Public Sector — Risk Model Drift Monitoring Pipeline

Overview

The Risk Model Drift Monitoring Pipeline is designed to ensure the reliability of risk models used in the public sector by continuously monitoring their performance. The primary purpose of this DAG is to detect any drifts in model performance that may impact supply and demand forecasts. The data sources include production data from various public sector databases and results from existing risk models. The ingestion pipeline begins with the collection of relevant metrics from these sources, which

The Risk Model Drift Monitoring Pipeline is designed to ensure the reliability of risk models used in the public sector by continuously monitoring their performance. The primary purpose of this DAG is to detect any drifts in model performance that may impact supply and demand forecasts. The data sources include production data from various public sector databases and results from existing risk models. The ingestion pipeline begins with the collection of relevant metrics from these sources, which are then processed through a series of analytical steps. The processing steps involve analyzing the collected performance metrics to identify any significant deviations from expected outcomes. This analysis is crucial for maintaining the accuracy of forecasts and ensuring that risk models remain aligned with current conditions. Quality control measures are implemented to verify the accuracy and relevance of alerts generated during this process. These controls include threshold checks and validation against historical performance data. The outputs of this DAG are presented through a comprehensive dashboard that provides insights and alerts to analysts, enabling them to take proactive measures in response to detected drifts. Key performance indicators (KPIs) are monitored throughout the process, including alert frequency, model accuracy, and response times to detected issues. The business value of this pipeline lies in its ability to enhance the reliability of risk assessments, ultimately supporting better decision-making in public sector operations.

Part of the Supply/Demand Forecast solution for the Public Sector industry.

Use cases

• Improved accuracy in supply and demand forecasts
• Enhanced decision-making capabilities for public sector stakeholders
• Proactive identification of potential model failures
• Increased trust in risk management processes
• Streamlined reporting and compliance with regulatory standards