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  • Writer's pictureLuandrie Potgieter

Automating Daily Trading Revenue Reporting Using PowerApps and Python

Updated: Nov 16, 2023



Introduction

One of the major players in the African banking space faced challenges with their daily P&L (Profit & Loss) approval and signoff process. Deadlines were often missed, leading to regulatory fines and operational inefficiencies.


An application developed by the bank's IT support team addressed these issues by automating the workflow and improving turnaround time.


The Customer's Challenge

A prominent banking institution in Africa specialising in corporate and investment banking struggled with the reporting on their daily P&L numbers. Because the reporting of these numbers is mandated by the regulators with a daily deadline, the bank is under immense pressure to deliver on time every day.


Their daily P&L process relied on time-consuming manual adjustments and sequential country-by-country calculations which consistently led to significant time delays.


The existing solution required a 20 - 30 minute calculation process per country. Because of the way in which the database was set up, countries could not run in parallel. This process exposed the bank to the risk of regulatory fines and impacted its overall operations.


The bank initially considered reengineering the database to split the countries and reduce resource dependency but ultimately sought a quicker and more efficient solution.


A Customised Solution: Automating P&L Processes

The IT support team then developed a new solution to address these challenges. By leveraging Microsoft Power BI and Python, they modernised the P&L process and also introduced agility.


This new system addressed the governance gap and de-risked the daily P&L reporting and

control process from missing the deadlines. The team created a Power BI dashboard with the already calculated P&L numbers, and incorporated functionality using PowerApps that sends emails to the relevant stakeholders for sign-off.


Python was then used to create a bot that can automatically download and store the data into the warehouse.


The Results

  • The solution addressed a major gap in the governance process by ensuring consistent sign-off of the P&L by embedding the automated workflow in the daily process.

  • It improved efficiencies and turnaround time in the daily reporting process.

  • It modernised and introduced agility in the P&L process by leveraging Microsoft Power BI, Microsoft PowerApps and Python.

Conclusion

The new solution automated the P&L approval workflow, embedding it in the daily process. This ensured consistent sign-offs of daily trading revenue and improved efficiencies in the daily P&L reporting process.


As a result, turnaround times were significantly reduced, and the bank was better equipped to meet regulatory deadlines.


Download the case study here


 

Contact us to discuss how this solution streamlines manual and time-consuming processes to improve operational efficiency so you can achieve similar results in your organization.



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