
Identifying and Stopping Revenue Leakage

Industry
Fintech
Challenge
A growing fintech company discovered it was losing revenue due to operational inefficiencies, billing inaccuracies, and missed opportunities in upselling. The company lacked the necessary tools to pinpoint where the revenue was leaking and needed a solution to plug these gaps, recover lost revenue, and optimise its financial operations.
Solution
The team began by collecting and consolidating relevant data from the company’s ERP, CRM, and financial reporting systems, as well as customer transaction data, into a unified platform. This data was processed and cleaned using advanced data processing techniques, ensuring that inconsistencies and inaccuracies were addressed before analysis. By applying big data technologies, they efficiently handled large volumes of transactional and billing data, allowing them to identify key areas of revenue leakage, such as delayed payments, missed invoices, and errors in applying discounts.
Next, they utilised advanced analysis and predictive modelling to forecast potential future leakage areas based on historical patterns and transaction behaviours. These insights were translated into business intelligence recommendations, enabling the company to streamline its billing processes and address upselling opportunities. Additionally, the results were presented through visualisation tools like interactive dashboards, providing the client with a clear understanding of where revenue was being lost and how to address it.
Results
Within three months, the fintech company was able to recover $1.5 million in lost revenue by resolving billing errors and streamlining their invoicing process. By addressing revenue leakage, the company increased its revenue from existing customers by 15%. The proactive approach to identifying potential revenue leakage also helped the company improve its financial oversight and reduce future risks..
Key Takeaways

Data collection from financial systems and customer transactions identified revenue leakage points.

Data processing ensured accuracy and reliability in the analysis.

Predictive models forecasted future leakage risks, preventing future losses.

Business intelligence transformed insights into actionable solutions, improving revenue recovery.
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