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Documentation Index

Fetch the complete documentation index at: https://docs.finwatch.finance/llms.txt

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The Problem: Siloed Logic in a High-Speed World
GitOps for Real-Time Risk & Automation
In most financial technology companies, the logic that drives risk, compliance, and operations is disconnected from the modern software development lifecycle. It lives in clunky UI-driven systems, spreadsheets, or opaque, third-party black boxes. This creates critical problems:  It’s Slow: Adapting to a new fraud vector or launching a new pricing model is bottlenecked by manual processes and vendor dependency. It’s Risky: Changes are often made without rigorous testing or peer review, leading to costly production errors. It’s Opaque: Auditing who changed what, when, and why is a painful, manual exercise.  FinWatch is built on a fundamentally different philosophy. We believe that your company’s most critical business logic should be treated with the same rigour, transparency, and automation as your core application code.

The FinWatch Difference: A Developer-First Engine

FinWatch is not just a tool; it’s a programmable, developer-first engine. By representing all rules as simple, text-based scripts (‘.ws’ files), we unlock the entire modern software development toolchain for your financial, risk and operational logic.
  1. It Enables “GitOps for Risk and Compliance”
    This is the cornerstone of the FinWatch approach. Because rules are just code, you can manage them with a “GitOps” workflow, bringing unprecedented safety and velocity to your risk operations.
  2. Version Control & Perfect Audit Trail Every change to a rule is a commit in Git. This provides a perfect, immutable audit trail for regulators, answering who changed what*, when*, and why with cryptographic certainty.
  3. Rigorous Peer Review A new rule or a change to a risk threshold can be submitted as a pull request. This enables collaborative peer review from developers, analysts, and business stakeholders, ensuring every change is vetted before it reaches production.
  4. Automated Testing (CI/CD) You can build a CI/CD pipeline for your rules. Before deploying a change, automatically test it against a dataset of historical transactions. This allows you to:
    • Measure the financial impact of a rule.
    • Calculate the precise false positive rate.
    • Ensure the change doesn’t have unintended consequences.
This transforms risk management from a reactive, manual process into a proactive, automated, and engineering-driven discipline. 

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It’s an Extensible Engine, Not Just a Tool

Most transaction monitoring systems are built for a single purpose. FinWatch is designed as a powerful, extensible building block for developers. The ‘then’ action in a rule is not limited to ‘block’ or ‘review’. Developers can easily extend the engine to create custom actions eg:
  • Trigger a webhook: to a Slack channel or PagerDuty for real-time alerts.
  • Call a different microservice to apply a dynamic fee or adjust a customer’s risk score.
  • Enrich transaction data by calling a third-party KYC or geolocation API.
  • Publish an event to a Kafka stream for deeper, asynchronous analysis.
This extensibility turns FinWatch from a compliance cost centre into a value-add platform for automating business-critical logic across your entire organisation.