RESOLUTION BAZAAR

{

"agentName": "Insolvency Risk Prediction Agent (IRPA)",
"agentDescription": "Leverages machine learning models trained on historical financial data, qualitative factors, and industry benchmarks to predict the probability of corporate insolvency within a defined timeframe. Aims to provide early warnings and support strategic decision-making for risk mitigation and insolvency management.",
"version": "1.0",
"status": "Conceptual",
"goals": [
  "Accurately predict the likelihood (probability) of corporate insolvency over specific future time horizons (e.g., 1 year, 2 years).",
  "Identify key financial and non-financial drivers contributing to predicted insolvency risk for specific debtors.",
  "Provide timely and actionable risk scores and classifications.",
  "Continuously monitor debtor performance and update predictions.",
  "Facilitate the development of proactive risk mitigation strategies.",
  "Support scenario analysis and stress testing based on insolvency predictions."
],
"keyCapabilities": [
  "Data Ingestion and Preprocessing: Collects and cleans diverse historical data relevant for prediction.",
  "Feature Engineering: Creates relevant predictive features from raw financial, market, and qualitative data.",
  "Machine Learning Model Training: Trains various classification models (e.g., Logistic Regression, SVM, Gradient Boosting Machines, Neural Networks) on historical insolvency data.",
  "Model Validation and Backtesting: Rigorously tests model performance using historical data and appropriate metrics (AUC, Precision, Recall, F1-Score).",
  "Probability Scoring: Generates a calibrated probability score indicating the likelihood of insolvency.",
  "Risk Classification: Categorizes debtors into risk levels based on predicted probability (e.g., Low, Medium, High, Critical).",
  "Explainable AI (XAI): Provides insights into the factors driving a specific prediction (e.g., using SHAP or LIME).",
  "Benchmarking: Compares a debtor's predicted risk against industry or peer group benchmarks.",
  "Automated Monitoring and Alerting: Continuously processes new data to update predictions and trigger alerts when risk thresholds are breached.",
  "Reporting: Generates reports summarizing predictions, key risk drivers, and trends."
],
"targetUsers": [
  "Credit Risk Managers",
  "Loan Officers",
  "Investment Analysts",
  "Portfolio Managers",
  "Chief Financial Officers (CFOs)",
  "Treasury Departments",
  "Restructuring Advisors",
  "Insolvency Practitioners",
  "Regulatory Bodies"
],
"inputDataRequirements": [
  "Historical Financial Statements (multiple periods for time-series analysis)",
  "Market Data (Stock price volatility, credit default swap spreads, bond yields)",
  "Macroeconomic Indicators (GDP growth, inflation, interest rates, unemployment)",
  "Industry-Specific KPIs and Benchmarks",
  "Payment History Data",
  "Director/Management Information (e.g., turnover)",
  "News Sentiment Data (Optional, requires NLP)",
  "Historical Insolvency/Default Labels (Crucial for supervised model training)"
],
"outputFormats": [
  "Insolvency Probability Score (e.g., 0.0 - 1.0)",
  "Risk Category/Classification Label",
  "Predicted Time Horizon for Insolvency Risk",
  "List of Top Predictive Factors/Drivers (from XAI)",
  "Confidence Intervals for Predictions",
  "JSON/API output for system integration",
  "PDF/HTML Analytical Reports",
  "CSV exports of predictions and features",
  "Dashboard Visualizations"
],
"potentialBenefits": [
  "Enhanced accuracy in predicting defaults and bankruptcies compared to traditional methods.",
  "Earlier identification of companies heading towards financial distress.",
  "More effective allocation of monitoring and mitigation resources.",
  "Improved loan pricing and provisioning.",
  "Data-driven support for strategic decisions (e.g., divestment, intervention, restructuring).",
  "Reduced financial losses due to unforeseen insolvencies.",
  "Increased operational efficiency in risk management."
],
"requiredTools": [
  {
    "toolCategory": "Data Acquisition",
    "tools": [
      "Financial Data APIs (e.g., Bloomberg API, Refinitiv Eikon API, FactSet API, S&P Capital IQ API, XBRL processors)",
      "Web Scraping Tools (for news, alternative data)",
      "Database Connectors (SQL, NoSQL)"
    ]
  },
  {
    "toolCategory": "Data Processing & Feature Engineering",
    "tools": [
      "Data Processing Libraries (e.g., Pandas, Dask, Spark)",
      "Numerical Computation Libraries (e.g., NumPy)",
      "Feature Engineering Libraries (e.g., Featuretools, Scikit-learn's preprocessing modules)"
    ]
  },
  {
    "toolCategory": "Machine Learning & AI",
    "tools": [
      "Core ML Frameworks (e.g., Scikit-learn, XGBoost, LightGBM, CatBoost)",
      "Deep Learning Frameworks (Optional, e.g., TensorFlow, PyTorch, Keras - for complex patterns or sequential data)",
      "Explainable AI (XAI) Libraries (e.g., SHAP, LIME)",
      "Statistical Libraries (e.g., StatsModels, SciPy)",
      "Hyperparameter Optimization Libraries (e.g., Optuna, Hyperopt, Scikit-Optimize)"
    ]
  },
  {
    "toolCategory": "Data Storage",
    "tools": [
      "Relational Databases (e.g., PostgreSQL, MySQL - for structured data and labels)",
      "Data Warehouses / Data Lakes (e.g., Snowflake, Redshift, BigQuery, Databricks Lakehouse - for large historical datasets)"
    ]
  },
  {
    "toolCategory": "Model Management & Deployment",
    "tools": [
      "Experiment Tracking Platforms (e.g., MLflow, Weights & Biases)",
      "Model Serving Frameworks (e.g., FastAPI, Flask, TensorFlow Serving, TorchServe)",
      "Containerization (e.g., Docker)",
      "Orchestration (e.g., Kubernetes)",
      "Cloud ML Platforms (e.g., AWS SageMaker, Google Vertex AI, Azure Machine Learning)"
    ]
  },
  {
    "toolCategory": "Visualization & Reporting",
    "tools": [
      "Data Visualization Libraries (e.g., Matplotlib, Seaborn, Plotly)",
      "Business Intelligence Platform APIs (e.g., Tableau, Power BI)",
      "Reporting Libraries (e.g., ReportLab for PDFs)"
    ]
  },
  {
    "toolCategory": "Workflow Orchestration",
    "tools": [
      "Workflow Management Tools (e.g., Airflow, Prefect, Dagster)"
    ]
  },
  {
     "toolCategory": "Alerting & Notification",
     "tools": [
       "Messaging Services (e.g., APIs for Email, SMS, Slack)"
    ]
  }
]

}