honi05/FraudDetector

1---2license: mit3task_categories:4  - tabular-classification5  - audio-classification6tags:7  - fraud-detection8  - finance9  - synthetic10  - multi-modal11pretty_name: Fraud Detector Dataset12---13 14# Fraud Detector Dataset15 16Synthetic 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.17 18The companion system that consumes this data is available at [Honi05/Fraud-Detector](https://github.com/Honi05/Fraud-Detector).19 20---21 22## Dataset Structure23 24`25FraudDetector/26├── transactions.csv27├── users.json28├── locations.json29├── sms.json30├── mails.json31└── audio/32    └── *.mp3  (48 files)33`34 35---36 37## File Descriptions38 39### 	ransactions.csv40The 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.41 42### users.json43User 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.44 45### locations.json46Geolocation records linked to transactions or user activity. Used to flag geographical inconsistencies such as impossible travel sequences or transactions in unusual regions.47 48### sms.json49SMS message logs associated with users. Analyzed for phishing indicators, suspicious links, and fraud-related language patterns using LLM-based text scoring.50 51### mails.json52Email logs per user. Similar to SMS — processed for social engineering cues, fraud language, and anomalous communication behavior.53 54### udio/ (48 MP3 files)55Recorded phone call segments named by timestamp and participant (e.g., 20870117_010505-jolanda_orsini.mp3). Intended for voice-based fraud signal extraction.56 57---58 59## Usage60 61This dataset is used as input to a multi-agent fraud detection pipeline:62 63`ash64python main.py --data ./data --output ./output/predictions.txt65`66 67The pipeline ingests all five modalities and produces a ranked list of flagged transaction IDs.68 69---70 71## Team72 73**Masala Techii** — Owais Mehboob, Sanya Khan, Honi Arora74