Enriching transactions with Categorization: a must-have in digital banking
Visualising consumer spending through categories is a must in digital banking. Learn about its benefits and implementation to enrich transaction data.
- Published
Money management is more important than ever, but it’s also a challenge for many. Nearly 40% of UK adults admit they’re not confident in handling their finances. That’s where banks have an opportunity - and a responsibility - to step in, starting with a tool most people already rely on: the banking app.
The challenge is that many apps still fall short with clunky user experiences and incomplete data that leave users feeling stuck. By integrating smart categorization, banks can make it easier for users to understand and manage their money with confidence.
At Snowdrop Solutions, we’ve built the Merchant Reconciliation System (MRS), a trusted API that’s already being integrated by leading banks across Europe, the Middle East, and the Asia-Pacific region. As consumers demand more intuitive, user-friendly banking apps, MRS API helps meet this growing need for better user experiences.
In this article, we’ll explore how transaction categorization in digital banking works and why it’s a must-have feature for banks and financial institutions looking to boost customer engagement.
What is Transaction Categorization and How Does it Work?
Transaction categorization is a process that allows banking apps to group transaction data, giving both clients and banks a clear view of where money is being spent. This process examines details like transaction descriptions, merchants, amounts, and other data points to accurately classify each purchase.
For example, when a user buys groceries, the transaction is automatically categorised under “groceries.” At the end of the month, the user can easily see which categories have taken up the most of their budget, helping them make smarter financial decisions. By using labels, brands, attributes, or other criteria, transaction categorization provides users with a comprehensive breakdown of their spending, making it easier to track and manage their finances.
Traditionally, transaction categorization relies on MCC codes, or "Merchant Category Codes", which are four-digit identifiers assigned to businesses to help credit and debit card companies categorise transactions. The problem is that many banking apps solely depend on these codes, which can result in basic or mismatched data about what you're actually buying.
Our approach goes beyond just using MCC codes. We leverage AI and machine learning to ensure the highest accuracy in transaction data, with 95% success rate. Instead of grouping transactions into basic categories, we create a more granular structure, breaking down spending into specific sub-categories. Plus, we offer custom attributes, giving businesses the flexibility to define categories that align with their unique needs.
How Do Banks Benefit from Transaction Data Categorization
Smart Categorization, designed with a consumer-first approach, is transforming the way users interact with their banking apps. It provides users with a visual breakdown of where their money is going, offering valuable spending insights that help them manage their finances more effectively.
Snowdrop's Transaction Data Enrichment API streamlines and simplifies the experience. Users can create unlimited custom categories, enabling them to dive deeper into their spending patterns. Give customers the tools to manage their money with confidence and clarity.
Integrating location data enhances categories, creating even more enriched insights into consumer behaviour. Together, these features allow consumers to visualise on a map where they spend the most time and money. This combination also aids in early fraud detection. Specifically, when users can see exactly where a transaction occurred, it becomes easier to identify suspicious activity and report it to the bank’s fraud department.
