In How to implement a Credit Risk Data Warehouse – Part 1 I did an overview and an executive summary of the activities required for the delivery of Credit Risk Data Warehouse project. If you haven’t read this already I recommend you read How to implement a Credit Risk Data Warehouse – Part 1 first.
In addition to the above, the DW Architect, Project Manager & their teams will have to work and define the implementation approach, which will allow the Implementation team to complete the work on an accelerated timeline.
Usually a multistage “work breakdown structure” approach for the implementation phases of the project is preferred.
Because of the complexity surrounding the Credit Risk DW implementation, and depending on the nature of the bank doing the implementation, the project can be divided into four distinct implementation work streams covering the following areas:
- Wholesale banking,
- Retail banking,
- Securities/trading,
- Bank securities.
Having various work streams provides the advantage of dividing the efforts and opting for a parallel execution to meet the completion timelines.
It’s mandatory that in the first stage of the engagement to:
- Establish the project governance framework and the communication strategy,
- Identify key stakeholders,
- Define the high-level test, training strategy and approach
and once these are set the Implementation team has to work closely with the Business team during the subsequent stages of functional and technical design and project implementation.
During the functional design stage, a workshop approach usually facilitates an in-depth analysis that drives out any required changes to be made in the bank’s finance department.
Being the project’s DW Arhitect it’s your responsibility to work closely with the technical team and to help them complete the technical application design.
Key steps of this process include:
- Confirming source-to-target mapping.
- Designing extract, transfer and load (ETL) rules, standards and procedures.
- Designing interfaces for the various in-scope source systems.
- Building a working prototype that integrates a physical data model.
- Developing a training plan.
- Building test plans based on functional specifications and designs for unit, system integration, performance and user acceptance testing.
Finally, the Implementation team will commence the build stage of the project the development environment previously configured to build ETL maps and integrate interfaces as set during the design phase.
As part of this process data & master data dictionary has to be finalized for the data model, unit testing has to be executed and passed and a few pilots & trials need to be carried out to demonstrate the new business processes.
After completion of testing and validation of the system and data feeds, the implementation team has to support the Release Management and Production support teams to migrate the Credit Risk DW into a production environment.
Once the system is live, continual support has to be facilitated by the implementation team in order to go through at least a month-end and year-end close period.
An Credit Risk DW reporting project will gave the bank a centralized and powerful mechanism to analyze and report on its financial data.
The Credit Risk DW database will establish a consolidated data store for a majority of the bank’s financial information, which can now be leveraged for other management reporting activities.
One of the challenges that needs to be achieved is the ability to bridge the gap between functional and technical requirements in order to deliver results quickly and correctly.
A project of this nature required a tight connection between the broad functional knowledge of Basel and the leading industry practices in finance with the technical and architecture specific experience.
Last but not least on the final stages of the project the focus has to be on training key bank personnel on the system’s functionality that will help the institution gain real benefits from the implementation, while equipping it to operate the system going forward.
Until next time,
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Article originally published on: Linkedin – How to Implement a Credit Risk Data Warehouse – Part 2
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