Summary
Nance automatically categorizes transactions using AI, rules, and learning from your edits—and also suggests contacts based on UPI transactions to improve accuracy.
How This Works in Nance
Nance combines AI + rule-based logic + user behavior to categorize transactions and enrich them with meaningful context.
1. Merchant & Transaction Analysis
- Nance analyzes:
- Merchant name
- Bank narration
- Transaction context
- Based on this, it assigns a category and subcategory
2. Category as the Source of Truth
- Every transaction is assigned:
- One category
- One subcategory
- This keeps insights, budgets, and reports consistent and reliable
3. Learning from Your Edits
- When you change a category or contact:
- Nance learns from that behavior
- Repeated patterns improve future predictions
- Over time, categorization becomes more personalized
4. UPI-Based Contact Suggestions
- For UPI transactions, Nance can:
- Detect identifiers (name/handle) from the transaction
- Suggest or auto-assign a contact
- This helps:
- Better identify who you paid or received money from
- Improve grouping and search accuracy
5. Smart Suggestions (Confidence-Based)
- Nance suggests categories and contacts based on:
- Past transactions
- Repeated patterns
- Auto-application happens only when confidence is high
What Happens If It’s Wrong
- You can edit:
- Category
- Subcategory
- Contact
- Your corrections directly improve future suggestions
Important to Know
Categorization works across:
- Bank transactions
- Credit card transactions
- Cash transactions (once added)
It doesn’t just read transactions.
It learns who, what, and why.