Transaction Categorization API
Empower your users with personalised spending insights. Our machine learning models deliver accurate and tailored categories and tags, helping your clients understand their finances at a deeper level.
Expanding beyond MCC codes
| Our merchant transaction categorization system bypasses the use of traditional merchant category codes (MCC), leveraging instead advanced machine learning (ML) and artificial intelligence (AI) technologies. | |
| By analysing individual merchant data in detail, the system assigns each business a precise category, along with additional contextual insights about the merchant’s activities. | |
| This approach ensures a detailed, accurate, and nuanced understanding of transaction data and customer insights. |
Unlocking Multilevel Categorization with Custom Attributes
Brand Aggregation
Effortlessly generate insights on brands by consolidating sub-brands expenditures
Merchant Categories
Flexible and comprehensive transaction categorization system that provides a detailed and accurate reflection of spending behaviour
Enhanced Search
Simplified search and improved visibility with granular categories and attributes
Benefits of Transaction Categorization
For the end-user
| Enhanced user experience: Increase your customer engagement by providing tailored solutions. | |
| Enable better financial management: Provide customers with a visual representation of their primary spending areas. | |
| Provide better insights: Enable your customers to better understand their finances, and explore trends and spending habits. |
For the bank
| Develop targeted products and offers: Facilitate the development of specific and targeted products, offers, and solutions based on consumption habits. | |
| Build brand loyalty: And trust through personalised offerings and enhanced customer satisfaction. | |
| Establish yourself as a digital leader: By showcasing innovation and providing customers with enhanced financial insights and user-centric services. |
Explore more MRS API features
Transaction Location
Add precise geo-enrichment data to each transaction.
Accurate Logos & Names
Empower your users to identify their transactions more easily.
Contact Details
Facilitate the resolution of unknown transaction queries.
Eco Footprint Tracking
Foster more sustainable consumption habits.
Upgrade your payment data with transaction categorization API for richer financial insights
How does categorization work?
“Categorization” is a way for banking apps to group transactional data within the app, giving clients and banks the opportunity to see where money is being spent. Usually, this is done using “Merchant Category Codes (MCCs)”, an approach that gives rudimentary data and is often mismatched to the product or service. MRS makes MCCs redundant by leveraging machine learning (ML) and artificial intelligence (AI) technologies.
How does MRS enhance personal finance management?
MRS provides a clear and intuitive breakdown of transactions, which helps customers track their spending more effectively, identify potential savings areas, and adhere to their budgeting goals.
How can Snowdrop Solutions help?
Our MRS API takes it a step further and comes back with clean code that accurately matches the business’s name, location, and transaction category with a 95% success rate. We analyse individual merchant data in detail, assigning each business a precise category, along with additional contextual insights about the merchant’s activities. This approach ensures a detailed, accurate, and nuanced understanding of transaction data and customer insights.