The Crédito Agrícola Group is a Portuguese financial group made up of a vast number of local banks – Caixas de Crédito Agrícola Mútuo – and specialized companies, with its central structures being the Caixa Central de Crédito Agrícola Mútuo. Established in 1911, with historical roots dating as far back as 1498, the Crédito Agrícola Group presently oversees 68 Caixas de Crédito Agrícola, maintains a network of 618 branches throughout Portugal, boasts over 400,000 associates, and serves 2.1 million customers. As one of the primary banking groups in Portugal, it holds a significant position in the financial sector.

The real estate division of Crédito Agrícola oversees the bank’s recovered assets—properties acquired through credit transactions and subsequently put up for sale as part of a divestment strategy. One of the key outputs of this department was a comprehensive monthly report detailing the bank’s evolving position, following rigorous internal evaluation controls. Due to being a substantial document of around 200 pages, the preparation of this report consumed 2 to 3 weeks every month, leaving the division’s personnel limited time for other tasks.

“It took us 2-3 weeks each month, so we couldn’t do almost anything else other than be here preparing this 200-page report.”

– Tiago Fernandes, Property Strategy and Management Office, Crédito Agrícola

Recognizing the time-intensive nature of the process, the reporting frequency was eventually adjusted to a quarterly basis. However, even in this revised format, the report continued to demand a significant portion of the department’s time, limiting its capacity to perform other tasks. The data utilized for this report was sourced directly from Crédito Agrícola’s Datawarehouse and underwent processing in Excel before finally being incorporated into a PowerPoint presentation.

After attending a Dashboard in a Day workshop conducted by our team at DevScope, Crédito Agrícola became acquainted with the capabilities of Power BI and decided to explore its potential. The bank enlisted the services of a consultant to develop a data model, create visualizations, and initiate work on automating data processes to streamline reporting. Unfortunately, the outcomes fell short of the team’s expectations, particularly in terms of visual presentation and data loading speed. To make matters worse, there was no notable reduction in the workload associated with the production of the report.

Despite these challenges, Crédito Agrícola saw potential in Power BI and reached out to DevScope to resume and enhance its implementation where they had left off.

Resuming a project midway poses unique challenges, and adapting to Crédito Agrícola’s existing data model added an extra layer of complexity to the task. While our team typically deploys our signature ETL framework, the intricacies of this project demanded a departure from the usual approach to achieve comprehensive process automation for all the metrics required in Power BI. This became the initial focus of our team’s efforts.

Subsequently, we expanded our scope to incorporate new indicators and implemented a visual presentation overhaul with the goal of enhancing the appeal and readability of the reports, ensuring they were not only informative but also visually engaging.

In the initial project plan, a fair portion of Crédito Agrícola’s data was sourced from Excel files linked to Power BI. Despite this reliance on Excel, the introduced automations played a crucial role in substantially decreasing the workload associated with these files. Furthermore, the automation significantly mitigated the risk of human errors that these files were susceptible to. This strategic implementation not only streamlined the data flow but also enhanced the overall accuracy and reliability of the information integrated into Power BI.

“There is no longer a risk of tampering with data by circulating alternative versions of an Excel sheet.”

– Filipe Ferreira, Property Strategy and Management Office, Crédito Agrícola

Maintaining a record of their activity was also crucial, especially for the internal control component the dashboard focuses on. However, due to the structure of Crédito Agrícola’s data warehouse, the files are currently being secured manually. The bank is working to overcome this hurdle and reduce its reliance on Excel by automating the entire process, aspirations that are part of mid-term plans, as achieving this goal requires an overhaul of the data warehouse.

The efforts put into the project resulted in a remarkable reduction in the time spent working on the report, slashing it from 2-3 weeks down to just 2-3 days. This efficiency gain proved so significant that it empowered the department to revert to monthly deliverables for their reports thanks to the substantial enhancement in the overall workflow for Crédito Agrícola.

“What took us between 2 to 3 weeks now takes us 2 to 3 days. This is a significant difference.”

– Tiago Fernandes, Property Strategy and Management Office, Crédito Agrícola

The data centralization achieved with this project also grabbed the attention of other departments within Crédito Agrícola, including the supervision department, responsible for overseeing non-compliance situations related to internal control. This department has been using the Power BI dashboard and found it to be highly effective. In light of this success, Crédito Agrícola is looking for ways to share the dashboard not only with other internal departments but also with regulatory bodies such as Banco de Portugal (Bank of Portugal) and other entities mandated by law. This reflects the project’s far-reaching impact and the potential for widespread adoption across other sides of the organization. Other departments have demonstrated keen interest in receiving training to acquire the skills to work with Power BI and leverage the tool to enhance their operations.

• Took over an ongoing complex Power BI project.
• Automated data processes that helped Crédito Agrícola streamline reporting in Power BI.
• Expanded the scope to introduce new indicators and a visual overhaul.
• Reduced report preparation time from 2-3 weeks to 2-3 days, allowing for monthly deliverables.