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---
license: mit
language:
- en
library_name: transformers
pipeline_tag: text-generation
tags:
- banking
- sms
- json
- parser
- financial
- india
datasets:
- synthetic
widget:
- example_title: "Transaction SMS"
text: "Sent Rs.1500.00 from HDFC Bank AC XX1234 to john@okicici on 15-Aug-25.UPI Ref 123456789012."
- example_title: "Credit SMS"
text: "Rs.25000 credited to your SBI Bank a/c XX5678 via NEFT from beneficiary COMPANY LTD."
---
# Banking SMS JSON Parser V8
Advanced AI model that converts Indian banking SMS messages into structured JSON format.
## Features
- ✅ Detects transaction vs non-transaction messages
- ✅ Extracts amount, date, transaction type, last 4 digits
- ✅ Categorizes transactions into 32+ categories
- ✅ Handles unknown merchants with "Other" category
- ✅ Supports UPI, NEFT, RTGS, Card transactions
- ✅ 60,000+ training samples with realistic Indian banking patterns
## Usage
## Training Data
- 60,000 training samples
- 6,000 validation samples
- 75% transaction, 25% non-transaction messages
- Realistic Indian banking SMS patterns
- Major Indian banks: ICICI, HDFC, SBI, Kotak, Axis, BOB, YES, etc.
## Performance
Optimized for high accuracy on real-world Indian banking SMS messages with proper category classification and transaction detection.
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