The banking sector is undergoing major changes and redefining its way of doing business, as a result of economic, regulation and technological changes. To do so, it is paramount to find solutions that allow them to improve risk management, provide better service to their customers and improve their operational efficiency. One such example is the Bank of Portugal. With the beginning of the financial crisis in Europe that has later spread to Portugal leading to the Troika bailout (International Monetary Fund, European Financial Stabilisation Mechanism, and the European Financial Stability Facility), the Bank of Portugal has been instructed to ask financial institutions for a set of systematic information to be provided on a regular basis.
This request had clear implications on the IT systems, which needed to be changed in order to address these requests. To ensure its robustness, availability and long-term perspective, information had to reside in a Data Warehouse, which would not only allow for a report to be made, but also to allow to extract timeline statistics of all the available information.
Notwithstanding, these changes are not so straightforward. In fact, as financial institutions attempt to include their information on a Data Warehouse, challenges arise, which can usually be summarized as the large volume of data, the diversity of information sources and the need from business areas to seek the information that resides on it.
As such, one of the greatest challenges that needs to be addressed consists on data normalization, since the fact that there are several business areas within an organization leads to different concepts for the same indicator. One such example can be illustrated as follows: the business area of the bank perceives the due credit, for simplification of the reporting, as including the component of due interests. On a different perspective, for the financial reporting, this same indicator can only have the due credits, hence creating the need for two different indicators, one for due interest and one for due credits and interest.
This simple case highlights the relevance of streamlining concepts and the need to create a cross-group committee within the organization that defines and updates all existing concepts and, at the same time, ensuring that they are properly used by the reporting systems of the institution. In order to make this streamlining process more effective, we propose that all information be integrated into a dictionary of concepts, based upon an MD (Master Data Management) tool, which will ensure information consistency throughout the organization, regardless of the data source used and of the entity for which this information is created.
Another challenge is the volume of data to integrate, in which business intelligence systems are used, in order to adopt best practices and optimize processes, allowing the manipulation of large quantities of data within the processing timeline, which generally is not very long.
Lastly, it is critical to create a set of predefined reports with agile adaptation and comprehension. The strategy, in this case, includes the creation of a set of templates that will be afterwards used, ensuring the streamlining of criteria and layouts in all reports the organization provides.
As such, BI4ALL has developed a solution that plays a pivotal role on the decision making process for top managers, providing customer-centric data reports that are relevant to allow increased adaptability to constant change. This solution will lead all analytic process and will allow the management of the decision making process, increasing the business performance. BI4ALL will support you in the implementation of the best solution for your business, because each solution us customized for the needs of each customer and business.