| --- |
| license: mit |
| task_categories: |
| - tabular-classification |
| - audio-classification |
| tags: |
| - fraud-detection |
| - finance |
| - synthetic |
| - multi-modal |
| pretty_name: Fraud Detector Dataset |
| --- |
| |
| # Fraud Detector Dataset |
|
|
| Synthetic multi-modal dataset created for the **Reply / ReplyMirror Fraud Detection Challenge**. It simulates real-world banking activity across five data types — transactions, users, locations, communications, and audio calls — designed to support fraud detection research combining tabular, textual, geospatial, and audio signals. |
|
|
| The companion system that consumes this data is available at [Honi05/Fraud-Detector](https://github.com/Honi05/Fraud-Detector). |
|
|
| --- |
|
|
| ## Dataset Structure |
|
|
| ` |
| FraudDetector/ |
| ├── transactions.csv |
| ├── users.json |
| ├── locations.json |
| ├── sms.json |
| ├── mails.json |
| └── audio/ |
| └── *.mp3 (48 files) |
| ` |
| |
| --- |
|
|
| ## File Descriptions |
|
|
| ### ransactions.csv |
| The core file. Contains individual financial transactions with fields for transaction ID, amount, timestamp, merchant, and other contextual attributes. This is the primary target file — fraud predictions are made at the transaction level. |
|
|
| ### users.json |
| User profile records. Includes demographic and account information for each customer. Used to build behavioral baselines and detect deviations from a user's normal activity patterns. |
|
|
| ### locations.json |
| Geolocation records linked to transactions or user activity. Used to flag geographical inconsistencies such as impossible travel sequences or transactions in unusual regions. |
|
|
| ### sms.json |
| SMS message logs associated with users. Analyzed for phishing indicators, suspicious links, and fraud-related language patterns using LLM-based text scoring. |
|
|
| ### mails.json |
| Email logs per user. Similar to SMS — processed for social engineering cues, fraud language, and anomalous communication behavior. |
|
|
| ### udio/ (48 MP3 files) |
| Recorded phone call segments named by timestamp and participant (e.g., 20870117_010505-jolanda_orsini.mp3). Intended for voice-based fraud signal extraction. |
|
|
| --- |
|
|
| ## Usage |
|
|
| This dataset is used as input to a multi-agent fraud detection pipeline: |
|
|
| `ash |
| python main.py --data ./data --output ./output/predictions.txt |
| ` |
|
|
| The pipeline ingests all five modalities and produces a ranked list of flagged transaction IDs. |
|
|
| --- |
|
|
| ## Team |
|
|
| **Masala Techii** — Owais Mehboob, Sanya Khan, Honi Arora |
|
|
