Case Study: Santander Bank Polska achieves 90% transaction categorisation accuracy with WEBSENSA's Personal Finance Manager

Santander Bank Polska - Customer Case Study

Santander Bank Polska sought to enhance its customers' ability to manage their personal finances by intelligently utilizing their transaction data. The challenge was to develop a system that could automatically and accurately categorize spending and present it in a user-friendly format. To address this, the bank engaged WEBSENSA to develop a Personal Finance Management (PFM) tool.

WEBSENSA built the backend for the PFM system using Python and an Oracle database. Their solution featured a sophisticated transaction categorization engine that was trained over four months with live data. The implemented system achieved a 90% accuracy rate in transaction classification, surpassing market benchmarks, and has been successfully used by thousands of the bank's customers since 2016 to make smarter financial decisions.

Santander Bank Polska

Paweł Włódarczak

Santander Bank Polska