Case Study

Corporate Risk Early Warning

Analytical intelligence for monitoring public signals of risk, compliance and governance.

Corporate Risk Early Warning

Overview

Corporate early warning system that transforms news and public signals into risk, compliance, governance and reputation indicators.

Challenge

Corporate crises rarely emerge from a single isolated event. They often evolve from dispersed public signals such as financial pressure, executive changes, investigations, reputational controversies and regulatory exposure.

Solution

An interactive dashboard was developed with automated public news collection, risk signal classification, category scoring, alerts and an explainability layer using Machine Learning and local AI.

Impact

  • Early monitoring of public corporate risk signals
  • Explainable classification across risk, compliance and governance categories
  • Executive analysis support with indicators, alerts and audit trail

Tech Stack

PythonStreamlitPlotlyScikit-learnOllamaLinux VPS

Project Details

Corporate Risk & Compliance Dashboard

🎯 Project Objective

Practical study case focused on corporate risk monitoring, early warning indicators, public news signal detection, compliance, governance and executive dashboarding.

📅 Development Timeline

Project start date: 24/04/2026

🛠️ Technologies Used

Python — data ingestion, automation, risk logic and machine learning.

Streamlit — rapid interactive dashboard development.

Pandas — transformation, consolidation and time-series analysis.

Plotly — interactive charts and monitoring visuals.

Google News RSS — public source for corporate signals.

Rule Engine — custom risk classification logic.

Scikit-learn — experimental secondary model.

Ollama / Local LLM — AI summaries and explanations.

⚠️ Disclaimer

This dashboard was created exclusively for educational, study and portfolio purposes. It should not be used as the sole basis for investment decisions, credit analysis, financial recommendations or real-world risk judgments.