corporate data warehouse allowed for automating and improving the quality of data in prudential reporting, and for implementing the managerial accounting in the form of interactive reports and dashboards with support for advanced imaging and data handling technologies, including the Drill–down/up technology and the support of mobile technologies.

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