Marble is an open-source real-time decision engine designed for financial institutions, fintechs, and crypto exchanges to combat fraud and meet AML compliance requirements. Unlike proprietary solutions like ComplyAdvantage or Actimize, Marble offers full transparency and control over detection logic, data flow, and infrastructure. It enables organizations to build custom transaction monitoring systems, screen customers against global sanctions and PEP lists, and automate investigations—all while keeping sensitive data on-premises. With a rule-based engine and AI-assisted workflows, Marble is tailored for teams that need precision, auditability, and integration flexibility without vendor lock-in.
Built by a team with deep expertise in RegTech, Marble serves over 100 organizations across 15+ countries. It is ideal for compliance officers, data engineers, and fraud analysts who need to customize detection rules, integrate with internal systems (like core banking or KYC platforms), and maintain full ownership of their data. The platform supports both self-hosted deployment and licensed SaaS options, with a fully functional open-source core that removes the need for expensive third-party subscriptions.
What You Get
- Real-time Transaction Monitoring - Monitor transactions in real time or post-trade using a customizable data model that mirrors your data warehouse and integrates with core banking systems and third-party tools.
- Customer and Company Screening - Screen individuals and entities against global sanctions, PEPs, and adverse media lists with daily updates, supporting both real-time and scheduled screening workflows.
- Continuous Monitoring - Automatically re-screen customers against updated lists without manual intervention, ensuring ongoing compliance with evolving regulatory requirements.
- Unified Investigation Suite - Investigate alerts in a centralized case manager with annotations, context tracking, and action history to reduce context switching during fraud investigations.
- AI Automation & Assistance - Leverage AI to accelerate rule building, optimize detection programs, and assist in case investigations by suggesting patterns or relevant data points.
- Embedded Reporting & BI - Access built-in analytics dashboards to track detection program performance and connect directly to your database for custom reporting with BI tools like Power BI or Tableau.
- Audit Trail - Maintain searchable, immutable logs of all detection rules, workflows, and case actions to meet regulatory audit requirements.
- Enterprise-Grade Governance - Enforce security with role-based access control (RBAC), SSO via OpenID Connect, IP whitelisting, and SOC 2 Type II certification.
- Self-Hosted Option - Deploy Marble on your own infrastructure to ensure data never leaves your environment, with full control over configuration and updates.
Common Use Cases
- Building a multi-tenant SaaS platform with AML compliance - Fintechs use Marble to embed real-time transaction monitoring and customer screening into their platforms, ensuring each tenant has isolated rulesets while maintaining a unified backend.
- Scaling AML operations for crypto exchanges - Crypto firms deploy Marble to screen on-chain transactions and wallet addresses against global sanctions lists in real time, reducing false positives through custom rule tuning.
- Replacing expensive proprietary AML tools with open-source control - Banks and mid-sized institutions replace ComplyAdvantage or Actimize by using Marble’s transparent rule engine to customize detection logic and reduce licensing costs.
- DevOps teams managing compliance across hybrid clouds - Engineering teams use Marble’s self-hosted deployment to enforce compliance policies consistently across AWS, Azure, and on-prem environments with centralized rule management.
Under The Hood
The project is a cloud-native infrastructure and application deployment framework designed to support flexible, multi-environment deployments across Kubernetes, Terraform-based infrastructures, and bare-metal setups. It emphasizes modular architecture, containerization, and integration with Firebase and Google Cloud services for scalable and reproducible systems.
Architecture
This system adopts a modular, multi-layered structure that enables deployment across diverse environments with clear separation of concerns.
- The system is organized into backend, frontend, and cron services, each with dedicated deployment artifacts such as Helm charts
- Data processing, user interface, and infrastructure provisioning are distinctly separated into modular components
- Configuration management and environment-specific setups support flexible deployment targets across cloud providers
- Containerization and orchestration patterns are central to ensuring scalable and consistent deployments
Tech Stack
It leverages HCL and Terraform for infrastructure automation, with a strong emphasis on cloud-native development practices.
- The tech stack is built around HCL for configuration management and includes HTML templates for frontend components
- Integrations with Firebase and Google Cloud services reflect a modern, cloud-first development approach
- Docker and Kubernetes form the core of its deployment and orchestration tooling, complemented by Makefiles for automation
- CI/CD pipelines are present, indicating a commitment to automated validation and deployment workflows
Code Quality
While the project shows some structural clarity, it suffers from limited testing practices and inconsistent code standards.
- The absence of test files highlights a lack of automated testing, which is critical for maintaining reliability
- Error handling is basic and not consistently applied across the codebase, increasing risk of unhandled failures
- Code style and naming conventions vary significantly, with no clear standards or linting enforcement in place
- Lack of linting tools and structured code reviews suggests potential for growing technical debt over time
What Makes It Unique
This project distinguishes itself through its modular and extensible architecture tailored for multi-cloud and hybrid environments.
- A modular Helm chart system enables flexible deployment across Kubernetes, Firebase, and various cloud providers like AWS and GCP
- Comprehensive Terraform templates and Kubernetes manifests support multi-cloud infrastructure provisioning
- The inclusion of Firebase emulator setup allows for local development and testing without external dependencies
- Detailed documentation and tailored installation guides make it accessible for different deployment scenarios including bare metal and production environments