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Fraud Intelligence Platform

Transparent. Explainable. Deterministic.

An open-source ecosystem of fraud intelligence projects covering fraud detection, investigations, explainable decision engines, device risk intelligence, regulatory mapping, and operational tooling.

Built by Gururaj G J

License: MIT GitHub LinkedIn

Live site: gururaj-gj-g.github.io/fraud-intelligence-platform


Platform at a Glance

Metric Value
Public repositories 9
Interactive demos 6
Decision engines 2
Investigation tools 3
License MIT

Why this platform exists

Most fraud repositories demonstrate isolated concepts. This platform brings together decisioning, investigations, analytics, device intelligence, regulatory mapping, and operational controls into a cohesive ecosystem of explainable fraud intelligence projects.

Every component is designed to be transparent, auditable, and human-review first.


Platform Modules

Decision Intelligence

Investigation

Operations

Intelligence

Governance


Live Demos

Project Live Demo Repository
Fraud Investigation Canvas Launch GitHub
Fraud Analytics Dashboard Launch GitHub
Emergency Outflow Lock Launch GitHub
Android Device Risk SDK Launch GitHub
Regulator Intelligence Library Launch GitHub
ATO Investigation Standard Launch GitHub

Architecture

                   Fraud Intelligence Platform

                           Signals
                              │
                              ▼
                 Deterministic Decision Engine
                              │
      ┌───────────────────────┼────────────────────────┐
      ▼                       ▼                        ▼
 Investigation Canvas   Analytics Dashboard   Regulator Library
      │                       │                        │
      └───────────────┬───────┴────────┐               │
                      ▼                ▼               ▼
             Emergency Lock     Device Risk SDK   AI Agent Risk

See docs/architecture.md for the full design rationale and data flow.


Core Principles

  • Transparent decision-making — Every score and decision can be inspected
  • Deterministic risk scoring — Same inputs always produce the same outputs
  • Explainable outputs — Human-readable reasons accompany every decision
  • Human-review first — Systems assist investigators; they do not replace them
  • Audit-ready decisions — Full decision trails for compliance and review
  • Synthetic demonstration data — Safe, non-sensitive data for demos
  • Open standards — Designed for interoperability and inspection
  • Privacy-conscious design — Minimal data collection, clear purpose limitation

Core Technologies

Python · FastAPI · JavaScript · HTML5 · Chart.js · Kotlin · GitHub Pages · REST APIs · Explainable AI · Fraud Detection · Risk Scoring · Graph Analysis


Roadmap

Status Item
Explainable Decision Engine
Investigation Canvas
Analytics Dashboard
Device Risk SDK
Emergency Outflow Lock
Regulatory Intelligence
ATO Investigation Standard
AI Agent Risk Suite
Case Replay Engine
Network Intelligence
Graph Database Integration
Live API Gateway
SaaS Portal

Full details in docs/roadmap.md.


Getting Started

Each repository is self-contained. Clone any project and follow its README.

git clone https://github.com/Gururaj-GJ-G/fraud-investigation-canvas.git

For the Python decision engines:

cd deterministic-fraud-signal-engine
pip install -r requirements.txt
uvicorn main:app --reload

Screenshots

Add product screenshots to the screenshots/ folder (see screenshots/README.md). Once added, they will appear on the GitHub Pages site and can be referenced here.


License

All projects in this ecosystem are released under the MIT License.


Contact


Fraud Risk · Merchant Risk · Financial Crime · Trust & Safety

About

Open-source fraud intelligence platform showcasing explainable decision engines, investigation tooling, regulatory intelligence, and interactive demos.

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