RESOLUTION BAZAAR

{

"agentName": "Risk Assessment and Prediction Agent (RAPA)",
"agentDescription": "Evaluates the overall fraud risk profile of the corporate debtor by synthesizing data from financial statements, transactions, internal controls, and external benchmarks. Uses statistical models and machine learning to predict areas with a higher probability of fraudulent activities, helping prioritize forensic audit efforts. *This agent assesses risk and likelihood, it does not guarantee detection of fraud.*",
"version": "1.0",
"status": "Conceptual",
"goals": [
  "Develop a holistic fraud risk assessment score or profile for the corporate debtor.",
  "Analyze historical data patterns to identify indicators predictive of fraudulent behavior.",
  "Integrate findings from other agents (e.g., TPRA, FSAA) as risk indicators.",
  "Compare the debtor's risk indicators against industry benchmarks and known fraud schemes.",
  "Predict specific accounts, business processes, or time periods with elevated risk of containing fraudulent activities.",
  "Generate prioritized recommendations for audit focus based on quantitative risk assessment.",
  "Continuously refine predictive models as more data becomes available.",
  "Support the development of a risk-based audit plan."
],
"keyCapabilities": [
  "Data Aggregation: Consolidates inputs from financial statement analysis (FSAA), transaction analysis (TPRA), document analysis (DAVA), internal control assessments, and external data sources.",
  "Risk Factor Identification & Weighting: Identifies and assigns significance to known fraud risk factors (e.g., management pressure, opportunity, rationalization indicators, specific financial ratios, control weaknesses).",
  "Statistical Modeling: Uses techniques like regression analysis to correlate risk factors with potential fraud likelihood.",
  "Machine Learning Prediction: Employs supervised learning models (if trained on historical fraud data) or unsupervised models (anomaly detection on risk indicators) to predict high-risk segments.",
  "Benchmarking: Compares debtor's risk indicators against relevant industry statistics or peer group data.",
  "Fraud Risk Scoring Engine: Calculates composite risk scores for different segments (e.g., revenue cycle, procurement, specific accounts).",
  "Scenario Analysis (What-if): Potentially models how changes in certain factors might impact the overall risk profile.",
  "Prioritization Algorithm: Ranks areas for audit attention based on predicted risk and potential impact.",
  "Explainable AI (XAI): Provides insights into which factors are most influential in driving the risk prediction for a specific area.",
  "Dynamic Risk Monitoring: Can potentially update risk assessments periodically as new data flows in during the audit."
],
"targetUsers": [
  "Forensic Auditors",
  "Audit Managers / Partners",
  "Insolvency Professionals / Resolution Professionals / Liquidators (in determining audit scope)",
  "Internal Audit Risk Assessment Teams"
],
"inputDataRequirements": [
  "Outputs from FSAA (anomaly reports, ratio analysis).",
  "Outputs from TPRA (flagged transactions, pattern analysis).",
  "Outputs from DAVA (suspicious document reports).",
  "Financial Statements (multiple periods).",
  "Internal Control Assessment Reports / Narratives.",
  "Information on management structure, incentives, and turnover.",
  "List of Related Parties.",
  "Industry fraud benchmarks / risk statistics.",
  "Historical data on fraud incidents within the company or industry (if available).",
  "Corporate structure information.",
  "News and external sentiment data related to the debtor (Optional)."
],
"outputFormats": [
  "Overall Fraud Risk Assessment Report (PDF, HTML).",
  "Risk Scorecard/Dashboard showing scores across different dimensions.",
  "Heatmap visualizing high-risk areas/processes/periods.",
  "Prioritized list of audit areas/tests recommendation.",
  "Report detailing key risk factors identified and their contribution.",
  "Predictive Model Insights (e.g., feature importance from XAI).",
  "Structured data export (JSON, CSV) of risk scores and factors."
],
"potentialBenefits": [
  "Focuses limited audit resources on areas with the highest probability of fraud.",
  "Provides an objective and data-driven basis for scoping the forensic audit.",
  "Enhances the potential effectiveness of the audit by prioritizing intelligently.",
  "Helps in early identification of systemic risks or control deficiencies.",
  "Supports communication of audit strategy based on quantifiable risk.",
  "Can adapt to new information gathered during the audit to dynamically adjust focus."
],
"requiredTools": [
  {
    "toolCategory": "Data Acquisition & Integration",
    "tools": [
      "Database Connectors (SQL)",
      "API Clients (to pull data from other agents or systems)",
      "Spreadsheet/File Parsers"
    ]
  },
  {
    "toolCategory": "Data Processing & Analysis",
    "tools": [
      "Data Manipulation Libraries (Pandas, Dask, Spark - for potentially large datasets)",
      "Statistical Libraries (SciPy, StatsModels - for statistical modeling)"
    ]
  },
  {
    "toolCategory": "Machine Learning & AI",
    "tools": [
      "Core ML Frameworks (Scikit-learn - for regression, classification, clustering)",
      "Deep Learning Frameworks (Optional, for complex pattern recognition)",
      "Explainable AI (XAI) Libraries (SHAP, LIME)",
      "Model Management Platforms (MLflow, Weights & Biases - for tracking experiments and models)",
      "Rule Engines (Optional, for encoding explicit expert rules)"
    ]
  },
  {
    "toolCategory": "Data Storage",
    "tools": [
      "Relational Databases (PostgreSQL, MySQL - for storing risk factors, scores, model results)",
      "Data Warehouses / Data Lakes (for large integrated datasets)"
    ]
  },
  {
    "toolCategory": "Reporting & Visualization",
    "tools": [
      "Data Visualization Libraries (Matplotlib, Seaborn, Plotly, NetworkX for relationship viz)",
      "Business Intelligence Tools (Tableau, Power BI - for dashboards)",
      "Reporting Libraries (ReportLab for PDFs)"
    ]
  },
  {
    "toolCategory": "Workflow Orchestration",
    "tools": [
      "Workflow Management Tools (Airflow, Prefect)"
    ]
  }
]

}