Case study

Personal Finance Manager for Santander

WEBSENSA developed an innovative Personal Finance Management tool for Santander Bank Polska, significantly enhancing customers' financial spendings management.

Background

Santander Bank Polska, one of the largest banks in Poland, is among the market leaders in the use of modern technologies in banking services.

Santander Bank regularly introduces innovative functionalities that help their customers take care of both personal and corporate finances.

Challenge

The primary challenge for Santander Bank Polska was to create a system that could intelligently utilise customer transaction data.

The goal was to design a software solution that could not only categorise each transaction into specific groups such as food, clothing, and utilities but also present this information to customers in a user-friendly and actionable format. This required a deep understanding of user needs to ensure the solution was both ergonomic and effective, providing real value in helping customers manage and plan their expenses.

Solution

WEBSENSA responded to this challenge, developing Personal Finance Management Engine combined with a Transaction Categorisation Tool.

Our part of the project was to handle the backend layer of the PFM software. We used Python with an Oracle database to develop a professional risk management engine that categorised the transactions of Santander’s customers.

Ww designed and developed a user-centric web application that provided customers with a clear view of their spending habits, broken down into various categories, and allowed for detailed analysis over different time periods.

Project Execution

The initial phase, managed by Santander’s in-house team, focused on integrating data banking systems with the software and completing frontend development. This set the foundation for WEBSENSA’s expertise to shine in the subsequent phase.

WEBSENSA's role involved crafting the backend architecture using Python and an Oracle database. Our team, comprising five skilled developers and a project manager, worked to develop a sophisticated engine for categorising transactions. This engine was meticulously trained over four months with live data to ensure its capability in accurately categorising transactions.

Throughout the project, communication and project management were streamlined using tools like Jira, Skype, and Microsoft Teams, adapting efficiently to remote working conditions.

Results

The synergy between both teams led to the timely and successful delivery of a high-quality PFM system, reflecting WEBSENSA's commitment to understanding client goals and customising solutions accordingly.

One of the main success measurements was the quality of the categorisation engine. Our client's tests showed that the percentage of correctly categorised transactions was 90%. They considered it a great result compared to other categorisation tools on the market.

Santander bank has been using our software for 6 years with no major complaints about the data presentation.

Client's Review

  • Quality: 4.5
  • Schedule: 5.0
  • Cost: 5.0
  • Willing to refer: 5.0
They do their best to understand what clients are trying to achieve and customize a solution that fits their needs. – Paweł Włódarczak, Santander Bank Polska

Contact us

Interested in implementing a similar solution for your business? Contact us – our experts are ready to tailor our offer to your specific needs.

Let's talk about your project!

Contact us or use our interactive tool to estimate your project.

Discover other case studies

Knowledge Chat for Veolia Energia Polska

Veolia Energia Polska engaged WEBSENSA to create a conversational chatbot, providing employees with seamless access to company knowledge.

AI Shopping Recommendation Engine for Good Sort

WEBSENSA collaborated with Good Sort to develop an AI-powered shopping platform that transforms the way consumers receive expert product recommendations.